Use this glossary to look up the workforce management, contact center, and AI terms used across this help center, and the names Assembled uses for its features. For how Assembled calculates its metrics, see Metric calculations. If a term you need isn’t here, let our team know and we can add it.
A
Abandon rate (ABN): The percentage of contacts where the customer leaves the queue before reaching a team member, counted after a set wait, such as 30 seconds, 90 seconds, or 10 minutes.
Abandoned call rate (ACR): The percentage of calls where the caller hangs up before a team member answers.
After call work (ACW): The wrap-up time after a contact, beyond the conversation with the customer. It can include tagging the contact, adding notes for future support, routing the contact to the right team, or solving the underlying problem.
Agent: In this help center, an agent is an AI agent: a chat, voice, or email agent. See AI agents and Copilot. Some labels in Assembled, such as Agent states and Real-time agent analysis, use “agent” for the people on your support team, whom this help center calls team members.
Agent assist: AI that helps support team members while they work on a case, for example by drafting replies, finding knowledge, and summarizing the conversation. In Assembled, this is Copilot.
Agent occupancy: Another name for occupancy rate.
Agent states: The statuses a team member can have in your connected support platform, such as logged in, away, or on a call. Assembled imports them and uses them to measure adherence, for example on the Real-time overview. See Agent state mappings.
Agent utilization: How well team members use their time at work, usually measured as the utilization rate.
Agentic AI: AI that works toward a goal by deciding which steps to take, using tools such as your order system or CRM, and acting on the results, rather than only answering questions. For example, an AI agent following a workflow can look up an order, check it’s eligible for a return, and start the return.
AI agent: Software that uses AI to resolve customer cases on its own: it answers questions, looks up and updates data in your systems, and hands off to your support team when a person is needed. Assembled has a chat agent, a voice agent, and an email agent. See AI agents and Copilot.
AI experience score: Assembled’s rating of how well a conversation with an AI agent went for the customer: Excellent, Good, or Poor, based on resolution progress, efficiency, and sentiment. See AI experience scores and outcomes.
AI outcome: How a conversation with an AI agent ended: Resolved, Handed off, or Abandoned, or Active while it’s still in progress. See AI outcome.
Arrival pattern: When and how often contacts arrive, based on past contacts. It shows the peaks and troughs in contact volume.
Attrition: The rate at which people leave your support team. It can be external (they leave the company) or internal (they move to another team), and voluntary or involuntary.
Automatic speech recognition (ASR): Technology that uses AI to turn spoken words into written text, for example so a voice AI agent can understand what a caller says.
Availability rate: The share of a team member’s time spent ready to work with customers but not handling a contact, such as the time between contacts.
Average handle time (AHT): The average time spent on a contact, including hold time and after-contact work such as follow-up and notes. See Agent average handle time.
Average resolution time (ART): The average time it takes to resolve a case, from when it’s opened to when it’s solved, over a given period. Also called time to resolution or mean time to resolution (MTTR).
Average speed of answer (ASA): The average time customers wait before a team member answers their call or chat. Assembled reports show it as Average time to answer.
Average talk time (ATT): The average time a team member spends talking with a customer on a call. Unlike average handle time, it doesn’t include after call work.
Average time to abandon (ATA): The average time customers wait in the queue before they hang up or leave. Also called average patience.
B
Back-office optimization (BOO): Streamlining and automating the work a contact center does behind the scenes, such as processing requests and updating records, rather than live conversations with customers.
Backlog: The contacts that are still waiting to be handled or resolved after your expected handling time. Contacts that are still within the expected handling time usually aren’t counted. A backlog can grow quickly, because new contacts keep passing the expected handling time while the team works through it.
Blended agent: A team member who handles both incoming and outgoing calls.
Business process outsourcing (BPO): Contracting part of your operations, such as customer support, to a third-party vendor. In Assembled, you share your staffing requirements with your BPOs and track them in BPO planning. See BPO planning.
C
Call center: A team or department that handles inbound and outbound phone calls with current and potential customers. A contact center also handles other channels, such as email and chat.
Call center agent productivity: How efficiently team members handle customer interactions, often measured with metrics such as average handle time and cases solved.
