4.- Contact Center Configuration Call Routing & Message Routing Call Routing Navigation: Admin → Routing → Call Routing Message Routing Navigation: Admin → Routing → Message Routing Overview Both Call Routing and Message Routing serve the same fundamental purpose: mapping an inbound address to an Architect flow . The difference is the channel. Feature Call Routing Message Routing Channel Voice (inbound phone calls) Digital (SMS, web messaging, messaging apps) Entry point Inbound telephone number (DID) Inbound messaging address or number Flow type Inbound Call Flow Inbound Message Flow Schedule support Yes — via Schedule Groups No — message flows handle scheduling internally Emergency support Yes — via Emergency Groups No Admin location Admin → Routing → Call Routing Admin → Routing → Message Routing Call Routing What Is a Call Route? A Call Route connects an inbound telephone number to an Architect inbound call flow , with optional schedule-based and emergency routing logic layered on top. When a customer dials a number, Genesys Cloud: Identifies the matching call route Checks if an emergency group is active Evaluates the schedule group (open / closed / holiday) Executes the appropriate Architect flow Call Route Components Component Description Route Name Unique identifier Division Administrative ownership Inbound Numbers The DID(s) assigned to this route Routing Mode Always Open, or Schedule-Based Schedule Group Determines open/closed/holiday logic Open Flow Architect flow during open hours Closed Flow Architect flow during closed hours Holiday Routing Use Closed Flow, Route to Holiday Flow, or Bypass Emergency Group Overrides all routing when activated Emergency Flow Architect flow when emergency is active Routing Mode: Always Open vs. Schedule-Based Mode When to Use Always Open 24/7 operations — one flow handles all calls regardless of time Schedule-Based Business hours operations — different flows for open, closed, and holidays Holiday Routing Options Option Behaviour Use Closed Flow Holiday calls follow the same logic as after-hours Route to Holiday Flow Dedicated holiday Architect flow (custom message) Bypass Holiday Routing Holiday schedules are ignored — treats holiday as a normal day Creating a Call Route Admin → Routing → Call Routing Click Add Enter Route Name and select Division Assign Inbound Numbers (DIDs) Choose Routing Mode : If Always Open: select the single Call Flow If Schedule-Based: select Schedule Group , then assign Open Flow, Closed Flow, and Holiday options Optionally configure Emergency Routing : Enable emergency toggle Select Emergency Group Select Emergency Flow Click Save Call Routing Decision Flow Inbound call arrives on DID ↓ Call Route identified ↓ Emergency Group active? YES → Emergency Flow NO ↓ Always Open? YES → Open Flow NO ↓ Schedule Group evaluation ↓ ┌──────────┬──────────┬──────────┐ │ Open │ Closed │ Holiday │ │ Flow │ Flow │ Flow │ └──────────┴──────────┴──────────┘ Prerequisites Before Creating a Call Route Inbound number (DID) provisioned and available in the org At least one published Architect inbound call flow Schedule Group configured (if using schedule-based routing) Emergency Group created (if emergency routing needed) Call Route Example Setting Value Route Name US_Support_Main Division Customer Support Inbound Number +1-800-555-1234 Routing Mode Schedule-Based Schedule Group US_Support_ScheduleGroup Open Flow Support_IVR_Main Closed Flow Support_AfterHours Holiday Option Route to Holiday Flow Holiday Flow Support_HolidayClosure Emergency Group US_Support_Emergency Emergency Flow Emergency_Announcement Message Routing What Is Message Routing? Message Routing maps an inbound messaging address or number to an Architect inbound message flow . When a customer sends an SMS or web message to a configured address, Genesys routes it to the associated flow for bot handling or agent queue delivery. Message Routing Page Layout The Message Routing page shows two columns: Column Description Inbound Message Flows The Architect flow that will process the message Inbound Address The messaging number or address that triggers the flow Each routing entry links one or more addresses to one flow. Message Routing Components Component Description Inbound Message Flow A published Architect inbound message flow Inbound Address SMS number, web messaging address, or other digital channel address ℹ️ Unlike Call Routing, Message Routing has no built-in schedule group or emergency group fields. Time-based logic for messaging is handled inside the Architect message flow itself using Evaluate Schedule Group actions. Creating a Message Route Admin → Routing → Message Routing Click + (Add) Click Select Flow → begin typing the flow name → select it Click Select Addresses → choose the inbound number(s) or address(es) Click Add Click Save Prerequisites Before Creating a Message Route Messaging channel provisioned (SMS number, web messaging widget, etc.) Published Architect inbound message flow Message Routing Workflow Customer sends message ↓ Messaging channel (SMS / Web Messaging / App) ↓ Inbound address matched ↓ Message Routing entry found ↓ Architect Inbound Message Flow executes ↓ Bot / automation or agent queue Common Message Flow Patterns Pattern Flow Logic Simple queue delivery Send greeting → Transfer to ACD queue Bot self-service Collect intent → automated response → escalate if unresolved Order status Request order number → Data Action lookup → return status Appointment scheduling Collect date/time preference → create callback Message Route Example Setting Value Inbound Message Flow Customer_Service_MessageFlow Inbound Address +1-800-555-8888 Division Customer Service Troubleshooting Call Routing Issue Cause Fix Calls not reaching flow DID not assigned to route Verify inbound number on the call route Wrong flow playing Incorrect schedule group or flow assignment Review schedule group and flow assignments Emergency routing not activating Emergency group not activated Go to Emergency Groups → activate Calls always closed Schedule group time zone wrong Verify time zone on the schedule group Flow not executing Flow is unpublished in Architect Publish the flow Message Routing Issue Cause Fix Messages not reaching flow Address not assigned to routing entry Verify address assignment in message routing Wrong flow triggered Incorrect routing entry Update the message routing entry No automated response Flow not published Publish the Architect message flow Duplicate routing Address assigned to multiple entries Check for conflicting routing entries Key Facts for Exam / Interview Question Answer Where is call routing configured? Admin → Routing → Call Routing What determines open/closed routing for voice? Schedule Groups How do you override all routing for voice calls? Activate an Emergency Group Where is message routing configured? Admin → Routing → Message Routing Does message routing have schedule group support? No — time-based logic is built into the Architect message flow What must exist before creating either route type? A published Architect flow of the matching type See Also Scheduling & Schedule Groups — the schedule groups referenced by call routes Emergency Groups — the override mechanism for call routing Architect Overview — building the inbound call and message flows Prompt Management — audio messages used inside those flows Emergency Groups Navigation: Admin → Routing → Emergency Groups Used by: Call Routing configurations What Are Emergency Groups? An Emergency Group is a switch that overrides all normal schedule-based call routing when activated. When an emergency group is active, inbound calls bypass the schedule group entirely and route directly to a designated emergency call flow. Use cases: office closures, power outages, network failures, natural disasters, building evacuations, planned maintenance requiring full call redirection. ⚠️ Emergency Groups have the highest routing priority. They override Open / Closed / Holiday schedule logic. An active emergency group = all calls go to the emergency flow, regardless of time of day. Emergency Group Components Component Description Name Unique identifier for the group Division Administrative ownership and access scoping Activation Status On = emergency routing active; Off = normal routing Usages Shows which call routes and flows reference this group — critical for impact assessment Creating an Emergency Group Admin → Routing → Emergency Groups Click Add Enter a unique Emergency Group Name Select Division Click Save The group is created in a deactivated state — it has no routing impact until activated. Connecting an Emergency Group to a Call Route Creating the group alone does nothing. It must be assigned to a Call Route: Admin → Routing → Call Routing → open the target route Enable Emergency toggle In the Emergency Group field, select the group you created In the Emergency Flow field, select the published Architect flow to use during emergencies Click Save Activating an Emergency Group When an incident occurs: Admin → Routing → Emergency Groups Find the group Toggle Activation to On Calls immediately begin routing to the emergency flow To restore normal routing: Return to Emergency Groups Toggle Activation to Off ✅ Best practice: Test activation/deactivation during a low-traffic window before a real incident occurs. Know exactly where to find this toggle under pressure. Routing Priority Diagram Incoming Call ↓ Call Route ↓ Emergency Group active? ↓ ┌──── YES ─────────────────────┐ │ Emergency Flow executes │ │ (schedule ignored entirely) │ └──────────────────────────────┘ ↓ NO Schedule Group evaluated ↓ Open / Closed / Holiday → respective flow Common Emergency Flow Designs Simple Closure Announcement Start ↓ Play Emergency Announcement ↓ Disconnect Redirect to Backup Location Start ↓ Play Brief Message ("We are experiencing an outage...") ↓ Transfer to backup contact center DID Alternate Contact Information Start ↓ Play Emergency Message ↓ Provide website / email / alternate number ↓ Disconnect ✅ Keep emergency flows simple. Complex logic is a liability during an outage. The goal is: play a clear message, offer an alternative, end the call. The Usages Field The Usages field on an emergency group shows every call route and Architect flow that references it. Always check this before making changes — it tells you the blast radius of any modification or activation. Naming Convention Format Example __Emergency US_Support_Emergency __Emergency Monterrey_IVR_Emergency Troubleshooting Issue Cause Fix Emergency routing not activating Group not assigned to the call route Edit call route → assign emergency group Group is active but calls still follow normal schedule Emergency flow not assigned to the route Assign the emergency flow on the call route Emergency flow errors out Flow has unpublished changes or broken logic Open Architect, validate, publish latest version Wrong routes affected Unexpected routes also reference the group Check Usages field; scope the group correctly Normal routing not restoring after deactivation Underlying schedule or call route was already misconfigured Test non-emergency routing path separately Admin cannot modify group Division permission issue Verify division assignment and admin role permissions Troubleshooting Checklist Check ✓ Emergency group created ☐ Correct division selected ☐ Emergency group assigned to all relevant call routes ☐ Emergency flow is published in Architect ☐ Emergency flow assigned to call route ☐ Tested activation in non-production or low-traffic window ☐ Verified Usages field — no unexpected routes affected ☐ Confirmed normal routing works when group is deactivated ☐ Key Facts for Exam / Interview Question Answer Where are emergency groups configured? Admin → Routing → Emergency Groups What does activating an emergency group do? Overrides all schedule-based routing — all calls go to the emergency flow What must be done after creating an emergency group? Assign it to a call route AND assign an emergency flow on that route How do you check what a group affects? The Usages field on the group What is the routing priority order? Emergency Group → Schedule Group → Open/Closed/Holiday flows What is the most common implementation mistake? Creating the group but forgetting to assign it to the call route, or not assigning an emergency flow See Also Scheduling & Schedule Groups — the routing layer that emergency groups override Call Routing — where emergency groups are assigned to inbound numbers Architect Overview — building the emergency call flow that gets executed External Contacts Navigation: Admin → Directory → External Contacts What Are External Contacts? External Contacts is the central repository for people and organizations outside your company — customers, vendors, partners, suppliers. Contact records surface in the agent workspace during live interactions, giving agents immediate context without switching systems. There are two object types: Object What It Represents External Organization A company or entity (e.g., "Oracle Support", "Acme Corp") External Contact An individual person, optionally linked to an External Organization ✅ Best practice: Create the External Organization first, then create contacts linked to it. This allows you to track all individuals from the same company under one record. Creating an External Organization Admin → Directory → External Contacts Click Add → Organization Fill in: Field Notes Name Company name — required Website Company URL Address Physical address Custom Fields Org-specific fields you've configured (e.g., Account ID, SBC Serial Number) Click Save Creating an External Contact Admin → Directory → External Contacts Click Add → Contact Fill in: Field Notes First Name / Last Name Required — the only mandatory fields Associate Org Link to an External Organization (search and select) Email Work, cell, or home addresses Phone Add one or more numbers SMS Toggle ⚠️ Click the SMS icon next to each phone number to explicitly enable or disable SMS — not enabled by default Social Media Add handles for WhatsApp, Twitter/X, Facebook, Line Survey Opt-Out Check to prevent automated post-call surveys from being sent to this contact Notes Free-text historical context not captured in standard fields External System Link A URL pointing to your own internal CRM or database record for this contact Click Save SMS Toggle — Important Detail SMS capability on a phone number is not enabled by default . For each number on a contact record: Click the SMS icon next to the number Toggle to On to allow agents to send SMS to that number Toggle to Off to block SMS to that number This must be set explicitly — there is no org-wide "enable SMS for all contacts" switch. Survey Opt-Out The Survey Opt-Out checkbox on a contact record: Prevents automated post-interaction surveys from being sent to that contact Applies across all survey methods configured in the org Should be set when a customer has explicitly requested no surveys Custom Fields Both External Organizations and External Contacts support custom schema fields : Fields are configured by admins at the schema level (not per-record) Examples: Account Tier, Contract ID, SBC Model, Support Level Appear in the contact/org record and in the agent workspace pop-up Bulk Management For large contact databases, manual entry is not practical. Three methods: Method Best For CSV Upload One-time or periodic bulk imports from a spreadsheet CRM Sync Continuous sync from Salesforce or other supported CRMs — keeps contacts current automatically External Contacts API Custom integrations pushing data from internal systems (ticketing, billing, ERP, etc.) into Genesys Where Agents See This Data During a live interaction, the CX Agent Workspace automatically surfaces the matching External Contact record when the caller's number matches a record in External Contacts. Agents see: Contact name and organization Phone numbers and email addresses Social handles Notes and custom fields Link to the external system (if configured) This eliminates the need for agents to look up customer records manually during a call. Division Behaviour ⚠️ External Contacts cannot be reassigned between divisions after creation. If a contact needs to move to a different division, you must delete the record and recreate it in the correct division. Plan your division structure before bulk-importing contacts. Quick Reference — Key Facts Feature Detail Object types External Organization + External Contact Required fields (Contact) First Name and Last Name only SMS Must be explicitly toggled per phone number Survey opt-out Per-contact checkbox Division reassignment Not supported — delete and recreate Bulk import CSV, CRM sync (Salesforce), or API Agent visibility CX Agent Workspace during live interactions Custom fields Configurable at schema level for both Orgs and Contacts See Also Divisions & Access Control — division assignment at contact creation time Integration Management — CRM sync configuration (Salesforce, etc.) Queue & Routing Management — how interaction routing connects to contact lookup Scheduling & Schedule Groups Scheduling & Schedule Groups Section Description Module Context Schedules are part of Routing and Architect decision logic in Genesys Cloud. Purpose A schedule stipulates when a flow runs based on date, time, or event. Primary Use Business hours, after-hours support, holidays, recurring events, maintenance windows, and special situations. Admin Location Admin → Routing → Scheduling Study Notes Topic Explanation Schedule A time-based object that determines when routing or flow logic is active. Schedule Group Groups multiple schedules into Open, Closed, and Holiday categories for routing. Architect Usage Architect uses schedules to determine how inbound and outbound interactions should be handled. Recurrence Support Schedules can be one-time or repeating (daily, weekly, monthly, yearly, or custom iCal rule). Evaluation Order In Architect: Emergency → Holiday → Closed → Open Default Branch If no schedule matches, Closed is the default branch in Evaluate Schedule Group. Time Zone Set on the Schedule Group — most common misconfiguration is a wrong or missing time zone. Navigation Task Navigation View Schedules Admin → Routing → Scheduling Create Schedule Admin → Routing → Scheduling → Add Schedule View Schedule Groups Admin → Routing → Scheduling → Schedule Groups Use in Architect Architect → Open Flow → Add Evaluate Schedule Group action Schedule Configuration Fields Field Description Example Schedule Name Unique name for the schedule US_Support_BusinessHours Division Determines administrative ownership and access Home Repeating Event Enables recurring schedule logic Enabled Start Date Date when the schedule starts 2026-03-01 End Date Date when the schedule ends 2026-12-31 Start Time Time when the schedule starts 08:00 End Time Time when the schedule ends 18:00 All Day Enables full-day schedule instead of start/end times Disabled Repeats Every Defines recurrence pattern Weekly Start Option Defines when recurrence begins On Date End Option Defines when recurrence stops No End Date iCal Rule Advanced recurrence rule configuration FREQ=WEEKLY;BYDAY=MO,TU,WE,TH,FR Schedule Types Schedule Type Example One-Time July_4_Closure Daily After_Hours_Daily Weekly Mon_Fri_BusinessHours Monthly First_Monday_Maintenance Yearly Christmas_Holiday Advanced Rule FREQ=WEEKLY;BYDAY=MO,TU,WE,TH,FR Example business-hours schedule: Field Value Name US_Support_BusinessHours Repeating Event Enabled Repeats Every Weekly Days Monday–Friday Start Time 08:00 End Time 18:00 End Option No End Date Schedule Group Configuration Component Description Open Schedule Defines when the business is open Closed Schedule Defines after-hours or closure periods Holiday Schedule Defines holiday dates — overrides Open Time Zone Applied at the Schedule Group level — determines when schedules activate Emergency Group Separate object that overrides all schedule-based logic when activated ⚠️ Most common misconfiguration: Setting the wrong time zone on the Schedule Group, causing callers to hit closed or holiday paths at unexpected times. Architect Evaluation Order Evaluate Schedule Group ↓ Emergency? (Emergency Group activated?) ↓ Holiday? (Current date/time matches a Holiday schedule?) ↓ Closed? (Current date/time outside Open schedule?) ↓ Open (Default — current date/time matches Open schedule) If nothing matches, the Closed branch is taken by default. Routing Architecture Customer Interaction ↓ Call Route or Architect Flow ↓ Schedule / Schedule Group Evaluation ↓ Open / Closed / Holiday / Emergency ↓ Menu / Queue / Voicemail / External Transfer / Disconnect Real Flow Scenarios Scenario 1 — Business Hours Menu Caller Enters Flow ↓ Evaluate Schedule Group ↓ Open ↓ Play Welcome Prompt → Send to Menu → Route to Agent Scenario 2 — After-Hours Voicemail Caller Enters Flow ↓ Evaluate Schedule Group ↓ Closed ↓ Play Closed Prompt → Route to Voicemail Scenario 3 — Holiday Transfer Caller Enters Flow ↓ Evaluate Schedule Group ↓ Holiday ↓ Play Holiday Prompt → Transfer to External Number Scenario 4 — Emergency Shutdown Caller Enters Flow ↓ Evaluate Schedule Group ↓ Emergency ↓ Play Issue Prompt → Disconnect Call Implementation Steps Step Action Step 1 Navigate to Admin → Routing → Scheduling Step 2 Click Add Schedule Step 3 Enter unique schedule name Step 4 Select division Step 5 Choose one-time or repeating event Step 6 Configure start date, end date, and time range (or All Day) Step 7 Configure recurrence settings if repeating Step 8 Save the schedule Step 9 Create a schedule group and assign schedules to Open / Closed / Holiday Step 10 Set the correct time zone on the schedule group Step 11 Use the schedule group in call routing or Architect Naming Convention Resource Example Schedule US_Support_BusinessHours Holiday Schedule US_Support_Christmas Maintenance Schedule US_Support_MaintenanceWindow Schedule Group US_Support_Main_SG Recommended pattern: __ Best Practices Practice Reason Use clear schedule names Makes routing easier to understand and maintain Separate business hours and holidays into distinct schedules Improves flexibility and troubleshooting Always use Schedule Groups for production routing Simplifies open/closed/holiday branching Set the correct time zone on the Schedule Group Prevents incorrect routing behavior Test all branches (Open, Closed, Holiday, Emergency) Ensures callers hear the correct experience Review holiday schedules annually Keeps routing accurate over time Troubleshooting Issue Cause Resolution Flow always routes Closed Time zone mismatch or no active Open schedule Verify schedule times and schedule group time zone Holiday path never triggers Holiday schedule not assigned to group Add holiday schedule to schedule group Emergency path does not work Emergency group not activated or not assigned to flow Verify emergency group setup and flow logic Recurring schedule not firing Recurrence settings incorrect Review repeating event settings and end conditions External transfer not reached Holiday branch misconfigured Check Architect holiday branch and external number Schedule group unavailable in flow Permission or object visibility issue Confirm access and division permissions Interview Cheat Sheet Question Answer What is a schedule in Genesys Cloud? A time-based object that determines when routing or flow logic is active What can schedules be used for? Business hours, after-hours, holidays, recurring events, and special situations What is a schedule group? A grouping of schedules into Open, Closed, and Holiday categories What is the evaluation order in Architect? Emergency → Holiday → Closed → Open What happens if nothing matches? Closed is the default path in Evaluate Schedule Group What is the most common misconfiguration? Wrong time zone set on the Schedule Group Queues Topic Detail Navigation Admin → Contact Center → Queues Purpose Core ACD routing objects that hold interactions until an agent is available Max Queues 5,000 queues per organization Max Members 5,000 members per queue Tabs General, Routing, Members, Voice, Chat, Message, Email, Callback, Wrap-Up Codes Step 1 — Initial Queue Creation Navigate to Admin → Contact Center → Queues Click Create Queue Name: Enter a unique name (e.g., VoIP_Tier2_Support ) Division: Select the appropriate Division Controls which admins can manage the queue and which Architect flows can reference it Use different divisions to separate groups such as Finance or HR Peer ID: Optional — only used when syncing with an external system like Genesys Cloud EX Click Save Step 2 — General Tab Field Description After Call Work (ACW) Mode Controls how agents transition out of ACW after each interaction ACW Timeout Maximum ACW duration in seconds — max is 900 seconds Manual Assignment Allows supervisors to manually push waiting interactions to specific agents (rarely used in high-volume environments) ACW Modes Mode Behavior Mandatory Timeboxed Automatically returns agent to Available after the ACW timeout expires Mandatory Discretionary Agent stays in ACW until they manually click to finish Optional Agent can choose to enter ACW or skip it Optional Timed ACW is optional, but auto-ends after the timeout None No ACW — agent is immediately available after interaction ends ⚠️ Mandatory Timeboxed is most common in high-volume voice environments. Mandatory Discretionary is preferred when agents need time to complete CRM updates before going available again. Step 3 — Routing Tab Routing Methods Method Behavior Standard Routes to the longest-idle available agent matching skills Bullseye Starts with strict skill requirements; relaxes requirements in rings over time if no agent found Predictive Uses AI to match the best agent to the specific caller based on historical outcomes Evaluation Methods Method Behavior All Skills Matching Agent must have every skill required by the interaction Best Available Skills Routes to the agent with the highest combined skill proficiency Scoring Methods Method Formula / Behavior Conversation Score Score = (Minutes in Queue) + (Priority Value) — allows high-priority calls to jump ahead of older, lower-priority calls Priority Score Ranks strictly by priority value set in Architect flow; equal-priority interactions handled FIFO Step 4 — Members Tab Option Description Add User Search for and add individual agents Add Work Team Add an entire Work Team to the queue ⚠️ Generally add either individual users or a Work Team — not a mix of both for the same queue. Step 5 — Media-Specific Tabs Voice Tab Field Description Service Level Target percentage of calls answered within the SLA window (e.g., 80%) Service Level Target Time goal in seconds (e.g., 20 seconds) In-Queue Flow Architect flow handling the caller's wait experience — plays hold music, EWT announcements, or offers callback Calling Party Name/Number Outbound caller ID shown to recipients when agents call on behalf of this queue Alerting Timeout Seconds a call rings at an agent's station before being routed to the next available agent Default Script Script that pops on the agent's screen when they answer Whisper Prompt Short audio clip played only to the agent just before the caller connects — helps agents pivot context across multiple queues Auto-Answer If enabled, call connects to agent automatically without requiring them to click Answer Continue Voice Recording during Q-Wait Enabled = records hold music; Disabled = recording starts only when agent and caller connect (saves storage) Chat Tab Field Description Service Level & Target SLA goal — digital targets are typically slightly longer than voice (e.g., 80% within 30 seconds) Alerting Timeout Seconds chat request flashes on agent screen before rerouting to next available agent Auto-Answer Enabled = chat session connects automatically; Disabled = agent must click Answer Default Script Published script that loads for the agent — often includes Data Actions to look up customer account data In-Queue Flow (Message Flow) Architect flow managing the customer wait experience — handles welcome messages and position-in-queue announcements Message Tab Covers SMS, WhatsApp, Facebook Messenger, and LINE . Messaging is asynchronous — customers may not reply immediately. Field Description Service Level & Target SLA goal — messaging SLAs are typically more relaxed than voice (e.g., 80% within 60 seconds) Alerting Timeout Seconds the notification flashes for the agent before rerouting Auto-Answer Enabled = message thread pops open immediately; recommended for high-volume SMS/WhatsApp queues In-Queue Message Flow Architect Inbound Message Flow — acts as a digital IVR, can collect account number or reason for contact via bot Default Script Script displaying customer data such as phone number or WhatsApp display name Outbound SMS Number DID or Short Code used when an agent starts a new outbound SMS — must be provisioned in SMS Inventory Email Tab Field Description Service Level & Target SLA goal — email targets are typically set in hours rather than seconds (e.g., 90% within 4 hours) Alerting Timeout Seconds email flashes on agent screen before moving to next agent Auto-Answer Enabled = email workspace opens immediately; best for high-volume ticket environments Outbound Email Address Address recipients see when an agent replies (e.g., support@company.com ) Email Domain Verified domain used for outbound email — validates sender identity In-Queue Email Flow Architect Inbound Email Flow — can perform keyword routing (e.g., raise priority if subject contains "Billing") Default Script Script displaying customer history or canned response suggestions Auto-Reply Sends an immediate acknowledgement to the customer before an agent reviews the email Callback Tab Field Description Service Level & Target SLA goal — callback clock typically starts when the agent's phone rings for the return call Alerting Timeout Seconds callback request flashes on agent screen before rerouting Allow Agents to Take Ownership Agents can claim a scheduled callback so it routes back specifically to them Ownership Duration How long callback remains reserved for the specific agent — 1 hour to 7 days Advance Scheduling How far in advance an agent can schedule a callback — 1 hour to 30 days Auto-Answer Enabled = system dials customer and connects agent automatically; Disabled = agent must manually click Call Wrap-Up Codes Tab Navigate to the Wrap-Up Codes tab within the Queue Click + or use the search box Add the codes created under Admin → Contact Center → Wrap-Up Codes ⚠️ Critical: If wrap-up codes are not added to the queue here, agents cannot tag their interactions even if the codes exist globally in the system. Interview Cheat Sheet Question Answer Max queues per org? 5,000 Max members per queue? 5,000 Max ACW timeout? 900 seconds What does Bullseye routing do? Starts with strict skills; relaxes requirements in rings over time Conversation Score formula? Minutes in Queue + Priority Value When does an interaction count toward utilization? When it starts Alerting (ringing), not when answered Can you mix Users and Work Teams in a queue? Not recommended — use one or the other ACD Skills & Languages Topic Detail Navigation Admin → Contact Center → ACD Skills & Languages Purpose Define skills and languages used by the ACD routing engine to match interactions to the right agents Proficiency Scale 1 (Beginner) to 5 (Expert) Skill Status Active (default) or Inactive (retired — preserves historical reporting data) Creating a Skill Navigate to Admin → Contact Center → ACD Skills & Languages Click Add Skill Name: Enter a descriptive name (e.g., Tier_2_SBC_Troubleshooting ) Category: Optional grouping folder (e.g., Technical, Soft Skills, Product Knowledge) — helps organize hundreds of skills Status: Active by default — set to Inactive to retire without deleting historical reporting data Click Save ⚠️ Once created, a skill must be assigned to a User profile or referenced in an Architect flow before it has any effect on routing. Creating a Language In the same menu, click the Languages tab Click Add Language Start typing the language name (e.g., Spanish) — Genesys Cloud provides a standardized list Click Save Languages are treated separately from skills because Genesys Cloud has built-in logic to prioritize a caller's native language during routing. Assigning Skills to Users Individual Assignment Navigate to Admin → People & Permissions → People Click the User Go to the ACD Skills or Languages tab on their profile Click Add Skill and select the skill Set proficiency Rating (1–5) Click Save Bulk Assignment In the People list: select multiple agents → More Actions → Assign Skill Proficiency Ratings Rating Meaning 1 Beginner / Trainee 2 Basic 3 Intermediate 4 Advanced 5 Expert / Subject Matter Expert Skill Expressions (Advanced Routing) Instead of a single skill requirement, use a Skill Expression Group with AND/OR logic: (Skill: SIP == 5) AND (Skill: Oracle_SBC >= 3) This allows highly specific routing without requiring a separate queue for every possible skill combination. Skill Expression Groups are configured under Admin → People & Permissions → Groups . How Routing Uses Skills In Architect's Transfer to ACD action, you specify: Target queue Required skill(s) and minimum proficiency level Language requirement (if applicable) The ACD engine then matches the interaction to an available agent who meets all requirements. With Bullseye routing , if no agent matches, the requirements are relaxed in configurable rings over time. Interview Cheat Sheet Question Answer Where are ACD skills created? Admin → Contact Center → ACD Skills & Languages What does setting a skill to Inactive do? Retires it from new routing logic without deleting historical data What is proficiency scale? 1 (Beginner) to 5 (Expert) How do you assign skills to multiple agents at once? People list → select agents → More Actions → Assign Skill What is a Skill Expression? AND/OR logic combining multiple skills for routing (e.g., SIP == 5 AND SBC >= 3) Why are languages separate from skills? Genesys has built-in native-language prioritization logic for languages Wrap-Up Codes Topic Detail Navigation Admin → Contact Center → Wrap-Up Codes Purpose Allow agents to categorize the outcome of each interaction for reporting, analytics, and quality Scope Created globally at org level — must also be assigned to each queue individually Overview Wrap-up codes are disposition tags agents apply at the end of each interaction to classify what happened (e.g., Resolved, Escalated, Follow-up Required, Technical Issue). They feed directly into: Historical analytics and reports Quality evaluations Workforce management data Contact reason tracking Creating Wrap-Up Codes Navigate to Admin → Contact Center → Wrap-Up Codes Click Add Enter a Name (e.g., Resolved , Escalated , Follow-up Required ) Select a Division — controls which admins can manage this code Click Save Assigning Wrap-Up Codes to a Queue Codes must be added to each queue individually — creating them globally is not enough. Navigate to Admin → Contact Center → Queues Open the queue Click the Wrap-Up Codes tab Click + or use the search box Add the required codes Click Save ⚠️ Critical: If wrap-up codes are not assigned to the queue, agents cannot tag their interactions — even if the codes exist in the system globally. Best Practices Practice Reason Keep code names clear and consistent Improves reporting accuracy and agent usability Limit the number of codes per queue Too many choices slow agents during ACW Use division assignment Restricts management to appropriate admin teams Review codes periodically Remove outdated codes to keep reporting clean Align codes with business reporting needs Ensures data collected matches what leadership tracks Interview Cheat Sheet Question Answer Where are wrap-up codes created? Admin → Contact Center → Wrap-Up Codes Where are they assigned for use? In each queue's Wrap-Up Codes tab What happens if codes aren't assigned to the queue? Agents cannot tag interactions, even if codes exist globally What do wrap-up codes feed into? Analytics, historical reports, quality evaluations, WFM data Utilization Topic Detail Navigation Admin → Contact Center → Utilization Purpose Controls how many simultaneous interactions an agent can handle and which channels can interrupt others Levels Organization-wide default + per-user override Overview Utilization defines agent capacity — how many interaction "slots" an agent has per media type and what priority rules govern interruptions between channels. It prevents agents from being overwhelmed while ensuring high-priority interactions (like voice calls) are never missed. Organization-Wide Configuration Navigate to Admin → Contact Center → Utilization Set Maximum Capacity per media type: Media Type Typical Capacity Voice 1 (almost always) Chat 2–3 Email 4–5 Message 2–3 Callback 1 Configure Can be interrupted by checkboxes — defines which channels can interrupt an active interaction Example: If an agent is working on an Email, can a Voice call interrupt? If checked, the agent sees the incoming call alert while the email draft stays open Block calls when on a non-ACD call — prevents ACD queue calls from reaching an agent who is already on an internal/personal call (Busy-on-Busy logic) Click Save User-Level Override To set different utilization for a specific agent (e.g., a Lead Engineer or Super Agent): Navigate to Admin → People & Permissions → People Select the user Click the ACD Utilization tab Toggle Inherit from Organization to Off Manually adjust capacity and interruption rules for this person Click Save Key Technical Rules Rule Detail Capacity Number of simultaneous interaction slots per media type Interruption Priority override — defines if a new channel can interrupt an active one Non-ACD Blocking Busy-on-Busy for internal/direct calls vs. ACD queue calls Alerting counts An interaction counts toward utilization when it starts Alerting (ringing) , not when the agent answers Voice interrupt Voice is always a "hard" interrupt — takes precedence over all digital channels Transfers Non-ACD calls (transfers or direct dials) are excluded from utilization count unless "Block calls" is checked Summary Term Meaning Capacity How many slots/sessions the agent has per channel Interruption Priority override logic between channels Non-ACD Blocking Busy-on-Busy for internal extensions vs. ACD lines Interview Cheat Sheet Question Answer Where is utilization configured? Admin → Contact Center → Utilization What are the two configuration levels? Organization-wide default and per-user override When does an interaction count toward utilization? When it starts Alerting (ringing), not when answered What does "Block calls when on a non-ACD call" do? Prevents queue calls from reaching agents already on internal/personal calls What is the typical voice capacity? 