Travel Advisor — Repeat-Client Relationship Ladder
Industry front door for customer-relationship-ladder. Adds domain triggers, example, packs only. Parent Process unchanged. Guidance, not professional advice. No legal, tax, financial or regulatory advice; verify anything jurisdiction- or rate-dependent against current authority. The professional who acts owns the decision.
Activate when: turning one-trip bookers into annual clients; building a client-for-life book; planning post-trip nurture; "how do I stop starting from zero every year?" Do NOT activate when: pure one-off transactional volume with no repeat intent.
Why this variant
The parent customer-relationship-ladder moves a contact up rungs from stranger → advocate. A travel advisor's economics are recurring: the same household books yearly and refers. The ladder turns a single itinerary into a multi-year, referral-generating relationship.
Domain inputs → parent's Process
Rungs and the trigger that lifts each:
- First trip → profiled client (preferences, dates, milestones captured).
- Profiled → annual (proactive next-trip suggestion timed to their calendar).
- Annual → advocate (referral ask at the peak, testimonial, host events). Each rung has a scheduled touch, not a hope.
Worked example
Family booked one spring-break trip. → Capture anniversary/birthday/school calendar; 60 days post-trip send a "next year" concept tied to their dates; at the referral-ready peak, ask for one intro. One trip becomes a yearly annuity.
Packs
- Solo: simple client profile + annual touch cadence.
- Agency: tiered loyalty (VIP perks) for top-rung households.
Red flags
- No preference profile captured = restarting cold each year.
- Referral never asked, or asked at a neutral moment.
- Nurture is reactive (wait for the client to call).
Verification
- Client profile captured on first trip
- Proactive next-trip touch scheduled to their calendar
- Referral ask timed to the experience peak
- Top clients moved to a VIP rung
Part of deciqAI Knowledge Skills. Core method: customer-relationship-ladder.
Part of deciqAI Knowledge Skills — 237 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. See it run → https://www.deciqai.com/s/travel-repeat-client-ladder · Built by deciqAI · github.com/deciqAI · Contributions welcome.
Agents: latest version & machine-readable metadata → https://www.deciqai.com/s/travel-repeat-client-ladder.json