Simulate quote flows across carriers, personas, and markets — extracting premiums, excess levels, and bundling structures automatically.
The problem
Competitor premiums depend on age, location, coverage level, and claims history. They're generated dynamically at the end of a quote journey — not published on any page Radar can read. You have to fill in the forms to see the numbers.
Competitor premiums are only revealed at the end of a quote flow
Manual quote collection doesn't scale across multiple carriers and personas
Pricing changes go undetected between quarterly benchmarking exercises
Bundling structures and excess options vary in ways that are hard to compare systematically
How Jsonify works
Extract
Collect from quote flows
Automatically fill competitor quote journeys as a defined persona — navigating every step, field, and option.
Structure
Normalized premium datasets
Extract premiums, excess levels, coverage tiers, and bundle options into a consistent, comparable structure.
Insights
Competitive pricing intelligence
Compare how each carrier prices for each persona — and how that changes over time.
Coverage
Personal lines
Home, auto & life insurance
Simulate quote flows for motor, home, life, and health insurance across carriers and customer profiles.
Commercial lines
SME & business insurance
Benchmark pricing for business insurance, liability, and professional indemnity across commercial carriers.
What we track
Every pricing signal that only becomes visible at the end of a real customer quote journey.
Premium pricing
Extract the exact monthly and annual premium offered to each persona — including introductory rates.
Excess structures
Track mandatory and optional excess levels offered by each carrier for each persona and coverage type.
Coverage tiers
Understand how carriers structure basic, standard, and comprehensive coverage and what each tier includes.
Bundle add-ons
Identify what optional extras carriers offer — breakdown cover, legal protection, no-claims protection — and at what price.
Discount logic
Detect how pricing varies by multi-policy discounts, renewal incentives, and loyalty pricing across carriers.
Persona comparison
Run the same quote across hundreds of personas — different ages, locations, and risk profiles — to map pricing logic.
Example deployment
8
Countries
40+
Carriers
200
Personas
Weekly
Refresh cycle
What your team receives
Persona pricing table (carrier × persona × premium × excess)
Coverage structure comparison
Offer change alerts
Premium trend dataset (time series)
Bundling and add-on analysis
Use cases
Actuarial: systematic competitor premium benchmarking at scale
Pricing strategy: detect competitor repositioning before renewal season
Product: understand how competitors structure coverage tiers and add-ons
Market entry: map pricing across a new market before launch
Compliance: track how pricing changes across regulated products over time
Preview a live insurance benchmark — simulated across 8 countries and 40 carriers.