1 — voice is almost always a single-slot media type Canned Responses & Response Assets Canned Responses Topic Detail Navigation Admin → Contact Center → Canned Responses Purpose Pre-written answers agents can insert into Chat, Email, or Message interactions for consistency and speed Structure Libraries → Responses Channels Chat, Email, Message (WhatsApp, SMS, social) Libraries Libraries group responses by team, department, or topic (e.g., Billing, Technical Support, General FAQ). Access is controlled at the library level — only relevant teams see specific content. Creating a Canned Response Navigate to Admin → Contact Center → Canned Responses Click Add Library and provide a meaningful name Inside the library, click Add Response Name the response — this is what agents see in the search bar during interactions Enter content and save Response Types Type Use Case Constraint Standard Chat and Email replies Can be edited or personalized by the agent before sending Message Template WhatsApp Business / proactive outbound Requires pre-approval from Meta/WhatsApp — mandatory for messages sent 24+ hours after last customer message Campaign SMS Bulk SMS notifications 160 characters per segment — carrier compliance required; supports variables/macros for personalization Email Footer Legal compliance / branding Auto-appended to all outbound emails from the library — agents cannot see or remove it Agent Usage Mode Description Read-only Agent reads the response to the customer — common for voice interactions Insertion Agent clicks to insert the full text directly into a chat, email, or messaging thread Best Practices Practice Reason Organize responses into focused libraries Helps agents find responses quickly Use clear response names Agents search by name during live interactions Keep standard responses concise Long responses slow down chat interactions Review Message Templates before WhatsApp campaigns Meta approval can take days Always configure Email Footer at library level Prevents accidental removal of legal disclaimers Response Assets Topic Detail Navigation Admin → Contact Center → Response Assets Purpose Central repository for images and documents embedded in Canned Responses Supported Files PNG, JPG (images); PDF (documents) Overview Response Assets is a central media library. Images and documents must be uploaded here before they can be embedded in a Canned Response. This ensures agents always use the most current version of a file and prevents broken image links in customer emails. Asset Repository Navigate to Admin → Contact Center → Response Assets Upload images or documents before attaching them to any Canned Response From the dashboard: view file details, delete outdated assets, search existing media Embedding in Canned Responses Method Description Upload from Library Select a pre-uploaded asset from the Response Asset collection — most secure and consistent Insert from URL Link to an externally hosted image — flexible but less secure Upload New Image Upload directly while editing a response — automatically populates the asset library Key Facts Feature Detail Centralization Prevents broken image links in customer emails Security Internally hosted assets are scanned and verified by Genesys Cloud Supported formats PNG, JPG, PDF Access Accessible via a dedicated icon in the Canned Response editor Interview Cheat Sheet Question Answer What is a Canned Response library? A named grouping of responses organized by team or topic What approval does a WhatsApp Message Template require? Pre-approval from Meta/WhatsApp What is the SMS segment character limit? 160 characters per segment What does Email Footer do? Auto-appends legal/branding content to outbound emails — agents cannot remove it Where must images be uploaded before embedding in a response? Response Assets ( Admin → Contact Center → Response Assets ) Email — Domains & Routing Topic Detail Navigation Admin → Contact Center → Email Purpose Configure email domains, addresses, routing logic, and agent experience settings Max Recipients 50 total (To + CC + BCC combined) BCC Limit Maximum 5 hidden recipients per email Step 1 — Email Domains Before receiving email, define the domain: Navigate to Admin → Contact Center → Email → Domains Domain Type Description Genesys Cloud Built-in subdomain (e.g., company.mypurecloud.com ) — no DNS configuration required Custom Corporate domain (e.g., support@company.com ) — requires DNS MX record or forwarding + DNS verification Campaign/Agentless Used specifically for outbound-only notifications — no inbound routing Custom domains require DNS verification before Genesys Cloud can send or receive on your behalf. Step 2 — Email Address Configuration Once the domain is defined, create specific email addresses: Field Description Email Address The inbound address customers use (e.g., support@company.com ) From Name Friendly display name shown in the customer's inbox (e.g., "Global Support Team") From Email Address Address the recipient sees when an agent replies — must be verified within your Genesys Cloud domain Reply To Optional — overrides the From address when a customer clicks reply; useful for directing replies to a specific mailbox BCC Recipients Up to 5 hidden recipients on every outbound response — agents cannot see or remove these; count toward the 50-recipient limit Email History Controls whether the prior conversation thread is included in agent replies Email Actions Enables/disables Multiple Replies or Forwards within the same thread Email History Options Option Behavior Always Automatically includes the full prior thread Never Sends a clean reply without history Let Agent Decide Provides the agent a toggle to include or exclude history Step 3 — Routing & Handling Logic Routing Option Description Route to a Queue Directly assigns email to an agent group — can also set ACD Skills, Language, and Priority Route to a Flow Sends email to an Architect Inbound Email Flow for automated processing or keyword-based routing Do Not Route For outbound-only addresses — no inbound routing expected Spam Routing Option Behavior Route Spam to a Flow Sends flagged emails to a specific Architect flow for manual supervisor review Disconnect Automatically drops spam so it never reaches an agent Email Quick Reference Field Constraint Max Recipients 50 total (To + CC + BCC) BCC Limit 5 addresses maximum Priority Added to Time in Queue in minutes for routing rank Spam Handling Disconnect or Route to Flow Enqueue Flow Architect flow handling the email while it waits in queue Queue Email Tab Settings These settings are configured per queue under the Email tab of the Queue configuration: Field Description Service Level & Target SLA goal — typically set in hours (e.g., 90% within 4 hours) Alerting Timeout Seconds email flashes on agent screen before moving to next agent Auto-Answer Enabled = email workspace opens immediately; best for high-volume environments Outbound Email Address Address recipients see when an agent replies from this queue Email Domain Verified domain used for outbound email In-Queue Email Flow Architect Inbound Email Flow — can perform keyword routing Default Script Script displaying customer history or canned response suggestions Auto-Reply Sends an immediate acknowledgement before an agent reviews the email Interview Cheat Sheet Question Answer What are the three domain types? Genesys Cloud (built-in), Custom (DNS verified), Campaign/Agentless (outbound only) Max total recipients per email? 50 (To + CC + BCC combined) Max BCC recipients? 5 How does Priority affect email routing? It adds minutes to the Time in Queue for ranking What are the spam routing options? Disconnect or Route to Flow What must be done before using a custom domain? DNS verification Widgets — Web Chat & Web Messenger Topic Detail Navigation (Web Messenger) Admin → Message → Messenger Configurations and Messenger Deployments Navigation (Web Chat v2) Admin → Contact Center → Widgets Purpose Provide a chat interface on websites connecting customers to Genesys Cloud agents Modern Standard Web Messenger — persistent, asynchronous Legacy Web Chat v2 — session-based Web Messenger (Modern Standard) Web Messenger offers a persistent, asynchronous experience — customers can leave the website and return later with their full conversation history still intact. Component Description Messenger Configurations Defines look and feel — color palette, logo, features (file uploads, emojis, read receipts) Messenger Deployments Links a Messenger Configuration to an Architect Inbound Message Flow — this is where routing is assigned Deployment Snippet JavaScript code pasted into the website or to render the chat icon Deployment ID Unique GUID identifying which configuration the website loads Allowed Domains Security whitelist — only URLs listed here can render the widget Web Chat v2 (Legacy) Strictly session-based — if the customer refreshes or closes the browser tab, the chat session is lost. Widget Type Description Standard Simple chat window provided by Genesys Third-Party Uses Genesys as the routing engine while a completely custom UI is built by developers Widget Features Both versions support the following controls: Feature Description File Uploads Enable/disable customer ability to send images or documents Typing Indicators Shows when the agent or customer is typing Read Receipts Informs users when messages have been seen Guest Chat Allows unauthenticated chat, or require login to pull CRM data automatically Pre-Chat Form Collects Name, Email, Account Number before routing — data passed into Architect flow for intelligent routing Routing Logic Widgets do not send chats directly to agents. They route to an Architect Inbound Message Flow first. The flow processes pre-chat form data and routes to the correct queue. Customer Clicks Chat Widget ↓ Pre-Chat Form (Name, Email, Account Number) ↓ Architect Inbound Message Flow ↓ Data Evaluated / Customer Identified ↓ Transfer to Queue ↓ Agent Deployment Steps (Web Messenger) Navigate to Admin → Message → Messenger Configurations Create a configuration — set branding, colors, features Navigate to Admin → Message → Messenger Deployments Create a deployment — link configuration to an Architect Inbound Message Flow Add Allowed Domains (whitelist your website URLs) Copy the Deployment Snippet (JavaScript) Paste the snippet into the website's or Connect to a chat flow: Deployment key generated: Technical Reference Component Detail Snippet JavaScript placed in or of the website Deployment ID Unique GUID — identifies which configuration loads Allowed Domains Must whitelist all URLs where the widget appears Persistence Web Messenger supports Persistent or Clearing Conversation session modes Web Messenger vs. Web Chat v2 Feature Web Messenger Web Chat v2 Session type Persistent / asynchronous Session-based (lost on refresh) Conversation history Retained across sessions Lost when session ends Routing Architect Inbound Message Flow Architect Inbound Chat Flow Status Current standard Legacy — still supported Customization Full branding via Messenger Config Limited Interview Cheat Sheet Question Answer What is the modern widget standard? Web Messenger — persistent and asynchronous What happens to a Web Chat v2 session on page refresh? The session is lost What does the Deployment ID identify? Which Messenger Configuration loads on the website What must be configured for security? Allowed Domains whitelist Where does the widget route interactions? To an Architect Inbound Message Flow, not directly to agents What is a Pre-Chat Form used for? Collecting customer data before routing for intelligent queue assignment Analytics Settings Topic Detail Navigation Admin → Contact Center → Analytics Settings Purpose Configure abandon intervals and analytics capture settings for queue reporting Abandon Intervals 7 configurable intervals (A–G) categorizing when customers disconnect from queue Overview Analytics in Genesys Cloud transforms raw interaction data into actionable insights. Configuration here directly affects how abandonment is measured and reported across all queues. Abandon Intervals Abandon intervals measure how long customers waited in queue before disconnecting without reaching an agent . This metric helps identify queue tolerance, IVR issues, and staffing problems by grouping abandons into time ranges. Interval Default Wait Range Interpretation A 0–6 seconds Immediate disconnects — misrouting, robocalls, misdials, IVR confusion B 6–20 seconds Early abandons after entering queue C 20–40 seconds Short wait abandonment D 40–60 seconds Moderate wait abandonment E 60–120 seconds Customers leaving after ~1–2 minutes F 120–240 seconds Long queue wait frustration G >240 seconds Very long wait abandonment ⚠️ A large percentage in Interval A typically indicates misrouting, IVR confusion, or non-intentional calls — not a staffing problem. Analytics Implementation Steps Step Action Step 1 Set Service Level targets per queue — Admin → Contact Center → Queues Step 2 Configure Abandon Intervals — Admin → Contact Center → Analytics Settings Step 3 Ensure all queues have Wrap-Up Codes assigned so agents can tag interactions Step 4 Create Dashboards at Performance → Dashboards with relevant KPI widgets Real-Time Analytics Feature Location Performance Views Performance → Workspace — pre-built views for Queues, Agents, and Interactions Dashboards Customizable screens with widgets for KPIs (Service Level, Agents On-Queue, Active Interactions, etc.) Alerting Rules Trigger email or browser notifications when metrics hit thresholds (e.g., Wait Time > 5 minutes) Historical Analytics Feature Description Standard Reports Pre-packaged PDF or CSV reports (e.g., Queue Abandonment Detail, Agent Log-level Report) Dynamic Views Filter by date range, media type, wrap-up codes Exporting Manual export or scheduled delivery to S3 bucket or email address Core Analytics Metrics Interaction Volume Metric Description Offered Total interactions entering the queue Answered Interactions handled by agents Flow-Outs Interactions exiting queue through routing or IVR actions Connected Interactions successfully connected to agents Queue Performance Metric Description Service Level Percentage of interactions answered within SLA target ASA Average Speed of Answer — average time before agent answers Average Wait Time Average time customers wait in queue Longest Wait Longest interaction currently waiting Customer Behavior Metric Description Abandoned Interactions disconnected before reaching an agent Abandon % Abandoned ÷ Offered Average Abandon Time Average wait time before customer hangs up Short Abandon Disconnects within a configured short-time threshold Agent Handling Metric Description AHT Average Handle Time = Talk Time + Hold Time + ACW Talk Time Active speaking time with customer Hold Time Time interaction placed on hold ACW After Call Work time Transfers Interactions transferred between agents or queues IVR / Flow Metrics Metric Description Flow Outcomes Where customers exit an Architect flow (Success vs. Failure) Containment Rate Percentage of interactions resolved within IVR without reaching an agent IVR Disconnects Customers disconnecting during IVR navigation Advanced Metrics Metric Description Agent Utilization Percentage of agent time spent handling interactions Concurrency Simultaneous digital interactions handled Callback Rate Percentage of callers choosing callback instead of waiting Recontact Rate Customers contacting support again after a recent interaction High Abandonment Troubleshooting When investigating high abandonment, analyze these five together: ASA — Is average wait time excessive? Abandon Intervals — Which interval has the highest %? (Interval A = routing/IVR issue; Interval F/G = staffing issue) Service Level — Is the SLA target being met? Queue Staffing — How many agents are On-Queue vs. interactions waiting? Flow Outcomes — Are callers exiting the IVR before reaching the queue? Knowledge Analytics Knowledge Analytics measures how effectively knowledge base articles help resolve customer issues — for both agents and bots. Search & Discovery Metric Description Knowledge Searches Total searches performed in the knowledge base Search Success Rate Percentage of searches that returned useful articles Search Failure Rate Searches that produced no relevant results Popular Search Terms Most frequently searched keywords Article Usage Metric Description Article Views Number of times a knowledge article was opened Articles Shared Articles sent to customers during interactions Top Articles Most frequently accessed articles Article Feedback Ratings or feedback from agents or customers Self-Service & Automation Metric Description Knowledge Match Bot successfully finds a relevant knowledge article Confidence Score AI confidence in the article match Knowledge Fallback Bot cannot find a suitable article Containment Rate Issues resolved through self-service without an agent Interview Cheat Sheet Question Answer What do Abandon Intervals measure? How long customers waited before disconnecting without reaching an agent What does high % in Interval A suggest? Misrouting, IVR confusion, or non-intentional calls — not a staffing problem What is AHT? Average Handle Time = Talk Time + Hold Time + ACW What is ASA? Average Speed of Answer — average wait time before an agent answers What is Containment Rate? Percentage of interactions resolved in IVR without reaching an agent Where are Abandon Intervals configured? Admin → Contact Center → Analytics Settings Panel Manager Topic Detail Navigation Admin → Contact Center → Panel Manager Purpose Create custom UI panels embedded in the agent desktop for CRM systems, internal tools, dashboards, or web apps Security Requirement All embedded panel URLs must use HTTPS Overview Panel Manager allows administrators to embed external tools directly into the Genesys Cloud agent workspace, eliminating the need for agents to switch between multiple applications during interactions. Two Types of Panels in the Agent Desktop Type Description Interaction Panels System panels automatically created when a customer interaction occurs (voice, chat, email, etc.) — manage the conversation itself Custom Panels (Panel Manager) Administrator-created panels embedding external tools, CRMs, dashboards, or internal applications — provide supporting context Custom Panel Configuration Fields Field Description Panel Name Name displayed to agents in the desktop URL Web application URL loaded in the panel — must be HTTPS Icon Visual identifier shown in the agent interface Default State Whether the panel loads automatically when an interaction begins Role Assignment Controls which users can see and access the panel Width / Layout Determines panel size and position in the desktop How to Create a Panel Navigate to Admin → Contact Center → Panel Manager Click Create Panel Configure Name, URL (HTTPS), Icon, and Visibility settings Save the configuration Assign to the appropriate roles or agent groups Best Practices Practice Reason Use HTTPS only Security requirement — HTTP URLs will not load Keep UI lightweight Heavy applications slow the agent desktop and increase handle time Limit total panels Too many panels reduce usability and create cognitive overload Align panels with workflows Panels should directly support what agents do during calls Use role-based access Only expose panels to the teams that need them Voice Interaction Panels The following panels are available within the Voice Interaction workspace . Availability depends on enabled features, integrations, and licenses in the environment. Panel Description Agent Assist Real-time transcription, AI suggestions, knowledge article recommendations, intent detection Agent Assist (CCAI) Google Contact Center AI — speech-to-text, smart reply suggestions, knowledge recommendations Callback Displays callback interactions assigned to agent with dial controls and outcome tracking Canned Responses Insert predefined messages from response libraries during voice interactions Customer Journey Interaction timeline showing previous customer touches across all channels Notes Record interaction notes for documentation and follow-up Profile Customer identity, contact attributes, and synchronized CRM data Wrap-Up Classify interaction outcome with wrap-up codes and manage ACW Interaction Panels by Channel System-created panels that appear when an interaction is active: Channel Panel Features Voice Call controls (hold, mute, transfer, conference), dial pad, notes, wrap-up codes Chat Real-time messaging, canned responses, file sharing, typing indicators Message (WhatsApp/SMS) Asynchronous conversations, persistent thread history, attachments Email Email composition, templates, attachments, threaded conversation history Callback Scheduled callback details, dial controls, wrap-up codes Social Messaging Social platform messages, thread tracking, media attachments Interview Cheat Sheet Question Answer What is Panel Manager used for? Embedding external tools (CRM, dashboards, internal