Call center SLA: The service level a call center commits to, such as answering 80% of calls within 20 seconds.
Call center workforce optimization: The same as contact center workforce optimization, for a team that supports customers by phone.
Capacity planning: Working out how many people you’ll need over the coming months or year, based on expected volume, handle time, shrinkage, attrition, and how much of the work AI agents will take on, so you can plan hiring and BPO capacity in time. Also called long-term planning or headcount planning.
Case: One customer request that your team or an AI agent handles, such as an email, a chat conversation, or a phone call. Support platforms also call cases tickets, conversations, or contacts.
Champion challenger model: A way to test two or more approaches against each other to see which gives the best results. The approach you use now is the champion, and each alternative is a challenger.
Channels: The ways your team supports customers: email, chat, SMS, phone, social, and back office.
Chatbot: A program that answers customers in chat. Traditional chatbots follow scripted menus and decision trees, while AI agents understand questions in the customer’s own words and can take actions. If you use a chatbot from another provider, see Third-party chatbot conversations.
Concurrency: The number of contacts a team member handles at the same time, on average, such as two or three chats at once. Assembled uses it to calculate required staffing for chat, SMS, and social. See Staffing parameters.
Contact center: A team or department that handles a company’s communication with customers across channels, such as phone, email, chat, social media, and SMS.
Contact center forecasting: Predicting how many contacts, such as calls, emails, and chats, a contact center will receive over a coming period, so you can plan staffing. See Manage forecasts.
Contact center scorecard: A set of metrics that measures a contact center’s efficiency, quality, and customer experience, for the whole team or for each team member. In Assembled, see Agent scorecard.
Contact center workforce optimization (WFO): Improving how efficiently and effectively a contact center’s team works, by combining workforce management with practices such as quality management, performance management, and analytics.
Contact reason: Another name for intent.
Containment rate: The percentage of conversations an AI agent handles without handing off to your support team, including conversations where the customer leaves. In Assembled, containment rate = (Resolved cases + Abandoned cases) ÷ Total cases. See How resolution and containment rates are calculated.
Copilot: Assembled’s AI assistant for your support team. It works in the tools your team already uses, such as Zendesk and Salesforce, to suggest replies, surface knowledge and customer data, translate conversations, and write summaries. See How Copilot works.
Cost per case: The average cost of each support contact. It can include fixed costs, such as office and internet costs, and variable costs, such as scheduled labor and unscheduled overtime. Also called cost per contact.
Customer effort score (CES): A survey-based measure of how easy it was for a customer to get help, usually asked after a contact on a scale such as 1 to 7.
Customer experience analytics: Analyzing customer interactions and feedback, such as conversations and survey responses, to improve the customer experience.
Customer satisfaction score (CSAT): The score a customer gives in a survey after a contact. A survey can ask about parts of the experience, such as time spent, the team member who helped, and whether the issue was resolved, or ask for one rating from 1 to 5.
D
Default events: Events whose event type is classified as Default: parts of a shift that don’t count toward your staffing numbers, such as meetings, training, project time, lunches, and breaks. See Event types.
Deflection: When a customer gets what they need from self-service, such as a help center article or an AI agent, instead of reaching your support team. The deflection rate is the percentage of potential contacts this happens for. To see how a deflection rate would change your staffing needs, see Model a what-if scenario.
DuPont shift schedule: A rotating schedule of 12-hour day and night shifts over a four-week cycle, which includes a block of seven days off in a row.
E
Erlang formulas: Industry-standard formulas that model how staffing, contact volume, and response time relate. For a given set of inputs, they give the number of people you need. For more, see How to use Erlang C to plan staffing.
Escalation: Passing a case to someone better placed to handle it, such as a more senior team member or a specialist team. When an AI agent passes a case to your support team, it’s called a handoff.
Events: Blocks of time on a schedule. Each event has an event type, classified as Productive, Default, or Time off.
F
Filters: Ways to narrow what a page shows, such as by Channel, Queue, Site, Team, and Skill on the Staffing timeline.
First contact resolution (FCR): The percentage of issues resolved in the first contact, without the customer needing more help.
