{"site":{"name":"Koji","description":"AI-native customer research platform that helps teams conduct, analyze, and synthesize customer interviews at scale.","url":"https://www.koji.so","contentTypes":["blog","documentation"],"lastUpdated":"2026-05-28T10:27:51.744Z"},"content":[{"type":"documentation","id":"e4642de1-8d5d-47bd-b185-89fa94a1971d","slug":"ai-research-for-insurance","title":"AI-Powered Customer Research for Insurance Companies (2026)","url":"https://www.koji.so/docs/ai-research-for-insurance","summary":"Insurers can run policyholder satisfaction, claims-experience, retention, product concept, and pricing research at scale with AI interviews. Koji conducts voice or text conversations with policyholders, probes claims stories with adaptive follow-ups, captures NPS and CSAT with scale questions and coverage preferences with choice and ranking questions, and aggregates everything into a compliance-aware research report - no moderator or panel agency required.","content":"Insurance is one of the hardest industries to research well - and one with the most to gain from doing it. Policyholders only think about their insurer at a few emotionally charged moments (buying, renewing, and claiming), engagement with traditional surveys is low, and the journeys are long and regulated. AI interviews change the economics: with a platform like Koji, an insurer can conduct hundreds of voice or text conversations with policyholders, probe the *story* behind every claim or cancellation, and get an automatically analyzed report - without a panel agency, a moderator, or a six-week timeline.\n\nThis guide covers the highest-value research use cases across the insurance lifecycle and how to run each one.\n\n## Why Insurance Research Is Different\n\nFour things make insurance research uniquely challenging:\n\n- **Emotionally charged moments.** A claim is often filed during a stressful life event. A static survey cannot read tone or follow up on a painful detail; a conversation can.\n- **Low baseline engagement.** Most policyholders ignore email surveys. Response rates are poor, and the people who do respond skew to the extremes.\n- **Long, multi-touch journeys.** Quote, bind, service, claim, renewal - friction at any stage drives churn months later.\n- **Regulation and sensitivity.** Insurance data is sensitive, and health insurance touches PHI, so compliance has to be designed in, not bolted on.\n\nThe result: insurers often fly blind on the *why* behind their NPS and retention numbers. AI interviews close that gap.\n\n## High-Value Research Use Cases for Insurers\n\n### 1. Claims-experience research\nThe claim is the moment of truth. Run interviews with recent claimants - approved and denied - to learn where the process felt slow, opaque, or unfair. Voice mode captures the emotion; the AI probes \"What would have made that easier?\" so you get actionable friction, not just a score.\n\n### 2. Policyholder satisfaction and NPS drivers\nStop guessing why your NPS moved. Pair a **scale** question (0-10 likelihood to recommend) with adaptive probing so every detractor and promoter explains their rating. See the [NPS Survey Guide](/docs/nps-survey-guide).\n\n### 3. Retention and churn research\nInterview policyholders who cancelled or switched. Was it price, a bad claim, a competitor offer, or a life change? The AI digs into the real trigger - the kind of insight that a checkbox exit survey never surfaces.\n\n### 4. Product and coverage concept testing\nBefore launching a new rider, add-on, or coverage tier, test it. Use **single_choice** and **multiple_choice** questions for coverage preferences and a **ranking** question to prioritize features, all alongside open-ended reactions.\n\n### 5. Pricing and willingness-to-pay\nUnderstand price sensitivity for new products with conversational pricing research - the AI explores not just *what* a policyholder would pay but *why* a price feels fair or excessive.\n\n### 6. Digital onboarding and quote-flow usability\nWhere do prospects abandon the online quote? Run task-based interviews on your quote and bind flow to find the drop-off points.\n\n### 7. Agent and broker channel feedback\nFor intermediated lines, interview agents and brokers about tooling, commissions, and the support they need to sell more effectively.\n\n## How Koji Powers Insurance Research\n\n- **Voice or text, on the policyholder's schedule.** Participants join via a link 24/7 - no call center, no calendar coordination. Voice mode is ideal for emotional claims stories; text suits quick coverage or pricing checks.\n- **Adaptive AI follow-ups.** Koji probes hesitation and vague answers in real time, the way a skilled researcher would, surfacing the root cause behind a complaint.\n- **Structured questions for hard numbers.** Combine qualitative depth with chartable data: **scale** for NPS/CSAT, **single_choice** and **multiple_choice** for coverage and channel preferences, **ranking** for feature priorities, and **yes_no** for claim resolution. See the [Structured Questions Guide](/docs/structured-questions-guide).\n- **Methodology built in.** Studies run on real frameworks like Customer Discovery and Jobs to be Done, so the AI asks disciplined, non-leading questions.\n- **Automatic, segmentable reporting.** Koji aggregates every interview into a report with themes, verbatim quotes, and distribution charts, and you can segment by policy type, tenure, or claim status.\n\n## Compliance and Data Handling\n\nInsurance research must respect strict data rules. Koji supports GDPR-aligned consent and **transcript anonymization**, and PrimeClub members can run on their own model keys (BYOK) so conversations are never used to train third-party models. For health-insurance research where protected health information may surface, follow the HIPAA-focused guidance and practice data minimization - collect only the personal detail your analysis truly needs. See [GDPR-Compliant AI User Research](/docs/gdpr-compliant-ai-user-research) and [HIPAA-Compliant AI User Research](/docs/hipaa-compliant-ai-user-research).