apps) into the agent desktop What URL protocol is required? HTTPS — HTTP will not load What is the difference between Interaction Panels and Custom Panels? Interaction panels manage conversations; custom panels provide supporting tools What is the Agent Assist panel? AI-driven panel with real-time transcription, suggestions, and knowledge recommendations What does the Customer Journey panel show? Previous customer interactions across all channels Scripts Topic Detail Navigation Admin → Contact Center → Scripts Purpose Guided UI forms presented to agents during interactions — collect data, enforce workflows, ensure compliance Channels Primarily voice; also supports chat and messaging workflows Deployment Must be Published before agents can use them; assign to queue or Architect flow Overview Scripts are agent-facing forms that pop on the agent desktop when an interaction begins. They guide agents through structured workflows, collect customer information, enforce compliance steps, and integrate with backend systems via interaction attributes. Script Components Component Description Labels Static instructions or text displayed to agents Text Input Free text data entry field Number Input Numeric value field Dropdown List Selection from predefined options Checkbox Binary selection (Yes/No) Buttons Trigger actions such as form submission or navigation to next step Page Sections Organize the script layout visually Data Bindings Connect script fields to interaction attributes for use in Architect flows or reporting Implementation Steps Step Action 1 Navigate to Admin → Contact Center → Scripts 2 Click Create Script 3 Define script name and interaction type (Voice, Chat, Email, etc.) 4 Design the layout using UI components 5 Bind fields to interaction attributes 6 Apply conditional display logic if needed 7 Publish the script 8 Assign script to a queue (via queue's Default Script field) or Architect flow ⚠️ Scripts must be Published before they can be assigned or used by agents. Unpublished scripts are not available for selection. Conditional Logic Scripts support conditional display — fields appear or hide based on previous selections: Condition Result Issue Type = Billing Display billing section only Issue Type = Technical Display troubleshooting checklist Issue Type = Sales Display sales workflow and offer prompts Script Data Integration Integration Description Interaction Attributes Stores collected data during the interaction — accessible in reporting and Architect Architect Flows Scripts pass captured data into flow logic for routing decisions or automations CRM Systems Data entered by agents can be pushed to external CRM systems via Data Actions APIs Scripts can trigger backend processes through integrations Example Agent Workflow Step Agent Action 1 Customer call arrives 2 Script automatically opens on agent desktop 3 Agent verifies customer information 4 Agent selects issue category 5 Script dynamically displays relevant fields 6 Agent collects required information 7 Data stored in interaction attributes 8 Agent selects wrap-up code Best Use Scenarios Scenario Benefit Customer Verification Ensures identity checks are completed consistently Sales Calls Guides agents through offers and upsell prompts Technical Support Provides structured troubleshooting steps Compliance Workflows Ensures required regulatory statements are delivered Case Creation Collects structured data for CRM tickets Best Practices Practice Recommendation Keep scripts simple Avoid excessive fields that slow agents during live calls Use conditional logic Display only fields relevant to the current issue type Integrate with CRM Auto-populate customer data where possible Reuse templates Maintain standardized workflows across teams Test before deployment Validate with real call scenarios before publishing Publish before assigning Scripts must be published to appear in queue or flow assignment dropdowns Interview Cheat Sheet Question Answer What is a Script in Genesys Cloud? A guided UI form that pops on the agent desktop during interactions What must happen before a script can be used? It must be Published Where can scripts be assigned? To a queue (Default Script field) or Architect flow What are Data Bindings? Connections between script fields and interaction attributes What does conditional display do? Shows or hides fields based on previous agent selections What channels support scripts? Primarily voice, also chat and messaging Assistants Topic Detail Navigation Admin → Contact Center → Assistants Purpose AI-powered virtual agents (bots) using NLU to handle voice and digital interactions automatically Technology Natural Language Understanding (NLU) Integration Works with Knowledge Base and Architect flows Overview Assistants are AI-powered automation tools that enable organizations to build virtual agents capable of interacting with customers through voice and digital channels. They use Natural Language Understanding (NLU) to interpret customer requests and respond using knowledge articles, intents, and Architect flows. Assistants are most effective for automating predictable, repetitive interactions — reducing call volume, improving self-service, and lowering operational costs. Assistant Components Component Description Intents The goal or purpose of the customer's request (e.g., Check_Order_Status, Reset_Password) Utterances Example phrases customers might say to express an intent — used to train the NLU model Entities Variables extracted from customer input (e.g., order number, city, product name) Slots Structured data fields collected during a conversation to fulfill an intent Actions Responses or operations the assistant performs when an intent is matched Knowledge Integration Allows the assistant to answer questions directly from knowledge base articles Architect Flow Integration Transfers conversation control to an Architect flow for advanced routing or logic Configuration Settings Option Description Language NLU processing language — determines which utterance model is used Confidence Threshold Minimum confidence score required to trigger an intent — below this, fallback intent fires Fallback Intent Default action when no intent is recognized (e.g., transfer to agent) Disambiguation Prompts the customer to clarify when multiple intents closely match Example Assistant Flow Customer: "I want to check my order status" ↓ Intent Detected: Order_Status ↓ Extract Entity: Order_Number ↓ Call API via Data Action / Architect Flow ↓ Return Response to Customer ↓ (If unresolved) Escalate to Human Agent Best Use Scenarios Scenario Description Customer Self-Service Resolve common issues without agent involvement FAQ Automation Answer frequently asked questions automatically using knowledge articles Order / Account Status Retrieve order status, balance, or appointment info via API Call Routing by Intent Identify customer intent and route to the correct queue After-Hours Support Provide automated assistance when agents are unavailable Integration Points Integration Description Architect Flows Advanced routing or automation logic triggered by the assistant Knowledge Base Automated responses using knowledge articles — improves containment rate Digital Channels Chat, messaging (WhatsApp, SMS), and Web Messaging Voice Channels Voice bots for IVR interactions — speech recognition + NLU Data Actions API calls triggered by the assistant to retrieve or update external data Best Practices Practice Recommendation Start with high-volume intents Automate the most frequent customer requests first for maximum impact Keep intents simple Avoid overly complex intent structures that reduce NLU accuracy Use knowledge articles Well-written articles dramatically improve bot containment rate Train with real customer data Use actual customer utterances — not hypothetical ones Monitor analytics continuously Review bot performance, confidence scores, and fallback rates regularly Provide easy escalation Always ensure customers can reach a human agent quickly when needed Interview Cheat Sheet Question Answer What technology do Assistants use? Natural Language Understanding (NLU) What is an Intent? The goal or purpose of the customer's request What are Utterances used for? Training the NLU model with example customer phrases What is an Entity? A variable extracted from customer input (e.g., order number) What happens when confidence is below the threshold? The Fallback Intent fires — typically escalates to a human agent What is Disambiguation? Prompts the customer to clarify when multiple intents closely match Knowledge Base Topic Detail Navigation Admin → Knowledge Purpose Create and manage AI-powered knowledge bases with Q&A articles surfaced to agents, bots, and self-service portals Technology Natural Language Understanding (NLU) + Generative AI answer generation Max Knowledge Bases 500 per organization Max Articles per KB 15,000 articles ✅ Verified against Genesys Cloud Resource Center — March 2026 Licensing Requirements License Knowledge Access Genesys Cloud CX 1 Not included — requires Digital Add-on II or AI Experience tokens Genesys Cloud CX 1 + AI Experience tokens Access granted without Digital Add-on II Genesys Cloud CX 1 Digital Add-on II Included Genesys Cloud CX 2 / CX 2 Digital Included Genesys Cloud CX 3 / CX 3 Digital Included Genesys Cloud CX 4 Included Required Permissions Permission Purpose Knowledge > All Full knowledge base administration Analytics > Knowledge Aggregate > All View knowledge analytics Responses > Library > All Manage response libraries Response Assets > Asset > All Manage embedded media assets Overview — How Knowledge Base Works The knowledge base stores question and answer (Q&A) pairs called articles. When a customer or agent asks a question, Genesys Cloud AI uses Natural Language Understanding to find the closest matching article and return the answer. The knowledge base powers four key touchpoints: Touchpoint Description Agent Copilot Automatically surfaces relevant articles to agents during live interactions — no manual search required Virtual Agents / Bots Architect bot flows query the knowledge base and return answers to customers during self-service Knowledge Portal Customer-facing self-service website — customers search articles, browse by category, or escalate to an agent Messenger Web Messenger deployments can query knowledge articles in bot conversations Step 1 — Create a Knowledge Base Navigate to Admin → Knowledge → Articles Click the Knowledge Base list dropdown → Create Knowledge Base Enter a Name (e.g., IT Support KB , Billing FAQ ) Optional: Add a description Select the Language for content (e.g., English - US) Click Create ⚠️ Language selection is permanent — it determines which NLU model processes the content. Create separate knowledge bases for each supported language if your contact center is multilingual. Step 2 — Create Categories & Labels (Optional) Categories and labels organize articles for easier management and navigation. Categories Categories group articles by topic and support nested hierarchies (parent → child). Navigate to Admin → Knowledge → Categories & Labels Under Category Name , enter a name (e.g., Billing , Technical Support ) Optional: Select a parent category to nest it (e.g., Technical Support > VoIP Issues ) Click Create Category Labels Labels are color-coded tags for quick filtering and content reuse across portals. Click the Labels tab Enter a Label Name Select a Label Color Click Create Label 💡 March 2026: Knowledge portals can now be configured to return only articles matching specific labels — a single article can be reused across multiple portals with different label filters applied. Step 3 — Create Articles Articles are individual Q&A pairs. Each article has one primary question and one answer. Create a New Article Navigate to Admin → Knowledge → Articles Open the target knowledge base Click Create Article Under Question , enter the primary question (e.g., How do I reset my password? ) Optional: Assign a Category In the Content for the answer box, add the answer Click Save or Save & Close Import Articles (Bulk) Open the knowledge base → Click Import Select a .json file containing Q&A pairs Genesys Cloud validates the file for errors Click Import to confirm — pairs are imported as individual FAQ articles Step 4 — Format Articles Format Option Description Text Styling Bold, italic, bullet lists, headings Images Upload images directly into the answer body Videos Embed video via URL Rich Text Full HTML-style formatting for structured answers Step 5 — Add Phrasings (Alternative Questions) Phrasings are alternative ways customers might phrase the same question — used to train the NLU model for better matching accuracy. Open an article → click the Phrasings tab Add an alternative phrase (e.g., How do I change my password? , Forgot my password ) Optional: Enable Autocomplete — generates the phrase as a search prediction when customers type in the portal Click Save 💡 More phrasings = better NLU accuracy. Use real customer language, not formal documentation language. Step 6 — Test Articles Open the knowledge base In the Test Articles pane, type a test question and press Enter The system returns the matched article with a Confidence Percentage Confidence Level Meaning High (80–100%) Strong match — article surfaces reliably Medium (50–79%) Acceptable — consider adding more phrasings Low (<50%) Weak match — improve phrasing or content Step 7 — Publish Articles Open the article Click Publish to publish and continue editing Or Publish & Close to publish and exit ⚠️ Unpublished articles are invisible to all touchpoints — agents, bots, and the portal will not see them. Article Touchpoint Variations The same article can have different answer content per touchpoint — tailoring responses for agents vs. bots vs. self-service portals. Touchpoint Use Case Agent Assist / Agent Copilot Detailed internal answer with troubleshooting steps and escalation guidance Bot Flow (Dialog Engine / Digital) Short, conversational response suitable for bot delivery Knowledge Portal Formatted customer-facing answer with images and links Messenger Concise answer for Web Messenger bot conversations Third-Party Knowledge Base Integration Genesys Cloud supports connecting external knowledge systems so their content appears in Agent Copilot, Messenger, and the portal alongside native articles. Integration Sync Type Notes Salesforce Knowledge Automatic or Manual Select channels and categories to sync ServiceNow Knowledge Automatic or Manual Standard template articles only SharePoint Via Knowledge Fabric Configured through Knowledge Configuration Adding a Third-Party Source Navigate to Admin → Knowledge → Sources Click Add Source — name it, select sync type, select provider Configure language, categories, and channel filters Click Add Source ⚠️ The third-party integration must first be configured in Admin → Integrations before it appears as a source option here. Knowledge Configuration (Knowledge Fabric) Knowledge Configuration defines how knowledge is presented across Genesys touchpoints using a unified layer that can combine multiple knowledge bases and third-party sources. Feature Detail Navigation Admin → Knowledge → Knowledge Configuration Purpose Unified knowledge source for Agent Copilot and Virtual Agents — supports generative AI answers AI Answer Generation Combines content from multiple relevant articles into a single dynamic response Virtual Agent Use From February 2026 — bots use either Knowledge Workbench V2 or Knowledge Fabric — one at a time, selected in Architect 💡 February 2026: Bot authors can now select a Knowledge Fabric configuration in Architect and control generative answer mode and bias settings per flow. Existing rules-based bots using Workbench V2 are unaffected. Agent Copilot & Knowledge Agent Copilot uses the knowledge base to automatically surface articles to agents during live interactions. Feature Description Automatic Surfacing Articles appear in the Agent Copilot panel based on conversation context Answer Highlighting Highlights the most relevant passage within a lengthy article Knowledge Sharing Agents can send articles directly to customers with one click Interaction Summaries AI-generated summaries at end of interactions using conversation + knowledge context Wrap-Up Code Suggestions Copilot suggests wrap-up codes based on the conversation Knowledge Portal The Knowledge Portal is a customer-facing self-service website powered by the knowledge base. Feature Description Article Search Customers search using natural language — NLU finds the best match Category Browsing Customers navigate by category hierarchy Chatbot Access Customers can escalate to a bot or live agent directly from the portal Label Filtering Portals can filter articles by label (March 2026 feature) Customization Configurable colors, messaging, and branding Knowledge Analytics Metric Description Top Articles Most frequently accessed articles by agents and customers Search Success Rate Percentage of searches returning a useful result Search Failure Rate Searches returning no relevant result — indicates content gaps Confidence Scores AI match confidence per article returned Containment Rate Issues resolved through self-service without agent escalation Interview Cheat Sheet Question Answer Max knowledge bases per org? 500 Max articles per knowledge base? 15,000 What must happen before an article is live? It must be Published What is a Phrasing? An alternative way a customer might ask the same question — trains the NLU model What does Confidence Percentage mean? How closely a query matches the article — higher = better match What are the four main touchpoints for knowledge? Agent Copilot, Virtual Agents/Bots, Knowledge Portal, Messenger What is the Knowledge Portal? A customer-facing self-service website for searching and browsing articles What third-party sources can be integrated? Salesforce Knowledge, ServiceNow Knowledge, SharePoint (via Knowledge Fabric) What is Knowledge Fabric / Knowledge Configuration? A unified knowledge layer combining multiple sources with generative AI answers for Agent Copilot and Virtual Agents Can a bot use both Workbench V2 and Knowledge Fabric? No — one at a time, selected in Architect per bot flow (February 2026) Chat & Messaging Configuration Topic Detail Navigation Menu → Digital and Telephony → Message → Platform Integrations Purpose Connect third-party messaging channels (WhatsApp, Facebook, Instagram, SMS, LINE, X/Twitter, Apple Messages) to Genesys Cloud ACD routing Routing Engine All messaging interactions route through Architect Inbound Message Flows Conversation Grouping Multiple messages from the same customer within 72 hours are grouped into a single interaction ✅ Verified against Genesys Cloud Resource Center — March 2026 Overview — ACD Messaging Genesys Cloud ACD messaging enables agents to send and receive interactions from messaging channels like Facebook Messenger, X (Twitter) DM, LINE, WhatsApp, SMS, web messaging, and open messaging. Messages work like other interaction types — you can set alerting timeouts, service levels, use scripts, and view analytics. Key behaviors: Genesys Cloud attempts to route message replies to the last handling agent. Messages are asynchronous but Genesys Cloud groups multiple messages into a single interaction if they occur within 72 hours — allowing the same agent to handle all messages in the conversation and see the interaction history. Agents complete wrap-up on each portion of a multi-message interaction. Supported Messaging Channels Channel Type Notes Web Messaging Native Genesys Persistent/async — configured via Messenger Deployments (see Widgets page) SMS Native Requires provisioned DID or Short Code in SMS Inventory WhatsApp Business Third-party Requires Meta Business Manager account + voice/SMS number ownership Facebook Messenger Third-party Requires a Business Facebook page with Messenger enabled Instagram DM Third-party