All use cases

Upsell & Cross-sell

Coverage upgrade and add-on cross-sell

A new car sits in the driveway on an old policy that never covered it — the agent opens the coverage review before a claim turns the gap into a shock.

Get aheadNext best thingBehavioral triggerTime-based triggerSystem triggerChatEmailPushInsurance

What it does

Policyholders drift out of the right cover quietly. They buy a home, add a teenage driver, or take a quote at a limit that made sense three years ago, and the policy never catches up. Insurers can see the gap in their own data but usually surface it once a year on a renewal notice the customer skims. The agent reads the signals that say someone is under-insured — a life event, a newly insurable asset, a coverage gap flagged at quote or service — and opens a short coverage-review conversation that recommends the right rider or higher limit, framed as protection rather than a pitch and always inside suitability rules.

How it works

  1. 1
    Trigger. an under-insurance signal fires — a life-event flag (marriage, new home, new dependent), a new insurable asset on file, or a coverage gap detected during a quote or a service interaction.
  2. 2
    Decision. the agent checks the policyholder's memory (cover already held, riders previously declined, prior advice) against suitability and eligibility rules; a judge gates the message so only a genuinely fitting recommendation, with a clear reason, is sent.
  3. 3
    Action. a short chat or in-app message names the gap and the fix in one line, with the premium impact shown against the current policy; email or push is the fallback when the policyholder is not in-session.
  4. 4
    Follow-through. the outcome is written back to memory and sets a decline cool-down; if the signal resolves before the send (the gap is closed, the asset is removed), the stale message is cancelled. Binding the change runs in the insurer's own policy-admin flow — the agent guides, it never alters cover itself.
Example
AgentCongratulations on the new place. Your contents cover is still set at the limit from your old flat, which leaves about a third of what you'd need to replace everything today. I can add the higher limit for a small monthly difference — want to see the numbers?
CustomerHow much more are we talking?
AgentHere's the side-by-side on your policy. If it fits, I'll take you to the change screen and your insurer's own flow confirms it — nothing changes until you approve it there.

Configuration

How the agent is wired for this use case.

Triggera coverage_gap_detected or life_event signal from the policy admin system (or a gap flagged mid-quote), routed to the agent with the policy reference.
Tools & actions
  • Policy admin system · read current cover, limits, and held riders; stage a recommended endorsement for the customer to approve
  • CRM · read life-event and suitability flags; log the recommendation and the customer's response
  • Rating / quoting service · pull the premium delta for the proposed rider or higher limit
  • Customer memory · read prior declines and advice; write back the outcome and a decline cool-down
  • Messaging channel · send the coverage-review message and render the side-by-side comparison
Autonomymessage selection and the comparison run unattended under judge gating; any change to cover is confirmation-gated and binds only in the insurer's policy admin flow. Suitability-sensitive recommendations follow a regulated-advice policy class — the agent recommends and guides, it never binds or alters a policy itself.
Channelschat · email · push
Escalationcomplex suitability questions, complaints, or a request for regulated advice beyond the agent's scope hand off to a licensed adviser with full context.

What you need

The inputs this use case runs on. Your channels stay yours; the agent supplies the judgment.

Signals

life-event indicators, new-insurable-asset events, and coverage-gap flags from quoting or service — emitted by the insurer's own systems

Data

cover and limits held, riders available and their eligibility, suitability flags, consent state, customer memory of past offers and declines

Guardrails

suitability and eligibility rules enforced before any offer is composed; judge gating on every unprompted message; frequency caps and decline cool-downs; regulated-communications and advice-boundary policy; no binding or cover change by the agent — the insurer keeps owning both the policy-admin step and the send channels

Metrics it moves

  • attach-rateup, as riders and add-ons attach at the signal moment instead of waiting for an annual notice
  • arpuup, because right-sized cover adds premium from a policyholder the insurer already holds
  • renewal-rateup, since policyholders carrying the cover they actually need are less likely to shop the policy away

Related use cases

Upsell & Cross-sell

Banking product cross-sell from account signals

the same signal-to-offer logic on the banking side

Retain / Save

Policy auto-renewal and lapse save

the renewal-moment counterpart for insurance cover

Engage / Lifecycle

Health-benefits utilization nudge coach

nudging members to use cover they already pay for

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.

Book a demo