\n\n## A Simple Way to Start\n\n1. **Pick one moment of truth** - usually the claims experience or a recent-churn cohort.\n2. **Create a Koji study** and choose Customer Discovery as the methodology.\n3. **Add 4-6 questions**, mixing one open-ended claims story, an NPS scale question, and a coverage-preference choice question.\n4. **Choose voice** for emotional depth, **text** for speed.\n5. **Import or share the link** with the cohort and let interviews run in parallel.\n6. **Read the report** - themes and NPS drivers are ready as soon as interviews complete.\n\nWith new accounts getting 10 free credits, you can field a first claims-experience study before lunch. That is the 10x advantage over commissioning a panel study: insight in days, at a fraction of the cost.\n\n## Worked Example: A Claims-Experience Study\n\nHere is what a full study looks like end to end, so you can copy the shape.\n\n**Goal:** Understand why claims satisfaction dipped last quarter among auto policyholders.\n\n**Audience:** 30 recent claimants - a mix of approved and denied claims, filed in the last 60 days.\n\n**Interview plan (voice mode, ~7 minutes):**\n\n1. *Open-ended:* \"Walk me through what happened from the moment you needed to file a claim.\" (The AI probes for the emotional and practical friction points.)\n2. *Scale (0-10):* \"How likely are you to recommend us to a friend?\" with anchor probing on the rating.\n3. *Single choice:* \"At which stage was the experience most frustrating?\" (Filing / Waiting for a decision / Communication / Payout / None)\n4. *Yes/No:* \"Did you always know the status of your claim?\"\n5. *Open-ended:* \"If you could change one thing about the process, what would it be?\"\n\n**What you get back:** Within a day or two, Koji aggregates all 30 interviews into a report. You see the NPS distribution split by approved vs denied, a bar chart of the most frustrating stage, and the recurring themes - say, \"unclear status updates\" and \"slow adjuster callbacks\" - each backed by verbatim policyholder quotes. That is a board-ready insight in days, not a six-week panel engagement.\n\n## Which Use Case Fits Each Line of Business\n\n| Line of business | Highest-value first study |\n|---|---|\n| Auto | Claims-experience and FNOL friction |\n| Home/property | Claims-experience and renewal-price reaction |\n| Health | Onboarding/navigation and care-access experience (HIPAA-aware) |\n| Life | Application and underwriting-friction research |\n| Commercial/SME | Broker channel feedback and coverage concept testing |\n| Insurtech/D2C | Quote-flow usability and trial-to-policy conversion |\n\nStart with the moment that most directly drives churn or complaints for your line, prove the value with one study, then expand into an always-on voice-of-customer program. Because Koji runs interviews in parallel and analyzes them automatically, scaling from one study to a continuous program does not require hiring a research team - the platform absorbs the operational load that traditionally capped how much research an insurer could do.\n\n## Related Resources\n\n- [Structured Questions in AI Interviews](/docs/structured-questions-guide) - the six question types for insurance research\n- [Build a Voice-of-Customer Program](/docs/voice-of-customer-research-program) - make policyholder listening continuous\n- [NPS Survey Guide](/docs/nps-survey-guide) - measure and explain loyalty\n- [Customer Discovery Interviews at Scale](/docs/customer-discovery-interviews-at-scale) - talk to 100 policyholders in a week\n- [GDPR-Compliant AI User Research](/docs/gdpr-compliant-ai-user-research) - run compliant studies\n- [HIPAA-Compliant AI User Research](/docs/hipaa-compliant-ai-user-research) - for health-insurance research","category":"Use Cases","lastModified":"2026-05-28T03:20:58.530623+00:00","metaTitle":"AI Customer Research for Insurance Companies (2026)","metaDescription":"A practical guide to AI-powered customer research for insurers: claims experience, policyholder retention, product concept testing, and pricing research - run with voice or text AI interviews and analyzed automatically.","keywords":["insurance customer research","policyholder research","claims experience research","insurance market research","AI interviews insurance","insurance churn research","insurance product research"],"aiSummary":"Insurers can run policyholder satisfaction, claims-experience, retention, product concept, and pricing research at scale with AI interviews. Koji conducts voice or text conversations with policyholders, probes claims stories with adaptive follow-ups, captures NPS and CSAT with scale questions and coverage preferences with choice and ranking questions, and aggregates everything into a compliance-aware research report - no moderator or panel agency required.","aiPrerequisites":["Familiarity with your policyholder journey (quote, bind, service, claim, renewal)","A Koji account (free tier includes 10 credits)","Awareness of your data-handling and compliance requirements"],"aiLearningOutcomes":["Identify the highest-value research use cases across the insurance lifecycle","Design claims-experience and retention interviews that capture emotion and detail","Choose the right structured question types for NPS, coverage, and pricing research","Run policyholder research at scale without a panel agency","Handle insurance research data in a compliance-aware way"],"aiDifficulty":"intermediate","aiEstimatedTime":"9 minutes"}],"pagination":{"total":1,"returned":1,"offset":0}}