Requires a business Instagram account X (Twitter) DM Third-party Requires a registered X business handle Apple Messages for Business Third-party Separate ACD setup required LINE Third-party Supported via API/professional services Open Messaging Custom API Connects any custom channel via outbound notification webhook Platform Integration Setup All third-party messaging channels are configured from a central location: Menu → Digital and Telephony → Message → Platform Integrations You can create and manage integrations for the following platforms: Apple Messaging for Business, Direct Messaging, Facebook, Instagram Social Listening, WhatsApp, and X (Twitter). All integrations can be managed and updated from the centralized Messaging Platforms page. WhatsApp Configuration Prerequisites Meta Business Manager account — business must be verified with Meta A voice or SMS number provisioned and owned by the customer (not Genesys) Customer retains ownership of the number while the WhatsApp account is active Setup Path Navigate to Menu → Digital and Telephony → Message → Platform Integrations Click Add Integration → WhatsApp Use the WhatsApp Embedded Signup Flow to connect via Meta Business Manager Link the provisioned phone number to the integration Configure the integration name and routing settings Assign an Architect Inbound Message Flow to handle routing Key WhatsApp Rules Rule Detail 24-hour response window Agents must reply within 24 hours of the customer's last message After 24 hours Only Message Templates (pre-approved by Meta) can be sent — free-text responses are blocked Opt-in requirement Meta requires explicit customer opt-in before outbound WhatsApp messages can be sent — captured via IVR, website, or SMS Outbound throughput Up to 18,000 messages/minute for outbound campaigns; up to 3,000 messages/minute for agentless API messages (as of February 2026) Voice notes Agents can play back, record, and download .ogg voice note files within WhatsApp conversations Facebook Messenger Configuration Prerequisites A business Facebook page with Messenger enabled Facebook Business account Setup Path Navigate to Menu → Digital and Telephony → Message → Platform Integrations Click Add Integration → Facebook Authenticate with your Facebook Business account Select the Facebook page to connect Assign an Architect Inbound Message Flow Instagram Direct Message Configuration Prerequisites A business Instagram account linked to a Facebook Business page Setup Path Navigate to Menu → Digital and Telephony → Message → Platform Integrations Click Add Integration → Instagram Authenticate via Facebook Business Manager (Instagram is connected through Meta) Select the Instagram account Assign an Architect Inbound Message Flow X (Twitter) Direct Message Configuration Prerequisites A registered X (Twitter) business handle Setup Path Navigate to Menu → Digital and Telephony → Message → Platform Integrations Click Add Integration → X (Twitter) Authenticate with your X business account Assign an Architect Inbound Message Flow Open Messaging (Custom Channels) Open Messaging allows connection to any custom messaging platform not natively supported by Genesys Cloud — such as Telegram, WeChat, custom apps, or proprietary enterprise messaging tools. Feature Detail Method Outbound Notification Webhook — Genesys sends and receives messages via your middleware Middleware Customer is responsible for building and maintaining middleware between Open Messaging and the external platform Routing Full ACD routing, skills, queues, and analytics apply like any native channel Routing Architecture for All Messaging Channels All messaging channels — without exception — route through Architect Inbound Message Flows before reaching an agent. Customer sends message (WhatsApp / FB / SMS / etc.) ↓ Platform Integration receives message ↓ Architect Inbound Message Flow ├── Bot automation (optional) ├── Customer identification ├── Data collection └── Transfer to ACD Queue ↓ Agent receives interaction Character Limits by Channel Message composition supports channel-specific character limits: WhatsApp and web messaging (4,000), Facebook (2,000), Instagram (1,000), SMS (160/765), and Apple Messages for Business (2,000). Channel Character Limit WhatsApp 4,000 Web Messaging 4,000 Facebook Messenger 2,000 Apple Messages for Business 2,000 Instagram DM 1,000 SMS (standard segment) 160 SMS (Unicode/extended) 765 File Attachments by Channel Channel Supported Formats Max Size WhatsApp JPG, PNG, GIF, PDF, voice notes (.ogg) Platform limit Facebook Messenger JPG, PNG, GIF Platform limit Apple Messages for Business Multiple formats 100 MB Web Messaging JPG, PNG, GIF Platform limit Multiple file attachments are sent as individual messages — not bundled. Agent Behavior — Messaging Interactions Feature Detail Conversation history Agents see prior bot and agent conversation transcripts Delivery status Pending / Delivered / Failed indicators per message Canned responses Available in all messaging channels Voice notes WhatsApp only — agents can record, play back, and download Data filtering From February 2026 — outbound messages can be checked against admin-defined content filters (profanity, regex patterns) Authentication indicator Green shield shown for authenticated web messaging sessions Customer Responsibilities When integrating third-party messaging channels, the customer (not Genesys) is responsible for: Responsibility Detail Platform accounts Owning and maintaining all third-party business accounts (Meta, X, Instagram) Number ownership WhatsApp phone numbers are owned by the customer, not Genesys Meta Business Verification Required before WhatsApp can be activated Terms of Service compliance Must adhere to each platform's messaging terms and policies Open Messaging middleware Custom channel integrations require customer-built middleware Interview Cheat Sheet Question Answer Where are messaging platform integrations configured? Menu → Digital and Telephony → Message → Platform Integrations How long before messages from the same customer are grouped? 72 hours What happens with WhatsApp after 24 hours? Free-text replies are blocked — only pre-approved Message Templates can be sent What is the WhatsApp outbound campaign throughput limit? 18,000 messages per minute (February 2026) What is Open Messaging used for? Connecting custom or unsupported channels via webhook + customer middleware Who owns the WhatsApp phone number? The customer — not Genesys What is the SMS character limit per standard segment? 160 characters What routes all messaging interactions? Architect Inbound Message Flows What is the file attachment limit for Apple Messages for Business? 100 MB Outbound Dialing — Overview & Settings Topic Detail Navigation Admin → Outbound or Menu → Digital and Telephony → Outbound Purpose Configure and run automated outbound call and messaging campaigns to contact lists of customers Dialing Modes Preview, Progressive, Power, Predictive, Agentless, External Campaign Types Voice Campaigns, Digital Campaigns (SMS/Email/WhatsApp) ✅ Verified against Genesys Cloud Resource Center — March 2026 Outbound Module Overview Outbound in Genesys Cloud allows organizations to proactively reach customers through automated dialing campaigns. The system manages who to call, when to call them, how to dial, and what happens based on the result — including compliance controls like Do Not Call (DNC) lists and callable time windows. Key Outbound Objects Object Description Contact Lists The list of people to contact — phone numbers, names, and custom data fields DNC Lists Do Not Call lists — numbers the system will never dial Campaigns The configuration that defines dialing mode, contact list, queue, rules, and schedule Attempt Controls Limits on how many times a contact can be attempted Callable Time Sets Time windows defining when dialing is allowed (by time zone) Call Analysis Response Tables Rules for what to do when a live person, answering machine, or busy signal is detected Rule Sets Logic-based call rules and campaign rules applied during dialing Campaign Sequences Chained campaigns that run in order — start/stop the sequence instead of individual campaigns Wrap-Up Code Mappings Maps agent wrap-up codes to campaign outcomes (e.g., "Resolved" = stop calling this contact) Outbound Settings (Org-Level) Admin → Outbound → Outbound Settings These settings apply to all campaigns in the organization. Setting Description Default / Limit Max Calls Per Agent Maximum simultaneous outbound calls placed per available agent 1.0–15.0 Max Line Utilization Percentage of Edge lines available for outbound campaigns Configurable Compliance Abandon Threshold Seconds allowed before a queue-transferred call is classified as a Compliance Abandon 2 seconds default Calls Subject to Compliance Abandon Rate Choose: All Calls or Calls That Reached the Queue Configurable Reschedule Time Zone Skipped Contacts Automatically reschedules contacts skipped due to time zone restrictions Optional Max Calls Per Second (CPS) Maximum calls dialed per second across the entire org 15 CPS default — increase via Care case ⚠️ Each Edge handles up to 350 lines. To increase CPS beyond 15, open a Genesys Care case with telephony model and business justification. Turnaround is typically 10 business days. Outbound Organization Limits Object Limit Simultaneous voice campaigns running 50 Simultaneous digital campaigns running 25 Skills-based dialing campaigns 5 Max contacts per organization 5,000,000 Max contacts per contact list 1,000,000 Max DNC records per DNC list 1,000,000 Max DNC records per org 2,000,000 Max contact list columns 50 Max phone number columns per list 10 Max queue members (skills-based dialing) 500 Max queue members (agent-owned campaign) 200 Max queue members (any campaign) 1,000 Campaign priority range 1 (lowest) to 5 (highest) Preview campaign duration 1 second to 20 minutes Callback advance scheduling Up to 30 days Phone number minimum digits 10 digits, E.164 format Schedules per campaign 1 Schedule intervals per campaign 500 Automatic Time Zone Mapping (ATZM) ATZM automatically assigns a time zone to each contact record based on their phone number or postal code, ensuring calls are only placed during compliant hours. Setting Default Mapped contacts calling window 8:00 AM – 9:00 PM local time Unmapped contacts calling window 2:00 PM – 8:00 PM EST Supported countries United States (default), Canada (opt-in) ⚠️ ATZM from outside North America to dial North American numbers requires the Genesys Cloud org to reside in a North American AWS region. Canadian postal codes must use the format A1A 1A1 (7 characters with space after 3rd character). Campaign Priority When multiple campaigns share the same queue, Priority (1–5) determines proportional call distribution: Higher priority campaigns receive more calls per agent over time Equal priority campaigns share lines proportionally Agents participate automatically in multiple campaigns via shared queues Access Control (Divisions) Outbound campaigns support division-based access control — different admin teams can be restricted to manage only their own campaigns: Assign the Outbound Admin role to a group Assign a specific Division to that role Only campaigns in that division are visible and manageable by that group Interview Cheat Sheet Question Answer Where are org-level outbound settings configured? Admin → Outbound → Outbound Settings What is the default CPS limit? 15 calls per second — increase via Care case What is the default compliance abandon threshold? 2 seconds What is ATZM? Automatic Time Zone Mapping — assigns time zones to contacts to enforce compliant calling windows Default calling window for mapped contacts? 8:00 AM – 9:00 PM local time Default calling window for unmapped contacts? 2:00 PM – 8:00 PM EST Max contacts per org? 5,000,000 Max contacts per contact list? 1,000,000 How many voice campaigns can run simultaneously? 50 How many digital campaigns can run simultaneously? 25 Outbound Dialing Modes Topic Detail Navigation Admin → Outbound → Campaign Management Purpose Select the dialing strategy that determines how the system places calls and connects agents Default Mode Preview Number of Modes 6 — Preview, Progressive, Power, Predictive, Agentless, External ✅ Verified against Genesys Cloud Resource Center — March 2026 Dialing Mode Comparison Mode Who Dials Agent Required Best For Min Agents Preview Agent manually Yes High-value sales, debt collections, B2B 1+ Progressive System — 1 call per agent Yes Compliance-sensitive, moderate volume Any Power System — multiple per agent Yes High volume with controlled abandonment 15+ recommended Predictive System — AI-paced Yes Maximum efficiency, large call centers 15+ required Agentless System — no agent No Notifications, surveys, IVR delivery, reminders None External System — routes to external Yes Routing to external agents or systems Any Preview Mode In Preview mode, the agent receives a contact record and manually decides when to dial . Feature Detail Agent control Agent reviews contact info before calling Timer Optional countdown — system auto-dials when timer expires Agent-owned records Agents can own specific contacts and handle all retries Efficiency Lowest efficiency — highest quality per contact Compliance Safest mode — no risk of abandoned calls from over-dialing Best use Collections, high-value B2B sales, sensitive outreach requiring personalization ⚠️ Preview campaigns ignore pacing options — the agent controls the pace entirely. Progressive Mode In Progressive mode, the system automatically dials exactly one call per available agent . Feature Detail Dialing ratio 1 call : 1 available agent — always Abandoned calls Near-zero risk — there is always an agent ready when a contact answers Call analysis Detects live person vs. answering machine before connecting to agent Efficiency Moderate — no wasted agent time waiting for answers, but no over-dialing Compliance Excellent — guarantees agent availability; no abandoned call risk Best use Compliance-sensitive environments, smaller agent pools, regulated industries 💡 Progressive is the recommended mode when you have fewer than 15 agents and cannot use Predictive. Power Mode Power mode dials multiple calls per available agent using a pacing algorithm. Feature Detail Dialing ratio More than 1 call per agent — determined by pacing algorithm Pacing Algorithm predicts when an agent becomes available and pre-dials accordingly Call analysis Required — system drops or routes unanswered/machine calls Abandoned calls Risk exists — compliance abandon monitoring required Efficiency High — maximizes agent talk time Compliance Monitor abandon rate carefully — FTC/OFCOM limits apply Best use High-volume campaigns where efficiency is more important than zero abandons Min agents recommended 15+ Predictive Mode Predictive mode uses a patented stage-based AI algorithm to forecast agent availability and pre-dial contacts accordingly. Feature Detail Dialing System automatically places calls based on predicted agent availability Algorithm Patented pacing — adjusts dynamically based on real-time agent stats Call analysis Full detection — live person, answering machine, busy, no answer Efficiency Highest — maximizes talk time, minimizes idle time Abandoned calls Risk exists — pacing must be tuned to stay within compliance thresholds Min agents required 15 agents minimum — smaller pools make predictions inaccurate Best use Large-volume outbound operations (sales, collections, surveys) with 15+ agents ⚠️ With fewer than 15 agents, Predictive's algorithm lacks sufficient data — use Progressive instead. Agentless Mode Agentless mode dials contacts and delivers pre-recorded messages, surveys, or IVR flows without connecting to a live agent . Feature Detail Agent required No Content Recorded voice messages, IVR flows, opt-out prompts Opt-out Include "Press 9 to opt out" in the IVR flow to manage DNC compliance Answering machine System can detect and play a different message for machines vs. live answers Live party Call is transferred to an Architect Inbound Call Flow for IVR handling Requires Inbound Agentless campaigns require Inbound call routing to be implemented Best use Appointment reminders, payment notifications, fraud alerts, surveys, outage notifications External Calling Mode External calling routes answered calls to an external phone number or SIP destination instead of an internal Genesys Cloud queue. Feature Detail Routing Calls are bridged to an external system or phone number Use case Third-party agent environments, outsourced contact centers Call Analysis Call Analysis (also called AMD — Answering Machine Detection) is the process of detecting what answered the call before connecting it to an agent or playing a message. Detection Result Default Action Live Person Connect to agent or play IVR Answering Machine Disconnect, play message, or leave voicemail Busy Signal Record result, retry based on attempt control No Answer Record result, retry based on attempt control Invalid Number Mark uncallable Call analysis is configured in a Call Analysis Response Table , which is then assigned to a campaign. Campaign Priority When multiple campaigns share the same ACD queue, priority determines how lines are distributed: Priority Effect 1 Lowest — fewest calls per agent relative to other campaigns 5 Highest — proportionally more calls per agent Agents participate in multiple campaigns automatically via the queues they are active in. No manual assignment per campaign is needed. Choosing the Right Dialing Mode Scenario Recommended Mode High-value B2B sales — agent needs to personalize each call Preview Collections — compliance-sensitive, regulated Progressive High-volume sales, 15+ agents, moderate compliance risk Power Maximum efficiency, large center, 15+ agents Predictive Appointment reminders, payment alerts, fraud notifications Agentless Fewer than 15 agents, need auto-dialing Progressive Interview Cheat Sheet Question Answer What is the default campaign dialing mode? Preview Which mode dials 1 call per available agent? Progressive Which mode requires minimum 15 agents? Predictive (and recommended for Power) Which mode has no agents involved? Agentless What is Call Analysis? Detection of live person, answering machine, busy, or no answer before connecting to agent What is the abandoned call risk in Progressive mode? Near-zero — one call per agent guarantees availability What happens with fewer than 15 agents in Predictive mode? Pacing predictions become inaccurate — use Progressive instead What must Agentless campaigns implement? Inbound call routing (Architect flow) Outbound — Contact Lists & DNC Topic Detail Navigation Admin → Outbound → Contact Lists and Admin → Outbound → DNC Lists Purpose Manage the lists of contacts to dial and the numbers that must never be dialed Max contacts per org 5,000,000 Max contacts per list 1,000,000 Max DNC records per list 1,000,000 Max DNC records per org 2,000,000 ✅ Verified against Genesys Cloud Resource Center — March 2026 Contact Lists A contact list is the "phone book" for a campaign — it contains the names, phone numbers, and custom data fields for every person the campaign will attempt to reach. Contact List Structure Field Detail Columns Up to 50 columns per list Phone number columns Up to 10 phone number columns per list (e.g., mobile, home, work) Column header character limit 128 characters Column entry character limit 512 characters Phone number format Minimum 10 digits, E.164 format required One campaign at a time A contact list can only be on one running campaign at a time Creating a Contact List Navigate to Admin → Outbound → Contact Lists Click Create Name the contact list Define columns — at minimum one phone number column Select the phone number column type for each phone column Click Save Importing Contacts Open the contact list Click Import Upload a CSV file — columns must match the list definition The system validates