First response time (FRT): The time between a customer’s first message and the first reply. Many teams measure it in business hours, so time you’re closed doesn’t count. See Business hours. If an AI agent replies first, consider also tracking how long customers wait for a person after a handoff, since instant AI replies keep first response time low.
Five by eight schedule: A schedule of five eight-hour shifts a week.
Forecast accuracy: How closely your forecast of support volume matches the volume you actually get.
Full-time equivalent (FTE): The hours needed to handle your volume, expressed in full-time work weeks of 40 hours.
G
Generative AI (GenAI): AI that creates new content, such as text or speech, from instructions. AI agents and Copilot use generative AI to write replies in your brand’s voice.
Grounding: Making an AI model base its answers on trusted sources you provide, such as your knowledge base and customer data, rather than on its general training. Grounded answers are less likely to contain hallucinations.
Guardrails: Rules that keep an AI agent’s replies and actions within limits you set, such as topics it mustn’t discuss, information it must never share, or actions that need a person to approve them. For the chat agent, you write guardrails as critical instructions.
H
Hallucination: An AI answer that sounds confident but is wrong or isn’t supported by your sources, such as a made-up policy. Grounding, complete knowledge, and regular quality review make hallucinations less likely.
Handoff: When an AI agent passes a conversation to your support team, ideally with a summary and the details it collected, so the customer doesn’t have to repeat themselves. Also called a human handoff or an escalation. For the chat agent, you set how and when it hands off on the Handoff tab.
Headcount planning: Another name for capacity planning.
Human in the loop (HITL): A setup where a person reviews, approves, or corrects what AI prepares before it reaches the customer or takes effect. In Assembled, a workflow in Agent review mode prepares replies and actions for a support team member to confirm in Copilot. See Workflow activation.
I
Intent: What a customer wants to do when they contact you, such as check an order’s status, request a refund, or cancel a subscription. AI agents use the intent to decide how to respond and which workflow to follow. Also called the contact reason. Assembled can categorize your cases by contact reason automatically. See Case category classification.
Interactive voice response (IVR): A phone system that greets callers and routes them with a menu of keypad or spoken options, such as “Press 1 for billing.” Assembled’s voice agent works with your IVR, and answers calls in natural conversation instead of a menu. See Voice agent.
Interval: A period of time that’s forecast, staffed, and analyzed on its own. Common intervals are 60, 30, or 15 minutes. In Assembled, your company’s base interval is usually 30 minutes.
Intraday management: Adjusting schedules and workloads during the day in response to what’s happening, such as volume that’s higher than forecast or unplanned absences. In Assembled, you watch the day on the Real-time overview and change the schedule on the Staffing timeline.
Intraday scheduling: Creating and changing schedules for the same day.
J
Jailbreak: An attempt to get an AI model to ignore its instructions or guardrails, for example by asking it to play a role or claiming special permission. In a related attack, prompt injection, the instructions are hidden in content the AI reads, such as a message or a web page. Include attempts like these when you test an AI agent before you activate it.
K
Key performance indicator (KPI): A metric your team tracks to measure progress toward a goal, such as service level, CSAT, or resolution rate.
Knowledge base: The articles and documents your team and your AI agents use to answer questions, such as help center articles and internal guides. AI agents and Copilot answer from the knowledge sources you connect, such as your help center, Notion, Confluence, or Google Drive. See Knowledge management and Knowledge base best practices for AI.
Knowledge gap: A question your knowledge base doesn’t answer, or answers only in part, so an AI agent can’t resolve it. In Assembled, you can see the topics where AI agents couldn’t find what they needed. See Knowledge opportunities.
L
Large language model (LLM): An AI model trained on large amounts of text, so it can understand questions and write replies in natural language, such as the models behind ChatGPT, Claude, and Gemini. AI agents and Copilot use large language models.
Long-term planning: Another name for capacity planning.
M
Model Context Protocol (MCP): An open standard for connecting AI assistants to other tools and data. In Assembled, MCP connectors give your AI agents tools from your own systems, and the Assembled MCP server lets AI assistants such as Claude or ChatGPT answer questions from your Assembled data.
Multichannel contact center: A contact center that supports customers through more than one channel, such as phone, email, and chat, usually with each channel handled separately.
