How people research Life insurance and protection products

Evidence lanes, not one blended number

Every available lane was scanned. The report keeps AI-chat behaviour, conventional search queries, image-generation prompts and public Q&A separate, so that a useful broader view does not become a misleading claim about how people use ChatGPT.

What people are using language tools for

Across the human-language lanes, private health cover is the largest measured cluster. The strongest evaluation signal is price or affordability, while consideration is the most common funnel stage. AI-chat and traditional-query figures are intentionally shown side by side because they answer different questions.

Brand-adjacent wording appears in 32 AI-chat matches (13.17%). This is directional prompt evidence, not branded share of voice or sentiment.

The terms and product areas people use

Examples by product or service cluster

Safe, exact wording from the accepted AI-chat and traditional-query lanes. The source lane is shown beside each prompt.

Examples by funnel stage

Safe, exact wording from the accepted AI-chat and traditional-query lanes. The source lane is shown beside each prompt.

Examples of commercial behaviour

Safe, exact wording from the accepted AI-chat and traditional-query lanes. The source lane is shown beside each prompt.

Examples by persona and situation

Safe, exact wording from the accepted AI-chat and traditional-query lanes. The source lane is shown beside each prompt.

Direct prompts and long consultations are different

Earlier versions blended all prompt lengths, which made the average meaningless. This report separates short, direct question-style prompts from long consultations or pasted context.

Prompt patterns and real safe examples

The left-hand phrase is a rule-derived summary. The examples are exact, short, non-personal prompts from the accepted human-language lanes.

Examples behind the prompt patterns

Safe, exact wording from the accepted AI-chat and traditional-query lanes. The source lane is shown beside each prompt.

Australian-specific evidence

Only full, unambiguous country and city names are counted. State abbreviations are deliberately excluded. Small counts are directional, not a local market-size claim.

Safe Australian wording

Answer patterns to target

Use these patterns as answer-design and page-brief targets. Replace [product], [provider], [context] and [persona] with the client's verified offer and terminology.

Recommended content and conversion assets

The priority build list

Ranked by weight of human-language evidence in this corpus. Rows marked directional (low n) are early signals, not measured demand.

priority	industry cluster	human language evidence	confidence	recommended build
1	Private health cover	387	measured	Create a dedicated private health cover hub with price or affordability guidance and a compliant next step.
2	Life cover	332	measured	Create a dedicated life cover hub with price or affordability guidance and a compliant next step.
3	Policy and provider research	61	measured	Create a dedicated policy and provider research hub with price or affordability guidance and a compliant next step.
4	Income protection and TPD	5	measured	Create a dedicated income protection and tpd hub with coverage or exclusions guidance and a compliant next step.
5	Trauma and critical illness	2	directional (low n)	Create a dedicated trauma and critical illness hub with reviews or trust guidance and a compliant next step. Evidence is thin here; verify before prioritising spend.

• Use a product hub that separates life cover, income protection, TPD, trauma, funeral and private health rather than treating insurance as one generic category.
• Build decision-support pages around price, cover amount, eligibility, exclusions, waiting periods and claims. Link these to compliant quote or advice pathways.
• Create comparison and provider-selection content only where the evidence is current, criteria are transparent and regulated-product claims receive review.
• Use life-stage pages for family, mortgage and self-employed contexts where the accepted prompt sample supports them.
• Add search-volume, CPC and live AI-answer validation before allocating media or forecasting opportunity.

Top safe query-style wording

Ranked by the number of accepted source lanes and source records in this corpus, not external search volume. Personal, URL, credential and content-generation prompts are removed.

What this report does and does not prove

The active classified corpus contains 4,734,874 stored rows and 2,909,549 exact-unique prompts. It does not contain six million provenance-cleared LLM questions, and the wider 50M archive is not a customer-behaviour dataset. Counts show evidence within these sources, not Google search volume, demand forecasts, market size, AI-answer share of voice or conversion potential. Add external SV/CPC, live model-answer sampling and compliance review before prioritising spend.