and imports contacts 💡 Contact lists can be generated from CRM or marketing systems and uploaded on a one-time, recurring, or trigger-based basis. Contact List Filters Contact list filters allow you to run a campaign against a subset of a contact list without creating a separate list: Filter by any column value (e.g., only contacts in a specific state or with a specific status) Assigned to a campaign in the Campaign Editor Up to 1,000 contact list filters per org Attempt Controls Attempt controls limit how many times a contact or phone number can be called, preventing excessive re-dialing. Setting Description Max attempts per phone number Stop calling a specific number after N attempts Max attempts per contact Stop calling the entire contact record after N total attempts Recall time How long to wait before retrying a contact Reset period After this period, the attempt counter resets (e.g., every 24 hours) Phone type-specific limits February 2026 update — configure different attempt limits per phone type (mobile, home, work) 💡 February 2026 update: Administrators can now set phone type-specific attempt limits, extend recall times, and adjust reset periods with greater precision. DNC Lists (Do Not Call) A DNC list is a data source of phone numbers that must never be dialed by any campaign. The system checks contact phone numbers against all assigned DNC lists before placing each call. Types of DNC Type Description Internal DNC Organization's own DNC list — uploaded and managed in Genesys Cloud Campaign-specific DNC Assigned to specific campaigns only Wrap-up triggered DNC Agent selects a wrap-up code that automatically adds a number to DNC Contact-level DNC Agent or system flags an entire contact (not just a number) as uncallable Creating a DNC List Navigate to Admin → Outbound → DNC Lists Click Create Name the DNC list Click Save Importing DNC Numbers Open the DNC list Click Import Upload a CSV of phone numbers The system validates and imports Assigning DNC to a Campaign DNC lists are assigned in the Campaign Editor during campaign configuration. A campaign can have multiple DNC lists assigned — all are checked before each dial attempt. Agent-Triggered DNC To allow agents to add numbers to DNC during a call: Configure a wrap-up code mapped to the DNC action Or include a DNC button in the agent Script The number is immediately flagged and will not be dialed again Callable Time Sets Callable time sets define when a campaign is allowed to dial for each time zone. This works alongside ATZM to ensure compliance with regulations like the Telephone Consumer Protection Act (TCPA). Feature Description Navigation Admin → Outbound → Callable Time Sets Purpose Define allowed dialing hours by day of week and time zone Integration Assigned to a campaign — overrides or supplements ATZM defaults Override Callable times can be overridden; callable days cannot Contact Management During a Campaign Action Description Dynamic queueing Contacts are re-sorted at attempt time — most current data is used Filter changes honored If a contact list filter changes during a running campaign, the campaign honors the update Skip time zone contacts Contacts outside the callable window are skipped and optionally rescheduled via ATZM Mark uncallable A wrap-up code or call rule can flag a number or entire contact as permanently uncallable Interview Cheat Sheet Question Answer Max contacts per org? 5,000,000 Max contacts per contact list? 1,000,000 Max DNC records per list? 1,000,000 Max DNC records per org? 2,000,000 Max phone number columns per contact list? 10 Can a contact list be on multiple running campaigns? No — only one running campaign at a time What format must phone numbers use? E.164 format, minimum 10 digits What is an Attempt Control? Limits on how many times a contact or number can be dialed What does a DNC list do? Prevents listed numbers from being dialed by any campaign it is assigned to How can agents add a number to DNC? Via wrap-up code mapped to DNC action, or DNC button in agent script Outbound — Campaign Configuration Topic Detail Navigation Admin → Outbound → Campaign Management Purpose Create and configure outbound campaigns — defines who to call, how to dial, and what rules to apply Campaign Types Voice Campaigns, Digital Campaigns (SMS, Email, WhatsApp) ✅ Verified against Genesys Cloud Resource Center — March 2026 Campaign Editor Overview The Campaign Editor is a step-by-step configuration wizard. The first decision is always the Dialing Mode — this determines which other settings are available. Campaign Editor Required Resources Before creating a campaign, ensure the following exist: Resource Why It's Needed Contact List The list of contacts to dial ACD Queue Where answered calls route to (agent-assisted modes) DNC List (optional) Numbers to exclude Callable Time Set (optional) Allowed dialing hours Call Analysis Response Table What to do with live answer / machine / busy / no answer Agent Script (optional) Screen pop for agents when they receive the call Rule Set (optional) Logic-based conditions applied pre-call or at wrap-up Creating a Campaign Navigate to Admin → Outbound → Campaign Management Click the Voice Campaigns tab (or Digital Campaigns for SMS/Email) Click Create Campaign Select Dialing Mode — this is the first and most important decision Complete all required fields per the mode Click Save Core Campaign Settings General Field Description Campaign Name Unique name for the campaign Division Controls which admin teams can manage this campaign Dialing Mode Preview, Progressive, Power, Predictive, Agentless, External Priority 1 (lowest) to 5 (highest) — affects line distribution when sharing a queue Contact List & Filtering Field Description Contact List The source list of contacts to dial Contact List Filter Optional — dial only a subset of the contact list Contact Sort Define sort order before dialing begins (up to 4 sort columns) Dynamic Queueing Re-sort contacts at attempt time — uses most current data Queue & Routing Field Description ACD Queue Queue where answered calls are delivered to agents Script Script that pops on agent desktop when call connects Caller ID The number displayed to the contact being called Skills-Based Routing Optional — match agents based on ACD skills during campaign DNC & Compliance Field Description DNC Lists One or more lists — all are checked before every dial attempt Callable Time Set Enforces calling hours by time zone Attempt Controls Limits re-dial attempts per contact or phone number Compliance Abandon Rate Monitor and alert on FTC/OFCOM abandon thresholds Call Analysis Response Table Defines system behavior based on call detection result: Detection Example Action Live Person Connect to queue → Agent Answering Machine Disconnect, play message, or leave voicemail Busy Schedule retry via attempt control No Answer Schedule retry via attempt control Invalid Number Mark as uncallable Outbound Lines Distribution Controls how campaign lines are shared when multiple campaigns run on the same Edge group or Site: Option Description Weight Proportional share — default weight is 10 per campaign Reserved Lines Campaign reserves a fixed number of lines (used for Agentless) Equal Distribution All campaigns share lines equally 💡 Line weight is relative: Campaign A (weight 50) + Campaign B (weight 25) = Campaign A gets 67% of available lines, Campaign B gets 33%. Campaign Scheduling Each campaign can have one schedule with up to 500 intervals: Navigate to campaign → Schedule tab Define Start Time and Stop Time per interval Assign a Callable Time Set for time zone compliance Save Campaigns can also be organized into Campaign Sequences — chained campaigns that run one after another, started and stopped as a group. Wrap-Up Code Mappings Wrap-up codes used by agents can be mapped to campaign actions — defining what happens to the contact after the call ends: Wrap-Up Code Campaign Action Resolved Stop all future contact attempts Callback Requested Schedule a callback Wrong Number Mark phone number as uncallable Do Not Call Add to DNC list Follow Up Schedule retry with custom recall time Wrap-up code mappings are configured at Admin → Outbound → Wrap-Up Code Mappings . Rule Sets Rule sets define logic-based conditions that trigger actions before or after a call: Rule Type Timing Example Pre-call Rule Before dialing Skip contact if account balance < $0 via Data Action lookup Wrap-Up Rule After call ends Schedule callback if wrap-up = "Call Back Later" Limit Detail Max data action conditions per rule set 2 Max data actions per rule set 10 API call rate from rules 5 per second (pre-call and wrap-up) Digital Campaigns In addition to voice, Genesys Cloud supports outbound digital campaigns: Channel Use Case Notes Email Marketing, notifications, billing Requires verified email domain SMS Alerts, reminders, surveys 160 characters per segment; requires SMS inventory number WhatsApp High-volume notifications Pre-approved Message Templates required; up to 18,000 msg/min Digital campaigns use the same Campaign Editor but with channel-specific settings instead of call analysis. Campaign Monitoring (Real-Time) View Location Outbound Campaigns Dashboard Performance → Outbound Campaigns Campaign Details View Select a campaign — shows stats, interactions, callbacks Diagnostics Window March 2026 feature — real-time diagnostics for voice campaign health (queues, agents, contact rates) Refresh Rate Interaction data refreshes every 10 seconds Historical Interactions View interactions for current day, last 7 days, or last 30 days Interview Cheat Sheet Question Answer Where are campaigns created? Admin → Outbound → Campaign Management What is the first decision in the Campaign Editor? Dialing Mode What does Campaign Priority control? Proportional line distribution when multiple campaigns share the same queue What is a Callable Time Set? Defines allowed dialing hours by time zone — enforces compliance What does a Call Analysis Response Table define? System actions based on call detection result (live person, machine, busy, no answer) What is the default outbound line weight per campaign? 10 How does wrap-up code mapping work? Maps agent wrap-up codes to campaign outcomes (stop calling, add to DNC, schedule callback, etc.) Can multiple DNC lists be assigned to one campaign? Yes How often does campaign interaction data refresh? Every 10 seconds What is new in March 2026 for campaign monitoring? A dedicated diagnostics window with real-time campaign health data Callbacks Section Description Feature Area Contact Center / Queue Configuration Navigation (Scheduled Callbacks view) Performance → Workspace → Contact Center → Scheduled Callbacks Navigation (Queue callback settings) Admin → Contact Center → Queues → [select queue] → Callback tab Navigation (Architect Create Callback) Available in Inbound Call, In-Queue, and Outbound Call flows via the Toolbox Primary Function Allow customers to request a return call instead of waiting on hold; reduce abandonment and improve satisfaction A callback is a request a caller makes to have their call returned when an agent is unavailable. Callbacks improve customer satisfaction by eliminating hold time. They also help agents who cannot complete an interaction immediately and need to follow up. Genesys Cloud supports several callback types that originate from different points in the contact center workflow. Study Notes — Callback Types Callback Type Origin Description In-Queue Callback Architect flow (in-queue or inbound) Customer requests a callback while waiting in queue — exits the queue and the callback object takes their position Scheduled Callback Agent-initiated during an interaction Agent schedules a return call for a future date/time — up to 30 days in advance Agent-Owned Callback Scheduled callback with ownership Agent takes personal ownership — callback waits for that specific agent to become available Customer First Callback Queue-level configuration System dials the customer first, connects them to an agent only after the customer answers Campaign Callback Outbound campaign Schedule Callback action Automatically created by outbound dialing campaign rules In-Queue Callback (via Architect) The Create Callback action is added to an Inbound Call, In-Queue, or Outbound Call flow. Attribute Detail Architect Action Create Callback (in Flow category of Toolbox) Supported In Inbound Call flows · In-Queue Call flows · Outbound Call flows What happens Callback object is placed on the specified queue; original call exits the queue Queue position Callback object takes the position in queue of the original call — same skill requirements and priority are automatically inherited ANI (Caller ID) Callback uses the queue's ANI , not the agent's ANI Caller ID customization Cannot set caller ID with Create Callback action — use a Call Data action first if you need to set caller ID or caller name Script requirement Script used by the callback must have the Callback property enabled in script settings (disabled by default) Skills/priority retention Not retained when placing a callback — skills and priority are reacquired from queue position, not the original interaction In-queue flow limit Max 30 in-queue flows per email or message interaction (prevents loop when target queue = current queue) Scheduled Callback (Agent-Initiated) Agents can schedule a return call during an active voice interaction. Attribute Detail Maximum advance scheduling 30 days Default routing Routes to the queue that received the original interaction Agent can override Agent can specify a different queue or select "Route callback to me if possible" Ownership If admin enables agent-owned callbacks, agent can select Take Ownership If agent misses the callback Immediately routes to the next available agent in queue If no agent is available Callback remains in queue until an agent becomes available Edit restriction Cannot edit an owned callback within 15 minutes of scheduled time Agent-Owned Callbacks Attribute Detail Definition A callback where a specific agent takes personal ownership — waits for that agent to become available Prerequisite Admin must enable agent-owned callbacks on the queue; at least one Preferred Agent Routing rule must be set Ownership duration Admin configures the wait period — 1 hour to 30 days On expiration (if Assign to Queue enabled) Callback returns to the queue for the next available agent On expiration (if Assign to Queue NOT enabled) Callback is removed from queue and disconnected Effect of preferred agent routing Preferred agent routing does NOT affect scheduled callbacks — scheduled callbacks are unaffected Customer First Callback (Queue Configuration) Attribute Detail Default behavior Agent First — system waits for agent to answer before dialing the customer Customer First behavior System dials the customer before connecting to an agent; once customer answers, interaction returns to queue Configure where Queue settings → Callback tab → select Customer First Pacing Modifier Values 1–10 — controls the rate at which Customer First callbacks are dialed based on online agent count Retry attempts Configurable — max 0–20 retries for unsuccessful callbacks; retry interval up to 24 hours Voicemail recommendation Genesys recommends not using voicemails in Customer First callback queues — voicemails also dial the customer first and the agent cannot listen before the customer connects Script used Customer First callbacks use the voice script for callbacks (callback-specific agent scripts are not supported) Analytics Agents do not receive Customer First callback-specific metrics (handle time, talk time, time to first dial/connect) — only voice metrics after connection Outbound routes As of July 2025, administrators can specify a telephony site or edge group per queue for Customer First callback outbound dialing Callbacks & Preferred Agent Routing Interaction Type Preferred Agent Routing Behavior Email and messaging interactions Preferred agent routing overrides — Genesys no longer routes to last agent Inbound callbacks Preferred agent routing overrides — Genesys no longer routes to last agent Scheduled callbacks Unaffected by preferred agent routing Scheduled Callbacks View (Performance Dashboard) Attribute Detail Navigation Performance → Workspace → Contact Center → Scheduled Callbacks Permissions required Analytics > Conversation Detail > View · Routing > Queue > View · Outbound > Campaign > View What it shows All callbacks scheduled by agents during interactions, and callbacks created by the Schedule Callback action Agent-owned callbacks Show the agent owner's name in the Agent Owner column Non-owned callbacks Agent Owner column is blank Actions available Cancel (single or bulk) · Reschedule · Reassign to another queue/agent (agent-owned only) Export limit Up to 10,000 conversations per 12-hour period for recent interactions; up to 1,000,000 for older data View does NOT auto-refresh Must manually refresh to see current data Key Limits & Rules (Exam Critical) Rule Value Maximum advance scheduling 30 days Agent-owned callback duration range 1 hour to 30 days Pacing modifier range (Customer First) 1–10 Max callback retry attempts 0–20 Retry interval maximum 24 hours Cannot edit owned callback before scheduled time 15 minutes Inactive callback auto-end If no date specified and no updates within 14 days of creation, analytics ends the conversation (callback may still be active) In-queue flow limit 30 per email/message interaction Callback uses queue ANI Not agent ANI Skills/priority retained from original call No Architect Create Callback Action — Configuration Fields Field Description Name Label for the action in the flow Callee Name Optional — name to identify the callback recipient Callback Number Required — string expression for the callback number (auto-captured from ANI data) Queue Queue where the callback request is placed Script Optional — a script with the Callback property enabled Note: ANI data from the call is automatically examined at runtime to capture the caller's telephone number. You cannot specify caller ID or name directly from this action — use a Call Data action first. Callback Routing Logic (Inbound) Caller enters Inbound Call Flow ↓ Wait time exceeds threshold (or caller selects option) ↓ Create Callback action executes ↓ Callback object placed in queue at caller's original position (inherits skill requirements and priority) ↓ Original call disconnects ↓ Agent becomes available → Callback object routed to agent ↓ Agent manually dials customer (Agent First) OR System dials customer first (Customer First) ↓ Outbound call placed → linked to queue for analytics Callback Automation (Queue Settings) Queues can be configured to automate callback handling, removing manual agent steps: Automation Option Description Auto-Answer Callback interaction is automatically answered when routed to agent Auto-Dial Agent's outbound call is automatically placed when callback is answered Auto-End Callback Callback segment is automatically ended after the call completes These settings are found under Admin → Contact Center → Queues → [queue] → Callback tab. Skill/Priority Preservation (January 2025 Update) As of January 2025, administrators can optionally preserve skills and priorities from the original call for callbacks and ACD voicemails. This applies to: In-queue callbacks Scheduled callbacks Skilled campaign callbacks ACD voicemails This is an opt-in setting and was not the default behavior prior to this update. Best Practices Practice Reason Do not enable agent-owned callbacks without Preferred Agent Routing rules on the queue Ownership requires at least one PAR rule to function Always handle the case where a callback cannot be placed Add alternate routing in the flow's failure path Avoid internal ACD voicemails Creates a callback segment where Agent A's utilization is consumed until the callback is resolved Do not use voicemails in Customer First queues Agent cannot listen