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Data partnerships

Data Partnerships at Insurances Quote

Aggregated, anonymized U.S. insurance-shopper data for research, journalism, regulatory work, and academic study.

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Updated May 21, 2026

DP
Data lead
David Park
VP of Data Science
SC
Editor
Sarah Chen
Editorial Director
PW
Research
Dr. Patricia Wong
Industry Analyst
MA
Ops
Marcus Allen
Senior Editor
Data ethics:Personally identifiable information is never part of a data partnership. All shared data is aggregated and statistically anonymized. We don’t share individual quotes or policies.
Quick facts
  • 1.8M+ binding-quote comparisons since 2018 — across all 50 states.
  • Quote-level data normalized for driver profile, vehicle/home, state, ZIP.
  • Trend series back to 2018; quarterly refresh.

What we can share

  • Aggregated rate data by state, coverage tier, and driver/property profile.
  • Trended series (month-over-month, year-over-year) for premium movement.
  • Shopper-behavior datasets — comparison frequency, switch rates, churn patterns.
  • Carrier-level aggregated quote data (no individual quotes).
  • Telematics-program adoption rates and self-reported savings.
Data partnership tiers
  • Tier
    Academic / research
    Use case
    University research
    Data scope
    Aggregated, anonymized, free with attribution
    Refresh
    Annual
  • Tier
    Journalism
    Use case
    News + investigative pieces
    Data scope
    Story-specific aggregations
    Refresh
    Story-specific
  • Tier
    Policy / regulatory
    Use case
    State DOI, NAIC, federal agencies
    Data scope
    Custom aggregations
    Refresh
    Quarterly
  • Tier
    Commercial research
    Use case
    Industry analysts, reinsurers
    Data scope
    Licensed data feed
    Refresh
    Quarterly

What we won’t share

Personally identifiable information about shoppers is never part of a data partnership. All shared data is aggregated and statistically anonymized; no individual quote or policy is identifiable in the datasets we provide.

Who we typically work with

  • Academic researchers studying insurance markets, consumer behavior, or regulatory impact.
  • Journalists writing about rate trends, underwriting, or market structure.
  • Policy organizations and state DOIs.
  • Industry analysts and reinsurers.
DP
Expert Tip
David Park
VP of Data Science
We’re strict about anonymization. K-anonymity floor of 30 (no group of fewer than 30 shoppers is ever surfaced as a distinct cell). Geographic granularity caps at county for most published datasets — ZIP-level data is only shared under contract with verified researchers.

Why partner with us on data

Pros
  • Largest shopper-comparison dataset in U.S. consumer insurance.
  • Cleaner than carrier-reported rate filings — captures real-world shopping behavior.
  • Trend series back to 2018 with consistent methodology.
  • Editorial independence ensures data isn't shaped to any narrative.
Cons
  • Aggregated only — no individual-record sharing.
  • Limited to verticals we cover (auto, home, renters, life).
  • K-anonymity floor of 30 — small cells get suppressed.
  • Quarterly refresh — not real-time.

Email data partnerships

data@insurances-quote.com

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Frequently asked questions

Is data free for academic research?
Yes — aggregated datasets are free for academic research with attribution. Custom queries may have a methodology fee.
Can journalists access this data?
Yes — for story-specific requests, email data@insurances-quote.com with the question + outlet. Usually answered within 2 business days.
Is there an API?
For commercial partners, yes — licensed feed. For one-off academic/journalism use, CSV / Excel exports.
How do you anonymize?
K-anonymity floor of 30, geographic granularity capped at county for public datasets, no driver-identifying attributes (license #, SSN, DOB).

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Advertiser Disclosure

Insurances Quote is an independent insurance marketplace. We are paid by carriers when shoppers switch to a policy we’ve helped match — never by the shopper. We don’t resell your lead data to third-party buyers, and the carrier rankings on this page reflect our composite quality score (35% claims, 30% price, 20% service, 15% digital tools), not paid placement.

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