Why Insurance Personalization Keeps Failing

Every insurer wants to be "customer-centric" and "personalised." They've bought the CX platform, hired the head of customer experience, and launched the app. And most customers still experience the insurer as a faceless entity that knows nothing about them and asks the same questions every time they call.

The personalisation gap in insurance isn't a strategy problem or a tooling problem. It's a data problem, and a specific one.

What personalisation actually requires

Strip away the buzzwords. To personalise anything — an offer, a message, a renewal, a service interaction — you need to know three things at the moment of interaction:

  1. Who this person is — all of them, across every product and interaction, as one identity.
  2. What you know about them — their policies, claims, history, preferences, recent behaviour.
  3. What's most relevant right now — the next best action, given all of the above.

Most insurers fail at step one, which makes two and three impossible. And retailers who "get" personalisation nailed step one years ago, which is why the comparison is so unflattering.

The fragmentation tax, again

We keep coming back to this because it keeps being the answer. Your customer holds an auto policy in one system, filed a home claim in another, and called the contact centre last week — logged in a third. To that customer it's one relationship. To your systems it's three unlinked events about three unlinked records.

So when they call, the agent sees the auto policy and nothing else — not the home claim that's the actual reason for the call, not the life-insurance quote they abandoned online yesterday. The agent asks them to explain who they are, which is precisely the un-personalised experience the whole programme was meant to eliminate.

No amount of CX platform fixes this, because the CX platform is reading the same fragmented data. You've personalised the interface on top of an identity you don't actually have.

Why "next best action" projects stall

Next-best-action is the flagship personalisation use case: at any moment, recommend the single most valuable thing to offer or do for this customer. Cross-sell the home policy, pre-empt the churn, resolve the complaint.

These projects almost always stall, and predictably. The model is the easy part — recommendation is a solved science. The project dies because the model needs a complete, current, unified view of the customer to make a sensible recommendation, and that view doesn't exist. Fed fragments, the model recommends the home policy to someone who bought a house through you last year, or a retention offer to someone who already left. The recommendations are embarrassing, trust in the system collapses, and it gets quietly shelved.

The model didn't fail. It was asked to personalise for a customer the business couldn't actually see.

What has to be true first

1. Identity resolution. One customer, resolved across every product and channel, with a stable key. This is the non-negotiable prerequisite, and it's where the real work is.

2. A unified profile that updates. Not a nightly snapshot — a view that reflects the claim filed this morning and the quote abandoned an hour ago. Personalisation on stale data personalises to who the customer was.

3. The behavioural signals, joined in. Web visits, app usage, call history, telematics. The signals that indicate intent and satisfaction are usually the ones stranded furthest from the core policy data.

4. Then the model. Once one, two, and three exist, next-best-action is genuinely straightforward — and it works, because for the first time it can see the whole person.

The reframe for the person funding it

If you're being asked to fund "a personalisation initiative" or "a CX transformation," ask one question first: can we reliably identify the same customer across all our products today?

If the answer is no, the personalisation initiative is a house on sand. Fund the identity resolution first — it's less exciting, has no launch event, and it's the thing that determines whether everything built on top of it works or embarrasses you.

Customers don't experience your data architecture. But they experience its absence every single time they have to explain, again, who they are.

We build the identity resolution and unified customer data that real personalisation depends on. More at IntelliBooks.

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