N
Net Promoter Score (NPS): A survey-based measure of customer loyalty. Customers rate how likely they are to recommend you on a scale of 0 to 10, and NPS is the percentage who answer 9 or 10 minus the percentage who answer 0 to 6.
Net staffing: Scheduled staffing minus required staffing for an interval. A positive number is a surplus, and a negative number is a shortfall. See Staffing metrics.
O
Occupancy rate: The percentage of a team member’s available and occupied time spent working on customer issues. Industry-standard occupancy is 70–85%, and staying at or below 85% is often recommended to avoid burnout. Also called agent occupancy. See Occupancy.
Omnichannel contact center: A contact center that connects its channels, so a customer can move from one to another, such as from chat to email, without having to repeat themselves.
Overtime (OT): Hours worked beyond a team member’s scheduled or contracted hours, often to cover volume that’s higher than planned. In Assembled, you can publish extra work slots for people to pick up. See Extra work and voluntary time off slots.
P
Panama shift schedule: A rotating schedule of 12-hour shifts over a two-week cycle: two days on, two off, three on, two off, two on, and three off.
People: Everyone in your company’s Assembled account who can sign in, such as support team members, team leads, managers, and admins. Admins manage them in Manage team > People management. See People management.
Pitman shift schedule: A rotating schedule of 12-hour shifts, usually worked by four teams, with two teams on days and two on nights. Each team follows the same two-week pattern as the Panama schedule: two days on, two off, three on, two off, two on, and three off.
Productive events: Events whose event type is classified as Productive and mapped to a channel, such as email or chat. They count toward your scheduled staffing.
Prompt: The instructions and context given to an AI model to tell it what to do. For an AI agent, these include your style guide, instructions, and workflow steps. See Chat agent instructions and style.
Q
Quality assurance (QA): Checking that support conversations meet your standards, usually by reviewing a sample of them against set criteria. In Assembled, you review how your AI agents and Copilot respond in AI quality > QA review. See Quality review.
Quality management: The ongoing work of measuring and improving the quality of customer interactions against standards you set.
Queues: A way to split a channel’s volume, using the cases in your connected platform, so you can forecast and staff it separately. For example, VIP support and standard support can be separate queues with their own forecasts and service levels. See Queues and exclusions.
R
Real-time adherence (RTA): Checking during the day whether team members are doing what they’re scheduled to do, by comparing their agent states with their schedules. See Real-time overview.
Real-time overview: A live dashboard of your current volume, service levels, what your team is doing, and whether team members are in adherence. Go to Monitor > Real-time overview. See Real-time overview.
Required staffing: The staffing your forecast says you need in each interval to meet your service level, after allowing for shrinkage and concurrency. See How required staffing is calculated.
Resolution rate: The percentage of conversations an AI agent resolves without help from your support team. In Assembled, resolution rate = Resolved cases ÷ Total cases. Unlike containment rate, it doesn’t count conversations where the customer leaves. See How resolution and containment rates are calculated.
Retrieval-augmented generation (RAG): A way of grounding an AI model: before it answers, it searches your knowledge base for relevant content, then uses what it finds to write the reply. This is how AI agents answer from your own articles rather than from general knowledge. In Assembled, you can control which articles are searched for each case. See Knowledge mapping.
Rotating shift pattern: A schedule where people move between different shifts, such as day, evening, and night shifts, over a set period. In Assembled, you can set up a rotation of several weeks in working hours. See Working hours.
S
Schedule adherence (SA): The time a team member spends doing what they were scheduled to do, as a percentage of their scheduled time. For example, if a team member is scheduled for 100 minutes and follows their schedule for 90 of them, their schedule adherence is 90%.
Schedule conformance: The time a team member spends working, as a percentage of the time they were scheduled to work, whether or not they worked at the scheduled times. For example, if a team member is scheduled to work 100 minutes and works 95, their conformance is 95%.
Schedule efficiency: How closely your scheduled staff matches what an interval requires. It can be expressed as a percentage.
Self-service: Ways customers can solve problems without contacting your team, such as a help center, a community forum, or an AI agent.