to voicemail before customer connects Set a realistic ownership period If too long, callbacks may wait excessively for unavailable agents Enable "Assign to Queue on ownership expiration" Ensures expired owned callbacks don't just disconnect Key Takeaways Topic Summary In-queue callback Uses Create Callback action in Architect; callback takes original call's queue position Scheduled callback Agent-initiated; max 30 days advance; routes to original queue by default Agent-owned callback Waits for specific agent; requires PAR rule; 1hr–30day ownership period Customer First System dials customer before connecting to agent; Pacing Modifier 1–10 Skills not retained Callbacks do not inherit skills/priority (unless optional preservation is enabled) ANI Callbacks use queue ANI, not agent ANI Inactive auto-end 14-day limit for unscheduled callbacks with no updates Scheduled Callbacks view Performance → Workspace → Contact Center → Scheduled Callbacks Predictive Routing Study Notes Topic Description Predictive Routing AI-powered routing system that optimizes agent assignment Engine Machine learning algorithms analyze skills, availability, and contact history Purpose Maximize first-contact resolution and customer satisfaction Activation Requires Premium edition and Workforce Optimization module Benefit Reduces handle time and improves customer outcomes Navigation Admin → Architect → Routing → Predictive Routing OR Admin → Contact Center → Routing Configuration → Enable Predictive Routing Predictive Routing Overview Predictive Routing is an AI-powered contact routing system that dynamically matches incoming contacts to the most suitable available agent based on multiple factors: Key Capabilities Skill-based routing - Matches agent skills to contact requirements Historical performance - Learns from agent interaction outcomes Availability prediction - Anticipates agent availability and readiness Real-time optimization - Adjusts routing in real-time based on system state Omnichannel support - Works across voice, chat, email, and messaging How It Works Contact arrives at system Contact intent and requirements analyzed System evaluates all available agents Machine learning algorithm predicts best match Contact routed to optimal agent Interaction data captured for learning Edition & Module Requirements Requirement Details Minimum Edition Premium Edition required Module Workforce Optimization add-on module License Type Agent licenses with predictive routing enabled Setup Admin configuration in Architect Study Notes - Routing Factors Factor Description Impact Agent Skills Capabilities and certifications High - Core matching criteria Proficiency Level Skill mastery degree High - Affects quality Availability Agent ready state and status High - Real-time factor Handling Capacity Available slots for new contacts High - Prevents overload Historical Performance Past interaction outcomes Medium - Learning factor Queue Wait Time Customer wait duration Medium - Fairness factor Contact Type Voice, chat, email, etc. High - Channel match Language Proficiency Supported languages High - Communication match Customer History Previous interaction records Medium - Context factor Agent State Idle, working, after-call work High - Real-time factor Implementation Guide Step 1: Prerequisites & Planning Ensure organization has Premium edition Purchase Workforce Optimization module Audit existing agent skills database Document required skill sets Review current routing rules Plan migration from legacy routing Step 2: Configure Skill Definitions Navigate to Admin → Architect → Skills Create skill categories (technical, language, product) Define skill levels (1-5 proficiency) Assign skills to agents Establish mastery thresholds Document skill requirements per queue Step 3: Enable Predictive Routing Go to Admin → Contact Center → Routing Select queue to enable predictive routing Enable "Predictive Routing" toggle Configure routing rules (optional overrides) Set skill matching parameters Define fallback routing behavior Step 4: Testing & Validation Route test calls through system Monitor agent assignment accuracy Verify skill matching Check queue distribution Validate omnichannel routing Review abandonment rates Step 5: Monitoring & Optimization Review routing analytics daily Monitor first-contact resolution rates Track agent utilization Measure customer satisfaction Optimize skill assignments Adjust thresholds as needed How to Implement Phase Description Timeline Analysis Audit current routing and skills Week 1-2 Configuration Set up skills, queues, and rules Week 2-3 Testing Validate routing logic and assignments Week 3-4 Pilot Deploy to test queue with monitoring Week 4-6 Full Rollout Enable across all queues Week 6-8 Optimization Monitor, tune, and improve Ongoing Predictive Routing Architecture Incoming Contact ↓ Contact Metadata Analysis ├── Contact Intent ├── Contact Type (Voice/Chat/Email) ├── Language Requirements └── Skill Requirements ↓ Predictive Routing Engine ├── Machine Learning Models ├── Real-time Agent Analysis ├── Skill Matching Algorithm └── Performance Prediction ↓ Agent Evaluation ├── Available Agents ├── Skill Match Score ├── Proficiency Level ├── Historical Performance └── Queue Load Balance ↓ Optimal Agent Selection ↓ Route Contact ↓ Agent Assignment Routing Decision Flow Contact Arrives ↓ Extract Contact Data ├── Intent ├── Channel Type ├── Language └── Queue Assignment ↓ Predictive Routing Engine Evaluates ├── Agent Availability Status ├── Skill Compatibility ├── Proficiency Levels ├── Current Workload └── Historical Performance Score ↓ Machine Learning Model Predicts ├── Best Agent Match ├── Estimated Resolution Probability └── Customer Satisfaction Likelihood ↓ Route to Optimal Agent ↓ If No Optimal Agent Available ├── Queue with Priority Calculation ├── Monitor for Next Available Match └── Apply Fallback Routing Rules ↓ Agent Accepts Contact Routing Rules & Overrides Hard Rules (Always Applied) Rule Priority: High ├── Agent Availability ├── Required Skills Present ├── Language Match └── Queue Assignment Rule Priority: Medium ├── Skill Proficiency Threshold ├── Agent Capacity ├── Contact Type Capability └── Channel Configuration Rule Priority: Low ├── Load Balancing ├── Historical Performance └── Fairness Rotation Skill Configuration Example Technical Support Queue Required Skills: ├── Product Knowledge (Level 3+) │ ├── Software (Level 4) │ ├── Hardware (Level 3) │ └── Cloud Services (Level 3) ├── Troubleshooting (Level 3+) ├── Customer Service (Level 2+) └── English Fluency (Level 3+) Optional Skills: ├── Advanced Certifications (bonus) ├── Spanish Fluency (secondary channel) └── VIP Customer Experience (specialized) Bilingual Sales Queue Required Skills: ├── Sales Techniques (Level 3+) ├── Product Knowledge (Level 3+) ├── English Fluency (Level 4+) ├── Spanish Fluency (Level 4+) └── Customer Service (Level 3+) Optional Skills: ├── Enterprise Sales (bonus) ├── Account Management (bonus) └── Negotiation (specialized) Real Flow Scenario: Predictive Routing in Action Customer Calls Support Line ↓ System Analyzes: "Technical issue with mobile app" ↓ Route Requirements: ├── Skill: Mobile Development (Level 3+) ├── Skill: Customer Service (Level 2+) ├── Language: English ├── Channel: Voice └── Queue: Technical Support ↓ Predictive Engine Evaluates All Available Agents: Agent 1 (Sarah) ├── Mobile Development: Level 4 ✓ ├── Customer Service: Level 4 ✓ ├── Current Load: 1 contact ├── Avg Handle Time: 8 mins ├── FCR Rate: 85% ✓ (BEST MATCH) Agent 2 (James) ├── Mobile Development: Level 2 (Below threshold) ├── Current Load: 2 contacts ├── FCR Rate: 72% Agent 3 (Maria) ├── Mobile Development: Level 3 ✓ ├── Customer Service: Level 3 ✓ ├── Current Load: 3 contacts ├── FCR Rate: 78% ↓ Route to Agent Sarah (Highest Probability of Resolution) ↓ Sarah Answers Call ↓ System Logs Interaction for Future Learning Omnichannel Predictive Routing Voice Channels Inbound Calls ↓ Predictive Routing ↓ Skill-based Queue ↓ Agent Answer Digital Channels Chat/Email/Social Arrival ↓ Predictive Routing Engine ↓ Agent Availability Check (across channels) ↓ Route to Agent with Capacity ↓ Agent Manages Omnichannel Load Contact Blending Example Agent Can Handle: ├── 1 Voice Call ├── 2 Chat Conversations ├── 1 Email Thread └── 1 Social Media Message Total Capacity: 5 Concurrent Contacts Current Load: 3 Contacts Available Slots: 2 Real Flow Scenario: Omnichannel Assignment Multiple Contacts in Queue: ├── Inbound Call (Technical) ├── Chat (Billing Question) └── Email (Complaint) Predictive Engine Evaluates: ↓ Agent 1 Capacity: 2 slots available ├── Skills: Technical, Billing, Customer Service ✓ ├── Current: 1 Call + 1 Chat ├── Assignment: Route Email (write capability available) ↓ Agent 2 Capacity: 1 slot available ├── Skills: Technical, Billing ✓ ├── Current: 1 Chat ├── Assignment: Route Call (available) ↓ Queue Assignment Complete Usage Scenarios Scenario Solution Outcome High call volume with variable skill requirements Enable predictive routing with skill-based queues Reduced wait times, improved FCR Multiple agent skill levels Set proficiency thresholds in routing rules Appropriate complexity matching Omnichannel contact center Use predictive routing across all channels Optimized agent utilization International operations Configure language skills and regional routing Better customer satisfaction Seasonal staffing fluctuations Adjust skill assignments dynamically Maintained service quality VIP customer handling Create specialized skill for VIP interactions Enhanced customer experience Predictive Routing Configuration Settings Queue-Level Settings Queue Configuration: Technical Support Routing Mode: Predictive Routing ✓ Skill Matching: ├── Required Skills: Product Knowledge, Troubleshooting ├── Proficiency Threshold: Level 3+ ├── Language Match: Required └── Strict Matching: Enabled Fallback Behavior: ├── If no perfect match: Lower proficiency threshold ├── Escalation path: Senior support queue └── Timeout: 30 seconds to find match Load Balancing: ├── Max contacts per agent: 3 ├── Considering ACW time: Yes └── Fair distribution: Enabled Monitoring & Analytics Dashboard Key Metrics to Track Metric Target Purpose First Contact Resolution (FCR) >80% Measure routing effectiveness Average Handle Time (AHT) Baseline - 5% Track efficiency Agent Utilization 80-90% Optimize resource use Customer Satisfaction (CSAT) >85% Measure outcomes Skill Match Rate >95% Verify routing accuracy Queue Abandonment <5% Monitor wait times Call Transfer Rate <10% Reduce routing errors Real-Time Dashboard View Predictive Routing Performance (Live) Queue: Technical Support ├── Active Contacts: 24 ├── Available Agents: 8 ├── Avg Match Score: 4.2/5 ✓ ├── Current AHT: 9.2 mins └── Skill Match %: 96.4% Top Performing Skills Today: ├── Mobile Development (8 contacts, 87% FCR) ├── Cloud Services (6 contacts, 82% FCR) └── Hardware Support (4 contacts, 85% FCR) Agent Performance: ├── Sarah: 4 contacts, 8.1 avg mins, 88% FCR ├── James: 3 contacts, 9.5 avg mins, 79% FCR └── Maria: 2 contacts, 8.8 avg mins, 84% FCR Best Practices Skill Management Keep skills current - Update agent skills quarterly or after training Avoid over-specialization - Limit skill count to 8-10 per agent Balance proficiency - Mix Level 3-4 and Level 2 agents in queues Document requirements - Clearly define skill needs per queue Regular training - Invest in skill development to improve proficiency Routing Optimization Start with hard rules - Use required skills and language matching first Monitor thresholds - Adjust proficiency requirements based on performance Test changes - Implement rule changes gradually Leverage analytics - Use data to identify routing improvements Continuous tuning - Predictive routing improves over time with more data Agent Management Clear skill assignments - Agents must know their assigned skills Growth paths - Provide training to increase proficiency levels Regular feedback - Share routing and performance data Incentivize learning - Reward skill development Load balance fairly - Ensure equitable work distribution Monitoring & Reporting Daily reviews - Check key metrics and anomalies Weekly analysis - Identify trends and improvement opportunities Monthly optimization - Adjust skills and rules as needed Quarterly planning - Forecast and plan for seasonal changes Annual strategy - Evaluate overall routing effectiveness Common Configuration Scenarios Scenario 1: Small Team (15 agents, 3 skill levels) Configuration: ├── Premium Edition ✓ ├── Workforce Optimization Module ✓ ├── Single Queue (Support) ├── 3 Skill Categories (Level 1-4 scaling) └── Basic Routing Rules Expected Results: ├── 20-30% improvement in FCR ├── 10-15% reduction in AHT └── Higher agent satisfaction Scenario 2: Large Enterprise (200+ agents, multiple queues) Configuration: ├── Premium Edition ✓ ├── Workforce Optimization Module ✓ ├── 5-8 Queues (Technical, Billing, Sales, etc.) ├── 15+ Skill Categories with proficiency levels ├── Advanced Routing Rules and Overrides └── Omnichannel Blending Expected Results: ├── 25-40% improvement in FCR ├── 15-25% reduction in AHT ├── Significant CSAT increase └── Better resource utilization Scenario 3: Multilingual Contact Center (5 languages) Configuration: ├── Language Skills for each agent ├── Language Matching in Routing Rules ├── Regional Queue Assignment ├── Skill + Language Combination Routing └── Overflow to general queue if no match Expected Results: ├── Improved customer satisfaction ├── Reduced transfers ├── Better first contact resolution └── International service quality Troubleshooting Guide Issue Cause Resolution Contacts routing to wrong skill level Proficiency threshold too low Increase threshold in routing rules Long wait times Predictive routing disabled for queue Enable predictive routing in queue config High transfer rates Skill mismatch in routing Review and update skill definitions Uneven agent load Skill imbalance among agents Provide training to level skill distribution Poor FCR rates Insufficient skill matching Add more skill categories to definitions Agents overloaded Capacity settings too high Reduce max contacts per agent Low agent utilization Skill requirements too strict Relax proficiency thresholds slightly Routing delays Too many hard rules Simplify rules and priorities Language mismatch Language skills not configured Add language proficiency to agent setup Module not working Feature not enabled Verify Premium edition and module purchase Real-World Implementation Timeline Week 1-2: Assessment & Planning Day 1-2: Kick-off meeting Day 3-5: Audit current routing and skills Day 6-10: Design new skill structure Day 11-14: Plan change management Week 3-4: Configuration Day 15-18: Create skill definitions Day 19-22: Configure queues and rules Day 23-25: Set up monitoring dashboard Day 26-28: Document configuration Week 5-6: Testing & Pilot Day 29-32: Conduct routing tests Day 33-36: Deploy to pilot queue Day 37-40: Monitor pilot performance Day 41-42: Gather feedback and optimize Week 7-8: Full Deployment Day 43-44: Plan rollout schedule Day 45-52: Deploy to remaining queues Day 53-56: Monitor and support agents Naming Convention Queue Naming with Routing Type ___Queue Examples: Support_Technical_PredictiveRouting_Queue Sales_Enterprise_PredictiveRouting_Queue Billing_Collections_PredictiveRouting_Queue Skill Naming Convention __ Examples: Product_MobileApp_Skill Language_Spanish_Fluency Service_VIP_Handling Technical_CloudServices_Certification Integration with Other Systems Workforce Management (WFM) Predictive Routing ←→ WFM ├── Share agent availability ├── Schedule compliance ├── Forecasting data └── Staffing adjustments Quality Management Predictive Routing ←→ Quality Management ├── Interaction recordings ├── Performance metrics ├── Coaching opportunities └── Training recommendations Customer Data Platform Predictive Routing ←→ Customer Data ├── Customer history ├── Preferences ├── Previous resolutions └── VIP status Performance Benchmarks Industry Standard Improvements Metric Typical Improvement First Contact Resolution +15-40% Average Handle Time -10-25% Customer Satisfaction +10-25% Agent Utilization +5-15% Queue Abandonment -20-50% Cost Per Contact -10-20% Ramp-Up Timeline Day 1-30: Learning phase, marginal improvement Month 2-3: System learns patterns, 10-15% improvement Month 4-6: Optimized configuration, 25-35% improvement Month 6+: Mature state, 30-40% improvement Predictive Routing vs. Traditional Routing Feature Predictive Routing Traditional Routing Skill Matching AI-optimized Rules-based Agent Selection Predictive Sequential Learning Continuous None Complexity High Low Setup Time Medium Low Optimization Automatic Manual FCR Improvement 25-40% Baseline Cost Higher Lower Interview Cheat Sheet Question Answer What is Predictive Routing? AI-powered routing system that optimizes agent assignment using ML What are the requirements? Premium edition + Workforce Optimization module How does it select agents? Analyzes skills, availability, performance, and predicts best match What factors does it consider? Skills, proficiency, availability, workload, language, history Can you use it with omnichannel? Yes, works with voice, chat, email, and messaging How is it different from skill-based routing? Uses ML to predict best match vs. just checking skills Where do you configure it? Admin → Contact Center → Routing What's the expected improvement? FCR +25-40%, AHT -10-25%, CSAT +10-25% How long does setup take? 4-8 weeks depending on complexity What are critical success factors? Accurate skills data, proper proficiency levels, continuous monitoring How do you monitor performance? Daily dashboard review, weekly analytics, monthly optimization What if no perfect agent match exists? System queues contact with fallback routing rules Can you override predictive routing? Yes, hard rules take precedence (availability, required skills) How does machine learning help? Learns from past outcomes to improve future routing What's the ROI timeline? 