Most insurers don't realise they possess a significant data advantage regarding their customers. When households obtain motor insurance for multiple vehicles and home coverage, substantial data is generated. However, with each record isolated and priced independently, insurers miss vital connections.
This household data blind spot costs insurers considerably on both revenue and retention fronts.
The Problem with Policy-Level Thinking
Insurance traditionally organises around policies rather than people, reflecting how products are structured, systems built, and pricing models developed. Yet customers approach insurance holistically, viewing all their policies as part of household coverage.
A household might comprise one customer holding three policies across two insurers, a partner with separate cover, and an adult child quoting independently. These represent connected relationships sharing an address, risk profile, and market behaviour patterns. Pricing them as unrelated individuals causes insurers to overprice strong risks, underprice weak ones, and lose retention opportunities unknowingly.
What a Single Customer View Changes
A Single Household View assembles connected individuals and policies into a comprehensive picture, revealing who is this person, who are they connected to, what cover do they hold, and how do they behave in the market.
Three value streams emerge: pricing accuracy improves through enriched household claims history and quote behaviour; retention intelligence becomes more powerful when understanding household-level renewal intent rather than policy-level intent; and opportunity identification reveals cross-sell potential across product lines.
What Percayso Inform Delivers
Percayso's Intelligence Hub addresses this through Policy Intelligence, enriching policy books with external market data while monitoring quote feeds continuously. Policyholders' shopping behaviour becomes visible 30-50 days before renewal, allowing proactive response.
Customer Intelligence represents the next step, building household views from enriched policy data through entity resolution and multi-policy relationship mapping. The same data feed powers both products, minimising operational burden while maximising intelligence gains.
Quote Intelligence, the UK's largest quote dataset with billions of records across motor, home, and commercial lines, underpins both offerings, capturing every identity variation and behavioural pattern households leave across the market.
Pulling Ahead of the Competition
Insurance data capability follows a pattern where competitive gaps between leading and lagging firms widen gradually, then suddenly expand. Early enrichment pipeline adopters achieved better pricing; full-quote enrichment implementers will develop superior models. Household resolution represents the next competitive evolution, and timing is critical now.
The data exists, integration paths are straightforward, and insurers establishing household views first will gain pricing, retention, and customer lifetime value advantages creating difficult-to-close competitive gaps.