Sentiment analysis: Using AI to detect how a customer feels in a conversation, such as frustrated or satisfied, and how that changes. In Assembled, sentiment is part of the AI experience score, and negative sentiment is one of the signals the chat agent uses to decide when to hand off. See Sentiment.
Service level (SL): Your team’s target for how quickly you first respond to a customer. Also called a service level agreement (SLA). See Staffing parameters.
Shift bidding: A process where team members rank the shifts they’d like to work, and shifts are assigned in an agreed priority order, such as by seniority or performance.
Shift swap: When two team members trade shifts, usually with a manager’s approval. See Shift swaps.
Shrinkage: The share of paid time when team members aren’t available to handle contacts, because of breaks, training, meetings, vacation, and absences.
Sites: A filter, usually for a location, such as APAC, EMEA, New York, or San Francisco.
Skills: A filter for a proficiency that’s useful for certain cases or customers. If people on your team specialize, you can show it with skills.
Skills-based routing: Sending each case to someone with the skills it needs, such as a language or knowledge of a product.
Southern swing shift schedule: A rotating schedule of 8-hour shifts over a four-week cycle, usually a block of day shifts, a block of evening (swing) shifts, and a block of night shifts, with days off between each block.
Speech analytics: Analyzing recorded calls, usually with automatic speech recognition, to find insights such as common topics, customer sentiment, and compliance issues.
Staffable: A person who can be scheduled in Assembled. Staffable people appear on the Staffing timeline.
Staffing timeline: The page where you compare required staffing with your schedule, and create or change your team’s schedule. Go to Schedule > Staffing timeline. See Staffing timeline.
T
Teams: A filter that shows who belongs to which team. You name teams to match how your organization works, such as “Team A” or “Tier 2 team.”
Templates: Saved schedules that you can apply again to a later date range, for your whole team or for the people who match the filters and channels you’ve set. See Schedule templates.
Text-to-speech (TTS): Technology that turns written text into natural-sounding speech, so a voice AI agent can talk to callers. It works alongside automatic speech recognition.
Time off events: Events whose event type is classified as Time off, such as PTO or sick leave. When team members request time off, they choose which time off event type to use.
U
Utilization rate: The time a team member is productive or available to handle contacts, as a percentage of their total paid hours. The rest is time away from support, such as breaks, meetings, training, and meals.
V
Voice AI: AI that holds spoken conversations, by combining automatic speech recognition, a large language model, and text-to-speech. Assembled’s voice agent uses it to answer support calls. See Voice agent.
Volume forecast: A prediction of the contacts your team will receive over a period, such as a day, a week, a month, or the next 15 minutes.
Volumes: The contacts a support team expects to handle. They can be split by the channel they come in on, such as email, chat, phone, or SMS.
Voluntary time off (VTO): Optional time off, usually unpaid, that you offer when you have more people scheduled than you need. See Extra work and voluntary time off slots.
W
Workflows: In Assembled, the instructions that tell AI agents how to handle a specific kind of case, such as a cancellation request or an order status question. Each workflow has a trigger, which decides which cases it handles, and steps that look up data, reply to the customer, and update the case. See Building workflows.
Workforce engagement management (WEM): Keeping support team members satisfied, motivated, and productive, for example with flexible schedules, shift swaps, coaching, and recognition.
Workforce management (WFM): The forecasting, staffing, scheduling, and metrics that help your team meet its service goals reliably and efficiently. In Assembled, you can plan for your in-house team, your BPOs, and your AI agents in one place.
X
XLA (experience level agreement): A target for how customers experience your support, such as satisfaction, effort, or sentiment, rather than an operational target, such as response time in a service level agreement (SLA). You can measure it with scores such as CSAT, customer effort score, and the AI experience score.
Y
Year over year (YoY): Comparing a metric with the same period a year earlier, such as this December’s volume with last December’s, to see growth and seasonal patterns. The Seasonal and Prophet forecast models capture yearly patterns like these. See Forecast models.
Z
Zero-touch resolution: A case resolved entirely by automation, such as an AI agent, with no work from your support team. In Assembled, an AI agent case with the Resolved outcome is a zero-touch resolution, and the resolution rate shows how often it happens.
For longer explanations of many of these terms, see the Essential WFM glossary on the Assembled website.