We extract agent directories, coverage details, localised policy options, and public quote parameters from State Farm. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Agent Directory objects from statefarm.com. All fields typed and schema-versioned.
"agent_id": "SF-8492-TX", "name": "Sarah Jenkins", "city": "Austin", "state": "TX", "zip_code": "78701", "languages": "['English', 'Spanish']", "license_number": "TX-1928471"
| # | agent_id | name | address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Coverage Options objects from statefarm.com. All fields typed and schema-versioned.
"coverage_id": "COV-COMP-01", "name": "Comprehensive Coverage", "category": "Auto", "state_availability": "['All 50 States']", "deductibles": "[0, 100, 250, 500, 1000]", "related_discounts": "['Drive Safe & Save', 'Multi-Vehicle']"
| # | coverage_id | name | category | description | state_availability | limits |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Quote Parameters objects from statefarm.com. All fields typed and schema-versioned.
"vehicle_make": "Toyota", "vehicle_model": "Camry", "vehicle_year": 2022, "driver_age_bracket": "35-44", "zip_code": "78701", "quote_timestamp": "2026-05-12T10:14:00Z"
| # | vehicle_make | vehicle_model | vehicle_year | driver_age_bracket | zip_code | base_premium_estimate |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Office Locations objects from statefarm.com. All fields typed and schema-versioned.
"office_id": "LOC-9921", "agent_name": "Sarah Jenkins", "latitude": 30.2672, "longitude": -97.7431, "operating_hours": "Mon-Fri 9AM-5PM", "services_offered": "['Auto', 'Home', 'Life', 'Renters']"
| # | office_id | agent_name | street_address | latitude | longitude | operating_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Discount Programs objects from statefarm.com. All fields typed and schema-versioned.
"discount_id": "DISC-DSS-01", "name": "Drive Safe & Save", "category": "Auto", "eligibility_criteria": "Requires telematics app installation", "average_savings_pct": 30, "state_restrictions": "['CA', 'MA', 'RI']"
| # | discount_id | name | category | description | eligibility_criteria | average_savings_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our State Farm scraper navigates zip-code localisation, multi-step quote flows, and agent directory pagination — with JavaScript rendering and anti-bot circumvention built in.
Name, contact details, licensing, languages spoken, and office locations scraped across all 50 states.
Extract policy options, deductibles, and limits specific to individual zip codes and state regulations.
Map the dropdown parameters State Farm uses to classify vehicle makes, models, and driver demographics.
Capture eligibility criteria and state-level availability for programs like Drive Safe & Save and Steer Clear.
Navigate public, non-authenticated quote generation steps to extract baseline premium estimates based on standard inputs.
Extract latitude, longitude, and operating hours for every State Farm agency location nationwide.
Scrape the Simple Insights blog and public FAQ sections for NLP training and content analysis.
Run bulk agent directory exports or configure continuous pipelines at monthly or weekly intervals.
Bypass Akamai and Datadome protections using residential proxies and human-like interaction patterns.
Brief in. Clean data out.
Provide target zip codes, states, or specific quote parameters. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for statefarm.com.
Schema validation, null-rate checks, and geographical coverage verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Insurance carriers employ strict bot mitigation and heavily localised content. Here is how our pipeline maintains stability.
State Farm uses advanced bot protection (like Akamai) to block scraping. Our crawlers use US residential ISP proxies, realistic browser fingerprints, and randomised request timing to maintain access without triggering rate limits.
Insurance coverage and pricing are hyper-local. We manage persistent sessions tied to specific zip codes, allowing us to extract state-specific policy details and accurate agent assignments without session bleed.
Extracting quote parameters requires navigating complex, multi-step JavaScript forms. We use Playwright to orchestrate these flows, handling asynchronous validations and dynamic DOM updates reliably.
For agent directories, we maintain a hash index of last-seen values per agent. Subsequent runs only push diffs — tracking new agent licenses, office relocations, or retirements without redundant data transfer.
If a state's regulatory changes alter the site structure, our observability stack flags schema drift immediately. We alert on null-rate spikes and adapt selectors before your downstream processes fail.
Rival carriers monitor State Farm's localised coverage options, discount structures, and public quote parameters to benchmark their own products.
Insurtech firms and recruiters track the growth, density, and specialisations of State Farm's captive agent network across different states.
Actuaries and product managers analyse coverage availability by zip code to identify underserved markets or regulatory shifts.
Aggregators extract baseline quote parameters to map out generic pricing tiers for specific driver and vehicle cohorts.
Commercial real estate analysts map State Farm office locations and operating hours to understand retail footprint density.
AI companies scrape the Simple Insights blog and FAQ sections to train insurance-specific large language models.
"Insurance pricing and coverage data is heavily siloed behind zip codes and dynamic forms. Extracting it requires session persistence and geographical precision."
Mapping an insurance carrier's public footprint involves navigating enterprise bot protection and multi-step validation flows. DataFlirt manages the proxy rotation, JavaScript execution, and stateful sessions required to extract reliable agent and coverage data, allowing your team to focus entirely on market analysis.
Everything supported by our statefarm.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright manages the complex JavaScript interactions and multi-step forms required for insurance quote flows.
We route requests through high-quality US residential IPs, ensuring requests appear as legitimate domestic traffic to bypass enterprise bot mitigation.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management, ensuring reliable delivery of agent and coverage datasets.
Data delivered to where your team already works — no new tooling required.
About statefarm.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information, such as agent directories and public policy descriptions, is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal policyholder data, circumvent authentication walls, or scrape private claims history. Clients should consult legal counsel for their specific use cases.
We maintain stateful browser sessions tied to specific zip codes. This allows us to extract the precise coverage options, deductibles, and agent assignments relevant to that specific geographical area without session bleed.
We can extract baseline premium estimates generated through public, non-authenticated quote flows based on standard input parameters (e.g., standard vehicle, standard age bracket). We cannot extract personalised premiums that require a social security number or hard credit check.
Agent directories can be extracted on a weekly or monthly cadence. Our change-detection system ensures you only receive updates for new agents, relocations, or license changes, minimising processing overhead.
Yes. We build custom pipelines for various national and regional carriers, allowing you to standardise agent and coverage data across multiple sources into a unified schema.
Our minimum engagements typically start with a defined geographical scope (e.g., specific states or a set of 500 zip codes) for agent or coverage extraction. Contact us to scope your specific data requirements.
Insurance sites use strict WAFs. We utilise premium US residential proxies, realistic browser fingerprinting via Playwright, and human-like interaction delays to maintain stable extraction rates.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete agent directory map or continuous tracking of localised coverage options — we scope, build, and operate the pipeline. Tell us what you need.
