Upsell & Cross-sell
GLP-1 additive symptom-matched cross-sell
Your patient just told you they're tired all day and queasy after the shot. The add-on that answers that is sitting in your catalogue, unmentioned.
What it does
Most GLP-1 programs sell a row of add-ons — B12, L-carnitine, anti-nausea support, protein — but surface them as a flat menu the patient has to self-diagnose against. The result is a low attach rate and a patient quietly toughing out a symptom the program could have eased. In the same conversation where someone mentions queasiness, fatigue, or a goal, the agent reads that context and offers the one add-on that fits, as a next-best-thing rather than a cold pitch. Doing nothing leaves both a comfort gap and attach revenue on the table.
How it works
- 1Trigger. mid-conversation a patient mentions a symptom or goal — nausea after the dose, low energy, a protein concern — in chat or in-app.
- 2Decision. the agent maps the reported symptom to the contextually-right additive (nausea to a comfort kit, fatigue to B12, muscle worry to protein), then checks memory and consent — program stage, what they already own, prior offers and declines — so it never re-pitches or stacks. A quality judge gates the message so it reads as help, not merchandising, and keeps the framing non-prescriptive.
- 3Action. a single matched add-on appears in-thread with a one-line reason tied to what they just said, plus an in-app path to add it; commercial offers are steered through the commerce surface, kept separate from the clinical-safety conversation.
- 4Follow-through. the outcome (added, declined, not raised) is written to memory; if the symptom reads as severe or unexpected, the agent drops the offer and routes to the side-effect and escalation flow instead of continuing as a sale.
Configuration
How the agent is wired for this use case.
symptom_or_goal_mentioned behavioural event detected in the live conversation (a reported side-effect, energy complaint, or stated goal).- Messaging channel · detect the in-conversation symptom or goal cue and render the matched in-app add path
- Customer memory · read program stage, owned products, prior offers and declines; write back the outcome
- Product catalogue · select the single additive matched to the reported symptom and the patient's plan
- Clinical-safety judge · gate every offer against approved, non-prescriptive language and divert severe symptoms out
- Secure payment hand-off · complete any purchase through the client's hosted step, never in-chat
What you need
The inputs this use case runs on. Your channels stay yours; the agent supplies the judgment.
Signals
in-conversation symptom and goal cues from the live chat (reported nausea, fatigue, protein concern).
Data
consent state; program stage and treatment context; customer memory (owned products, prior offers, preferences); a catalogue of additives with the symptom or goal each one maps to.
Guardrails
the agent surfaces a product, never a dose or medical instruction; offer only against a real, in-context cue and only one at a time; judge gating on every unprompted message; frequency caps and instant opt-out; severe symptoms escalated to a clinician; product claims confined to approved language; payment only via secure hand-off.
Metrics it moves
- attach-rateup: add-ons attach to a symptom the patient just named instead of a flat menu they ignore.
- aovup: the matched additive lifts the order without a discount or a cold pitch.
- revenue-per-conversationup: a care exchange carries an attributable, well-matched attach.
- arpuup: the program monetises real, in-context needs inside the care relationship.
Related use cases
Next-best-product recommendation block
the in-reply offer UI, here matched to a reported symptom not a browsed item
GLP-1 muscle-preservation supplement upsell
the stage-triggered supplement attach this complements with symptom-triggered ones
GLP-1 side-effect education with red-flag escalation
where a severe symptom routes instead of becoming a sale
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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