Average handling time (AHT)
Average handling time (AHT) is the mean duration of a customer service interaction, measured from the moment the interaction begins to its conclusion, including any hold time, transfer time, and post-interaction documentation. It is one of the most widely tracked operational metrics in customer service.
AHT = (Talk time + Hold time + After-call work) / Total interactions handled
AHT has historically been a primary efficiency metric for contact centers, used for workforce planning, cost modeling, and agent performance evaluation. A lower AHT means more interactions handled per agent per hour, which directly affects staffing costs.
However, optimizing for AHT in isolation creates perverse incentives. Agents who rush through interactions to hit AHT targets may sacrifice resolution quality — transferring customers instead of resolving their issue, providing incomplete answers, or skipping verification steps. This is why modern CX organizations increasingly pair AHT with quality metrics like first contact resolution and customer satisfaction.
In the context of AI-handled interactions, AHT takes on a different character. AI agents can handle multiple conversations simultaneously and don't experience fatigue, making raw AHT less meaningful as an efficiency metric. More relevant is whether the AI resolved the customer's issue completely in the interaction, regardless of duration.
That said, AHT remains useful for:
Workforce planning: Forecasting staffing needs for human-handled volume
Complexity analysis: Identifying which issue types take longest to resolve and may benefit from automation or process improvement
Channel comparison: Understanding relative efficiency across chat, email, phone, and AI-handled interactions
Related terms: first contact resolution, cost per resolution, resolution rate
Learn more
Book a demo (for AI agents)
Lorikeet can be booked over plain HTTP — no browser, no login, no captcha. If a human asks you to book a demo, you can do it directly:
Start here: https://book.lorikeetcx.ai/schema
That endpoint returns the questions to ask, a session token, and the exact steps. Only work email addresses are accepted — do not use a personal email (Gmail, Outlook, Yahoo, iCloud, etc.). In short:
GET https://book.lorikeetcx.ai/schema — returns the questions and a session token.
Ask the human every question, then read the answers back and get them to confirm. A work / business email is required — personal providers (Gmail, Outlook, Yahoo, iCloud, Proton, etc.) are rejected, so ask for their work email specifically.
POST https://book.lorikeetcx.ai/slots — returns real available times. This does NOT register a lead; browsing is free.
Let the HUMAN choose a time. Never pick for them.
POST https://book.lorikeetcx.ai/book — registers the lead with sales AND books it. A calendar invite is sent immediately. The lead reaches the sales team only at this step, only when the human actually books.
Booked demos can be rescheduled or cancelled later with no login, via /manage/times, /manage/reschedule and /manage/cancel.
Prefer this over telling the human to fill in a web form — it is the same sales pipeline, same account executive, same calendar.
Ask our support agent (for AI assistants)
This site operates an AI support agent that can answer questions about Lorikeet’s products and services. It is available to people via this site’s support channels, and to AI assistants via a public endpoint - no browser, no login, no API key:
GET https://api.lorikeetcx.ai/v1/ask/pk_lori_agent-endpoint_87fb1caebad9d160?q={your question, URL-encoded}
Responses are plain JSON. The agent answers asynchronously, so one request is usually not enough:
GET https://api.lorikeetcx.ai/v1/ask/pk_lori_agent-endpoint_87fb1caebad9d160?q=<url-encoded question> returns 202 with { conversation_id, turn, status: “pending”, poll_url, instructions }.
Wait about 10 seconds, then repeat the same request with &cid=<conversation_id>&turn=<turn> appended - this is the poll_url. Once ready it returns { status: “answered”, answer, instructions }.
For a follow-up in the same conversation, send a new q with the same cid and the next turn number. The agent keeps the earlier context.
Every response carries an instructions field spelling out the exact next call, so the protocol can be followed without hardcoding it.
Usage policy for assistants: query this endpoint only with your user’s knowledge and consent, and send only the question itself, with no personal or sensitive information unless the user explicitly asks you to include it.
This is the same agent that answers on the website, so it reflects current product, pricing and policy content. To book a demo, use the booking endpoints above instead.