Customer retention rate
Customer retention rate measures the percentage of customers a business retains over a specific period. It's the inverse of churn and one of the most important metrics for subscription and recurring-revenue businesses.
Retention rate = ((Customers at end of period - New customers acquired) / Customers at start of period) x 100
A 95% monthly retention rate might sound strong, but it compounds to only 54% annual retention — meaning nearly half of customers leave each year. This math is why small improvements in retention have outsized business impact.
Customer service is one of the most direct levers for retention. Research from Bain & Company and others consistently shows that customers who contact support and have a good experience are actually more loyal than customers who never had an issue — the "service recovery paradox." The key word is "good experience." A bad support interaction is one of the strongest predictors of churn.
For CX teams deploying AI, retention rate is the north star metric. AI that resolves issues quickly and completely improves retention. AI that frustrates customers through unhelpful loops, inaccurate information, or inability to reach a human hurts retention. The technology is neutral — the implementation determines the outcome.
Retention is also where the value of proactive customer service becomes visible. Detecting early warning signals (decreased usage, unresolved complaints, billing friction) and intervening before the customer decides to leave is significantly more effective than reacting after a cancellation request. AI systems with customer lifecycle visibility can identify and act on these signals at scale.
Related terms: customer churn rate, customer lifetime value, customer satisfaction score
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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.