Deflection rate
Deflection rate measures the percentage of customer inquiries that are redirected away from human agents — typically to self-service resources, FAQ pages, or automated responses. It's one of the most commonly cited metrics in customer service automation, and one of the most misleading.
Deflection rate = (Inquiries handled without a human agent / Total inquiries) x 100
The problem with deflection rate as a success metric is that it measures activity, not outcomes. A customer who is shown a help article and gives up is counted as "deflected" — even though their issue is unresolved and their experience was negative. A customer who is routed through a chatbot loop and eventually abandons the conversation is "deflected." A customer who calls in after being deflected creates a new interaction that may also be deflected.
This is why leading CX organizations are shifting from deflection to resolution as their primary automation metric. The question isn't "did we keep the customer away from a human?" but "did we actually solve their problem?"
The distinction has real business consequences. High deflection rates often mask:
Hidden demand: Customers who need help but can't get it, leading to churn
Channel shifting: Customers deflected from chat who call in (or vice versa), inflating total contact volume
Repeat contacts: Customers who come back because their issue wasn't actually resolved
AI vendors who lead with deflection rate as their primary metric are often optimizing for the wrong thing. The more meaningful metrics are resolution rate (was the issue solved?) and customer effort score (how hard did the customer have to work?).
Related terms: resolution rate, self-service rate, customer effort score, cost per resolution
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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.