AI personalization
AI personalization in customer service is the use of AI to tailor interactions based on the individual customer's history, preferences, behavior, and context — rather than providing the same generic experience to every customer. It means treating returning customers differently from first-time contacts, VIP customers differently from standard tier, and frustrated customers differently from satisfied ones.
Personalization goes beyond using the customer's name. Meaningful personalization includes:
Context awareness: Knowing the customer's recent interactions, open issues, and account status before they explain anything
Communication adaptation: Adjusting tone, detail level, and channel preferences based on past interactions
Proactive relevance: Surfacing information or offers that are specifically relevant to this customer's situation
Preference memory: Remembering how the customer likes to interact (prefers email over phone, wants detailed explanations vs. quick answers)
Segment-specific handling: Applying different workflows or policies based on customer tier, lifecycle stage, or risk profile
AI enables personalization at scale in a way that human agents struggle to match. A human agent handling 50 conversations per day can't remember each customer's history and preferences. An AI agent accesses the full customer profile for every interaction, every time.
For regulated industries, personalization must operate within compliance boundaries. A financial services AI should personalize communication style but not vary the accuracy of product information. A healthcare AI should adapt tone but not deviate from clinical guidelines. The personalization layer sits on top of the compliance layer, not alongside it.
Related terms: AI concierge, customer journey mapping, sentiment analysis
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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.