Convert
Warm referral from free user to paid clinical consult
A free user asks the weight-medication chat a question only a clinician should really answer — the agent helps with what it can, then opens the door to the paid consult instead of leaving the question to evaporate.
What it does
GLP-1 programs run free chat surfaces that absorb a steady stream of medication questions, and a large share of that support traffic is exactly the kind of clinical question with no paid route attached today. The user gets a general answer and leaves; the paid clinical consult that would actually serve them sits one tap away, never offered, and the free surface stays a pure cost. The agent recognizes when a free or unpaid user's medication question carries genuine program-fit intent, answers what is safe to answer in the free scope, and warmly routes them into the paid consult — request, intake, secure payment, then connection to a clinician — turning unrouted medical-question volume into started clinical care.
How it works
- 1Trigger. a free or unpaid user's message in the chat, WhatsApp, in-app thread, or a push-prompted return shows a medication question that warrants clinical input — a side-effect worry, a "should I be on this" question, a dose or eligibility question beyond the free scope.
- 2Decision. clinical red-flag detection runs first, so anything urgent escalates to a clinician rather than being routed to a paid funnel. Then the agent reads memory — what this user has asked before, whether they have already declined the offer — and a quality judge gates the referral for tone: warm and optional, never pressuring, and only where the consult is genuinely the better answer.
- 3Action. the agent answers within the free educational scope, then offers the paid clinical consult as the honest next step in the same thread — you request it, fill a short intake, complete payment on the program's secure step, and a clinician picks it up.
- 4Follow-through. a decline writes to memory and sets a cool-down so the next free question is not met with another pitch; the payment completes on the program's own hosted step, never in the conversation; conversion from referral is measured against a holdout so the lift is real, not assumed.
Configuration
How the agent is wired for this use case.
- Messaging channel · read the inbound message, answer within the free educational scope, and offer the consult referral in the same thread.
- App backend · read the user's tier and entitlement state to confirm the user is unpaid and the paid consult applies.
- Knowledge base · source the general, non-clinical guidance the agent shares before referring.
- Scheduling · open the consult request and the short intake when the user accepts.
- Hosted payment step (program-owned) · receive the hand-off to take the consult payment; the agent never takes payment itself.
- CRM · record the referral, the outcome, and any decline cool-down for measurement against a holdout.
What you need
The inputs this use case runs on. Your channels stay yours; the agent supplies the judgment.
Signals
chat, WhatsApp, in-app, and push messages from free-tier users, plus intent classification that separates a clinical-input-worthy question from one the free scope can fully answer.
Data
user tier and entitlement state, consent state, memory of prior questions and declined referrals, the paid-consult catalogue and its intake fields.
Guardrails
clinical red-flag detection runs before any referral; judge gating for tone on every referral; decline cool-downs and frequency caps; care-first policy so the free answer is never withheld to force the upgrade; the agent gives no medical or dosage advice and routes clinical decisions to a clinician.
Metrics it moves
- conversion-rateup on free-to-paid, because the consult is offered exactly when the user's medication question already justifies clinical input.
- revenue-per-conversationup, as a large share of free medical-question traffic that had no paid route starts producing consults.
- csatheld or up, because the referral is gated to moments where a clinician is genuinely the better answer, not pushed on every question.
Related use cases
Free-to-paid nudge in the care chat
the cross-vertical parent this specializes for the GLP-1 paid consult
Clinical red-flag detection and safe escalation
the safety gate that runs before any referral
Doctor copilot — pre-drafted clinical reply with citations
what the clinician picks up once the consult is paid
See it on your own customer journey
Bring one drop-off, one churn cliff, or one silent segment. We will show you what a proactive agent with memory and judgment does with it.
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