Customer lifetime value (CLV)
Customer lifetime value (CLV or LTV) is the total revenue a business expects to earn from a single customer over the full duration of their relationship. It's a foundational metric for customer-centric businesses because it quantifies the economic impact of retention, satisfaction, and experience quality.
CLV = Average revenue per customer × Average customer lifespan
More sophisticated models account for gross margin, discount rates, expansion revenue, and the probability of retention at each period. For subscription businesses, CLV is directly linked to churn rate: reducing monthly churn from 5% to 3% can nearly double CLV.
The connection to customer service is direct and measurable. Every customer service interaction is either building or eroding CLV:
Positive resolution extends the customer relationship, increases likelihood of expansion, and generates referrals
Poor experience accelerates churn, reduces expansion, and creates negative word-of-mouth
Proactive service (catching and resolving issues before the customer contacts you) has the highest CLV impact because it signals the company is paying attention
For CX leaders, CLV reframes the cost conversation around customer service. When a CEO asks "why are we spending $X on support?", CLV provides the answer: because each resolved interaction protects $Y in future revenue. This is especially powerful when evaluating AI investments — if AI resolution improves CSAT and reduces churn, the CLV impact often exceeds the direct cost savings by an order of magnitude.
Related terms: customer churn rate, customer retention rate, 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.