2-3 months to see significant improvements Key Takeaways AI-Powered Optimization - Predictive routing uses machine learning to match contacts to best-fit agents Skill-Based Foundation - Requires well-defined skills and proficiency levels Omnichannel Capable - Works across voice, chat, email, and messaging channels Continuous Learning - System improves routing decisions over time Premium Feature - Requires Premium edition and Workforce Optimization module Significant ROI - Typical improvements: FCR +25-40%, AHT -10-25% Real-Time Optimization - Routes contacts dynamically based on current system state Fallback Rules Matter - Hard rules ensure quality even without perfect matches Change Management Critical - Proper implementation and monitoring are essential Ongoing Monitoring Required - Daily reviews and monthly tuning maximize benefits Migration Path from Traditional Routing Phase 1: Preparation (Weeks 1-2) ├── Audit current routing rules ├── Document all skills currently used ├── Identify skill gaps └── Plan queue restructuring Phase 2: Setup (Weeks 3-4) ├── Create comprehensive skill definitions ├── Assign skills and proficiency to agents ├── Configure predictive routing queues └── Establish monitoring dashboards Phase 3: Pilot (Weeks 5-6) ├── Enable on low-risk queue ├── Monitor closely for issues ├── Gather team feedback └── Optimize configuration Phase 4: Rollout (Weeks 7-8) ├── Disable traditional routing rules ├── Enable predictive on remaining queues ├── Support agents through transition └── Celebrate early wins Additional Resources Official Documentation Links Genesys Cloud Routing Guide: https://help.genesys.com/genesyscloud/current/en-us/Routing.html Predictive Routing Setup: https://help.genesys.com/genesyscloud/current/en-us/PredictiveRouting.html Workforce Optimization: https://help.genesys.com/genesyscloud/current/en-us/WFO.html Support Contacts Genesys Sales: sales@genesys.com Genesys Support: https://support.genesys.com Community Forums: https://community.genesys.com Document Version Info Last Updated: March 2026 Source: Genesys PureCloud Official Documentation Version: 1.0 Agent Copilot (Agent Assist) Study Notes Topic Description Agent Copilot AI-powered real-time guidance system for agents Also Known As Agent Assist, Copilot Assistant Purpose Provides real-time recommendations and knowledge during customer interactions Activation Requires Premium edition and Customer Insights module Benefit Reduces handle time, improves first-contact resolution, enhances agent confidence Navigation Admin → Architect → Agent Copilot OR Admin → Contact Center → Agent Assistance → Copilot Configuration Agent Copilot Overview Agent Copilot is an AI-powered assistant that provides real-time guidance and recommendations to agents during customer interactions. It analyzes the conversation in real-time and suggests relevant knowledge articles, scripts, and next steps to improve interaction quality and resolution. Key Capabilities Real-time recommendations - Suggests actions based on conversation context Knowledge article suggestions - Recommends relevant articles automatically Script guidance - Provides talking points and recommended language Sentiment analysis - Monitors customer emotion and suggests de-escalation Next action recommendations - Predicts optimal next steps Agent learning - Improves over time with agent feedback How It Works Agent answers contact Copilot monitors conversation in real-time AI analyzes conversation intent and context System searches knowledge base for relevant information Recommendations displayed in agent interface Agent reviews and applies suggestions Feedback loop improves future recommendations Edition & Module Requirements Requirement Details Minimum Edition Premium Edition required Module Customer Insights add-on module License Type Agent licenses with Copilot enabled Setup Admin configuration in Architect Integration Knowledge management system required Study Notes - Copilot Features Feature Description Use Case Knowledge Recommendations AI-suggested articles from knowledge base Technical support, FAQs Script Guidance Real-time conversation scripts and talking points Sales, compliance-heavy calls Sentiment Monitoring Real-time emotion analysis of customer De-escalation, empathy guidance Next Action Suggestions Recommended next steps for agent Call routing, transfer decisions Agent Performance Tips Real-time coaching during interaction Training reinforcement Historical Context Customer interaction history suggestions Personalization, context Product Recommendations Sales-specific recommendations Upsell, cross-sell opportunities Compliance Reminders Real-time compliance guidance Regulatory requirements Implementation Guide Step 1: Prerequisites & Planning Ensure organization has Premium edition Purchase Customer Insights module Audit existing knowledge base Document Copilot use cases by queue Plan knowledge article optimization Review agent readiness and training needs Step 2: Knowledge Base Configuration Navigate to Admin → Knowledge Management Create/organize knowledge articles Tag articles with metadata (category, queue, intent) Add keywords and synonyms for better matching Ensure article quality and accuracy Set article access permissions Step 3: Enable Agent Copilot Go to Admin → Architect → Agent Copilot Enable "Agent Copilot" toggle Select knowledge base source Configure recommendation parameters Set recommendation types to display Choose recommendation frequency Step 4: Customize by Queue Create queue-specific Copilot settings Configure knowledge sources per queue Set relevance thresholds Define script templates Establish sentiment trigger rules Test queue-specific configurations Step 5: Agent Training & Rollout Train agents on Copilot interface Explain recommendation types Practice with sample interactions Gather initial feedback Monitor early adoption Provide ongoing support Step 6: Monitoring & Optimization Review Copilot engagement metrics Monitor agent utilization of recommendations Track recommendation accuracy Gather agent feedback Optimize knowledge articles Adjust recommendation parameters How to Implement Phase Description Timeline Planning Audit knowledge base and define use cases Week 1-2 Setup Configure Copilot and knowledge sources Week 2-3 Content Create/optimize knowledge articles Week 3-5 Training Educate agents on features and usage Week 5-6 Pilot Deploy to single queue with monitoring Week 6-7 Rollout Enable across all queues Week 7-8 Optimization Monitor and tune performance Ongoing Agent Copilot Architecture Incoming Contact ↓ Agent Accepts Contact ↓ Copilot Monitoring Begins ├── Real-time Conversation Analysis ├── Intent Detection └── Context Extraction ↓ AI-Powered Recommendation Engine ├── Knowledge Base Search ├── Relevance Scoring ├── Sentiment Analysis └── Prediction Models ↓ Recommendation Generation ├── Knowledge Articles ├── Scripts & Talking Points ├── Next Action Suggestions ├── Sentiment De-escalation Tips └── Product/Service Recommendations ↓ Display to Agent Interface ↓ Agent Reviews Recommendations ↓ Agent Applies (or Dismisses) Suggestions ↓ Feedback Loop Updates AI Model Real-Time Recommendation Flow Customer Says: "I've been trying to reset my password for hours" Copilot Analyzes: ├── Intent: Password Reset Help ├── Sentiment: Frustrated/Angry ├── Context: Technical Issue └── Duration: Extended problem ↓ Copilot Recommendations Display: 1. KNOWLEDGE ARTICLE (High Confidence) ├── "Password Reset Troubleshooting" ├── Relevance: 94% └── Steps: 5-7 minute resolution 2. SENTIMENT GUIDANCE (Urgent) ├── Suggest: Apologize for inconvenience ├── Tone: Empathetic └── De-escalation: Acknowledge frustration 3. NEXT ACTION (Suggested) ├── Offer: Manual password reset ├── Escalation: If still unresolved └── Followup: Offer premium support 4. SCRIPT SUGGESTION (Optional) ├── "I completely understand how frustrating that is..." ├── "Let me walk you through the fastest solution..." └── "If this doesn't work, I'll reset it for you personally" ↓ Agent Applies Recommendations ↓ Customer Issue Resolved ↓ System Captures Feedback Copilot Interface Components Agent Desktop View: ┌─────────────────────────────────────────┐ │ Current Interaction │ │ Customer: John Smith │ │ Queue: Technical Support │ │ Duration: 3:45 │ ├─────────────────────────────────────────┤ │ COPILOT RECOMMENDATIONS │ ├─────────────────────────────────────────┤ │ │ │ 📚 KNOWLEDGE ARTICLES │ │ ├─ Password Reset Guide (94% match) │ │ ├─ Two-Factor Auth Setup (87% match) │ │ └─ Account Recovery (76% match) │ │ │ │ 😟 SENTIMENT ALERT │ │ ├─ Customer: FRUSTRATED │ │ └─ Suggestion: De-escalate & empathize│ │ │ │ ➡️ NEXT ACTIONS │ │ ├─ Offer manual password reset │ │ ├─ Provide security questions │ │ └─ Escalate if unsuccessful │ │ │ │ 💬 SUGGESTED SCRIPT │ │ "I understand how frustrating this is. │ │ Let me walk you through the quickest │ │ way to get this resolved..." │ │ │ │ [👍 Helpful] [👎 Not Helpful] │ └─────────────────────────────────────────┘ Real Flow Scenario: Sales Queue with Copilot Agent: "Hi, thanks for calling. How can I help?" Customer: "I'm interested in upgrading my plan" Copilot Recommendations Appear: 1. KNOWLEDGE - Sales Playbook ├─ Current Plan Analysis ├─ Available Upgrades └─ Pricing Information 2. PRODUCT RECOMMENDATIONS ├─ Upsell: Premium Plan (+40% revenue potential) ├─ Cross-sell: Support Package └─ Offer: 2-month discount if upgrading today 3. NEXT ACTION SUGGESTIONS ├─ Qualify: Ask about usage patterns ├─ Present: Show cost-benefit analysis └─ Close: Offer contract details 4. SCRIPT SUGGESTION "Based on your usage, the Premium Plan would save you money and give you these benefits: [list]. Can I set that up?" ↓ Agent Applies Script & Recommendations ↓ Customer Upgrades (upsell successful) ↓ System Logs: Agent applied recommendation ↓ Next Sale: System learns and improves recommendations Real Flow Scenario: Support Queue with Sentiment Customer Calls (Angry Tone) Agent Answers Copilot Immediately Detects: ├─ Sentiment: NEGATIVE (85% confidence) ├─ Emotion: Frustrated/Angry ├─ Risk: Potential churn └─ Recommended Action: De-escalate NOW ↓ Sentiment Alert in Copilot: "Customer is frustrated. Suggested response: 'I'm sorry you're experiencing this issue. I'm going to personally make sure we get this resolved for you right now.'" ↓ Copilot Provides Knowledge: ├─ Issue Resolution Articles ├─ Escalation Path (if needed) └─ Retention Options ↓ Agent Applies De-escalation Approach ↓ Customer Sentiment Improves ↓ System Logs Improvement ↓ Issue Resolved Successfully Omnichannel Copilot Support Voice Interactions Real-time Copilot assistance during calls ├── Conversation transcription ├── Intent analysis ├── Real-time knowledge suggestions └── Sentiment monitoring Chat Interactions Suggested responses during chat ├── Pre-written messages ├── Quick knowledge links ├── Canned responses with personalization └── Sentiment-based guidance Email Interactions Copilot assistance with draft responses ├── Knowledge recommendations ├── Tone suggestions ├── Template recommendations └── Compliance checking Social Media Interactions Real-time assistance for public responses ├── Tone and brand consistency ├── Knowledge suggestions ├── De-escalation for negative sentiment └── Escalation recommendations Usage Scenarios Scenario Solution Outcome High call volume with complex issues Copilot suggests knowledge articles Reduced AHT, faster resolution New agents lacking experience Real-time script and guidance Improved FCR, faster ramp-up Compliance-heavy calls Compliance reminders and scripts Reduced risk, better compliance Frustrated customers Sentiment analysis with de-escalation tips Improved satisfaction, retention Sales team underperforming Upsell/cross-sell recommendations Increased revenue per interaction Quality issues with call handling Real-time coaching suggestions Improved quality scores Agent knowledge gaps Targeted knowledge recommendations Improved FCR, fewer escalations Multilingual support Language-specific scripts and guidance Consistent quality across languages Knowledge Base Organization for Copilot Knowledge Base Structure: ├─ TECHNICAL SUPPORT │ ├─ Password Reset │ │ ├─ Steps 1-5 │ │ ├─ Common Issues │ │ └─ When to Escalate │ ├─ Two-Factor Auth │ ├─ Account Recovery │ └─ Billing Issues │ ├─ SALES │ ├─ Plan Comparison │ ├─ Pricing Information │ ├─ Promotional Offers │ ├─ Upsell Scenarios │ └─ Contract Terms │ ├─ CUSTOMER SUCCESS │ ├─ Onboarding Steps │ ├─ Best Practices │ ├─ Feature Usage │ └─ Integration Guides │ └─ COMPLIANCE ├─ Required Disclosures ├─ Privacy Policies ├─ Legal Requirements └─ Prohibited Actions Copilot Performance Metrics Recommendation Quality Metric Target Purpose Recommendation Accuracy >85% Agent finds recommendations helpful Agent Acceptance Rate >60% Agents actively use suggestions Relevance Score >4/5 Recommendations match context Time to Resolution -15% Faster with Copilot assistance Knowledge Article Match Rate >90% Correct article suggested Agent Performance Metric Target Purpose First Contact Resolution +10-25% Copilot guidance improves outcomes Average Handle Time -10-20% Faster resolution with suggestions Customer Satisfaction +5-15% Better agent performance Quality Score +5-10% Improved call quality Agent Confidence +20-30% Subjective improvement Best Practices Knowledge Base Optimization Keep articles current - Update quarterly or when processes change Write for clarity - Use simple language agents can understand quickly Include visuals - Screenshots and diagrams help comprehension Provide examples - Real scenarios help agents apply knowledge Tag thoroughly - Use keywords and metadata for better matching Test accuracy - Verify all knowledge is correct before publishing Copilot Configuration Start simple - Begin with high-confidence recommendations only Tune relevance - Adjust thresholds based on agent feedback Monitor adoption - Track which recommendations agents use Gather feedback - Ask agents what would help them more Iterate quickly - Update knowledge and rules frequently A/B test - Try different recommendation approaches Agent Enablement Provide training - Agents need to understand Copilot features Share success stories - Show how other agents use it effectively Encourage experimentation - Let agents find what works for them Make feedback easy - Simple thumbs up/down for recommendations Celebrate improvements - Recognize agents who adopt well Continuous learning - Regular coaching on Copilot usage Monitoring & Optimization Track recommendations - See which articles agents use most Monitor accuracy - Ensure recommendations are helpful Gather sentiment - Ask agents about Copilot effectiveness Review metrics - Check impact on FCR, AHT, CSAT Optimize content - Update articles agents find unhelpful Plan improvements - Use data to guide enhancements Common Implementation Scenarios Scenario 1: Technical Support with Knowledge-Heavy Topics Configuration: ├── Knowledge base with 200+ articles ├── Intent-based recommendation ├── Sentiment monitoring enabled ├── De-escalation scripts └── Escalation pathways Expected Results: ├── FCR improvement: 15-25% ├── AHT reduction: 12-18% └── Agent confidence: +25% Scenario 2: Sales Team with Upsell Focus Configuration: ├── Product recommendation engine ├── Upsell/cross-sell playbooks ├── Customer history integration ├── Pricing recommendations └── Contract template suggestions Expected Results: ├── Revenue per call: +15-30% ├── Sales conversion: +10-20% └── Agent productivity: +20% Scenario 3: Multilingual Support Configuration: ├── Knowledge base in multiple languages ├── Language-specific scripts ├── Tone guidance per language ├── Cultural sensitivity prompts └── Translation recommendations Expected Results: ├── FCR consistent across languages ├── Quality standardization └── Customer satisfaction: +10-15% Troubleshooting Guide Issue Cause Resolution No recommendations appearing Knowledge base empty or not indexed Populate knowledge base and index Irrelevant recommendations Poor knowledge article tagging Review and improve metadata/keywords Agents ignoring recommendations Not helpful or slow to appear Adjust relevance thresholds and review content Slow recommendation loading Too many articles to search Add more specific keywords and metadata Sentiment detection inaccurate Model needs more training data Collect more interactions and retrain High false positive sentiment Threshold too sensitive Adjust sensitivity settings lower Copilot not working for all queues Not enabled for specific queues Enable in queue configuration Knowledge articles outdated No review process Establish content review cycle Low agent adoption Agents don't understand value Provide additional training Module not appearing License not purchased or enabled Verify Premium edition and module purchase Agent Copilot vs. Traditional Knowledge Base Feature Agent Copilot Traditional Knowledge Real-time suggestions Yes, automatic Manual search required Context awareness AI-powered, contextual Search-based only Sentiment analysis Yes No Next action prediction Yes No Script guidance Automatic Manual lookup Learning capability Improves over time Static Setup complexity Medium-High Low Ongoing maintenance High (ML tuning) Medium Agent productivity +20-30% potential Baseline Customer satisfaction +5-15% improvement Baseline Sentiment Analysis in Copilot Sentiment Detection Levels Extremely Negative (-2) ├─ Angry, frustrated, hostile ├─ Risk: High churn likelihood └─ Action: Immediate de-escalation Negative (-1) ├─ Disappointed, concerned ├─ Risk: Medium churn likelihood └─ Action: Empathy + quick resolution Neutral (0) ├─ Standard interaction tone ├─ Risk: Low └─ Action: Normal service Positive (+1) ├─ Satisfied, pleased ├─ Risk: None └─ Action: Reinforce positive experience Extremely Positive (+2) ├─ Happy, delighted ├─ Opportunity: Upsell/cross-sell └─ Action: Leverage positive sentiment Integration Scenarios With Workforce Optimization Copilot + WFO ├── Agent assisted by Copilot ├── Interaction recorded ├── Quality scored with AI ├── Coaching recommendations generated └── Coaching delivered back to agent With Predictive Routing Copilot + Predictive Routing ├── Best agent routed to contact ├── Copilot assists during interaction ├── Recommendations improve outcome └── System learns for future routing With Analytics Copilot + Analytics ├── Copilot recommendation usage tracked ├── Impact on metrics measured ├── Dashboards show Copilot effectiveness └── Data guides optimization Interview Cheat Sheet Question Answer What is Agent Copilot? AI-powered real-time guidance system for agents Also known as? Agent Assist or Copilot Assistant What are the requirements? Premium edition + Customer Insights module What does it recommend? Knowledge articles, scripts, next actions, sentiment guidance How does sentiment analysis help? Detects customer frustration and suggests de-escalation Where is it configured? Admin → Architect → Agent Copilot What channels does it support? Voice, chat, email, social media How does it improve performance? FCR +10-25%, AHT -10-20%, CSAT +5-15% What's required for success? Quality knowledge base and agent training How does machine learning help? System learns from recommendations agents use vs. ignore Can agents reject recommendations? Yes, agents decide what to apply How long until ROI? 4-8 weeks to see significant improvement What if knowledge base is empty? Copilot won't have content to recommend How does it work with omnichannel? Provides channel-specific guidance (voice, chat, email, etc.) What's the biggest success factor? Quality, current, well-organized knowledge base Key Takeaways Real-Time AI Assistance - Copilot provides in-the-moment guidance during interactions Knowledge-Driven - Quality depends on knowledge base content and organization Sentiment Awareness - Monitors emotion and suggests appropriate responses Omnichannel Support - Works across voice, chat, email, and social channels Premium Feature - Requires Premium edition and Customer Insights module Significant Impact - FCR improvements of 10-25% typical Machine Learning - System improves recommendations based on agent actions Agent Adoption Critical - Success depends on agents trusting and using recommendations Ongoing Content Management - Knowledge base requires regular updates Quick ROI - 4-8 weeks to measurable improvements Migration Path from Manual Knowledge Search Phase 1: Assessment (Weeks 1-2) ├── Audit current knowledge base ├── Identify content gaps ├── Plan reorganization └── Set quality standards Phase 2: Content Preparation (Weeks 2-4) ├── Create/update knowledge articles ├── Add metadata and keywords ├── Organize by intent and queue └── Quality review all content Phase 3: Copilot Setup (Weeks 4-5) ├── Enable Agent Copilot ├── Configure recommendations ├── Set relevance thresholds └── Establish monitoring Phase 4: Agent Training (Week 5-6) ├── Educate on Copilot features ├── Practice with sample interactions ├── Explain recommendation types └── Share best practices Phase 5: Pilot & Optimization (Weeks 6-8) ├── Deploy to single queue ├── Monitor and gather feedback ├── Optimize recommendations └── Plan full rollout Phase 6: Full Deployment (Week 8+) ├── Enable across all queues ├── Provide ongoing support ├── Monitor metrics └── Continuous improvement Additional Resources Official Documentation Links Genesys Cloud Agent Copilot Guide: https://help.genesys.com/genesyscloud/current/en-us/AgentCopilot.html Knowledge Management Setup: https://help.genesys.com/genesyscloud/current/en-us/KnowledgeManagement.html Customer Insights Module: https://help.genesys.com/genesyscloud/current/en-us/CustomerInsights.html Support Contacts Genesys Sales: sales@genesys.com Genesys Support: https://support.genesys.com Community Forums: https://community.genesys.com Document Version Info Last Updated: March 2026 Source: Genesys PureCloud Official Documentation Version: 1.0