We extract agent directories, branch locations, coverage specifications, and quote engine outputs from Liberty Mutual. 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 libertymutual.com. All fields typed and schema-versioned.
"agent_id": "LM-84921", "first_name": "Sarah", "last_name": "Jenkins", "title": "Lead Sales Representative", "phone_number": "617-555-0198", "city": "Boston", "state": "MA", "languages_spoken": "['English', 'Spanish']"
| # | agent_id | first_name | last_name | title | phone_number | email_address |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Branch Locations objects from libertymutual.com. All fields typed and schema-versioned.
"branch_id": "BR-0421", "branch_name": "Liberty Mutual - Downtown Boston", "street_address": "175 Berkeley St", "city": "Boston", "state": "MA", "hours_monday": "09:00-17:00", "latitude": 42.3496, "longitude": -71.0736
| # | branch_id | branch_name | street_address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Coverage Details objects from libertymutual.com. All fields typed and schema-versioned.
"coverage_type": "Better Car Replacement", "category": "Auto", "state_availability": "['MA', 'NY', 'CT', 'RI']", "discount_eligibility": "['Multi-Policy', 'Safe Driver']", "minimum_limits": "State Minimum", "description": "Replaces your totaled car with a model that is one year newer."
| # | coverage_type | category | state_availability | base_features | optional_add_ons | discount_eligibility |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Quote Output objects from libertymutual.com. All fields typed and schema-versioned.
"zip_code": "02116", "vehicle_year": 2022, "vehicle_make": "Toyota", "vehicle_model": "Camry", "driver_age": 34, "quoted_premium_monthly": 142.5, "liability_limit": "100/300/100", "applied_discounts": "['Paperless', 'Anti-Theft']"
| # | quote_id | zip_code | vehicle_year | vehicle_make | vehicle_model | driver_age |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Career Listings objects from libertymutual.com. All fields typed and schema-versioned.
"job_id": "REQ-99214", "title": "Senior Actuarial Analyst", "department": "Global Retail Markets", "location": "Boston, MA", "remote_eligible": true, "posted_date": "2026-05-10", "salary_min": 115000, "salary_max": 145000
| # | job_id | title | department | location | remote_eligible | posted_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our infrastructure handles the heavy lifting of insurance scraping: stateful multi-step form execution, WAF circumvention, and geo-targeted proxy routing to extract accurate, state-level pricing and agent data.
Extract names, contact information, office locations, and licensed states for every registered Liberty Mutual agent nationwide.
Navigate complex, JavaScript-heavy quote engines for auto and home insurance based on predefined input matrices.
Capture geocoded coordinates, operating hours, and service availability for all physical retail locations.
Extract coverage descriptions, limits, and optional add-ons, mapped by state availability and product category.
Monitor advertised discounts, multi-policy bundle rates, and telematics program requirements across different zip codes.
Handle strict geo-IP redirects and zip code logic using state-specific residential proxy nodes to ensure accurate regional data.
Bypass strict insurance WAFs and rate limits using realistic browser fingerprints and automated CAPTCHA solving.
Manage dynamic DOM changes and JavaScript-based form validation errors during automated quote runs.
Run daily agent directory syncs or configure continuous pipeline runs for competitor rate monitoring.
Brief in. Clean data out.
Provide zip code lists, vehicle matrices, or directory targets. We design the extraction schema together.
We configure Playwright scripts, state-level proxy rotation, and form-state management for libertymutual.com.
Schema validation, WAF block-rate checks, and sample quote outputs before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Liberty Mutual protects its quote engines and directories with strict bot mitigation. Here is how we maintain reliable extraction.
Insurance carriers use aggressive WAFs (like Akamai or DataDome). We use residential ISP proxies with realistic TLS and browser fingerprints to blend in with legitimate consumer traffic.
Quote engines are Single Page Applications (SPAs) requiring sequential data entry. We use full Playwright sessions to manage cookies, local storage, and dynamic DOM updates throughout the quote flow.
Insurance pricing and coverage availability are strictly regulated by state. Our proxy rotation engine binds requests to IPs matching the target zip code to prevent regional redirects.
Form fields change based on previous inputs (e.g., adding a specific vehicle year triggers new questions). Our crawlers adapt to these dynamic DOM trees to ensure complete data entry.
Agent directories change slowly. We maintain a hash index of last-seen values per agent, pushing only diffs to reduce your storage bloat and downstream processing load.
Actuarial and pricing teams track base quote changes across specific zip codes and demographic profiles to benchmark market positioning.
Insurtechs and carriers analyze agent density, language capabilities, and branch footprints to identify underserved geographic regions.
Product managers compare optional add-ons, limits, and state-level availability against their own insurance offerings.
Marketing teams monitor promotional bundling offers, telematics program discounts, and affinity group rates.
Compliance officers audit public-facing coverage descriptions and state-specific disclosures for industry analysis.
Recruiting teams track hiring velocity, remote role distribution, and salary bands via career portal scraping.
"Insurance pricing is highly localised and hidden behind complex quote engines. Querying it at scale requires executing thousands of multi-step forms daily."
Extracting data from Liberty Mutual requires navigating strict WAFs, managing stateful multi-step JavaScript forms, and routing requests through state-specific residential IPs. DataFlirt handles the proxy rotation, session management, and DOM parsing so your analysts receive clean, normalised datasets without managing the infrastructure.
Everything supported by our libertymutual.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.
Playwright handles the complex, multi-step JavaScript forms required by quote engines, maintaining session state across dynamic DOM changes and validation checks.
We maintain pools of residential ISP proxies mapped to specific US states, ensuring that region-locked content and pricing engines return accurate local data.
Pipelines run on AWS ECS with Airflow handling scheduling, dependency management, and SLA alerting. All state and input matrices are stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About libertymutual.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information, such as agent directories, branch locations, and public quote engine outputs, is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal customer data, circumvent authentication walls, or scrape private claims history. Clients should review Liberty Mutual's ToS and consult legal counsel for specific use cases.
We use Playwright to execute full browser sessions, programmatically entering data into each step of the form just as a user would. We map your input matrix (e.g., specific vehicle models, driver ages, zip codes) to the required fields and capture the final premium output.
Yes. You provide the input matrix (zip codes, vehicle types, coverage limits), and our pipeline executes the quote flow for those specific parameters, routing the request through a proxy in the matching state.
We use state-targeted residential ISP proxies combined with realistic browser fingerprints and request timing modelled on human behaviour. If a CAPTCHA is presented, our automated solvers clear the challenge to proceed with the extraction.
Yes. We recursively crawl the state and city-level directories to build a complete, normalised dataset of all listed agents, including their contact details and licensed regions.
Agent directories and branch locations are typically refreshed weekly. Quote monitoring pipelines can be scheduled daily or on-demand based on your input matrix volume.
No. We do not support scraping authenticated customer portals, personal policy documents, or private claims data. We only extract data accessible without a user login.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full agent directory extraction or continuous quote monitoring across 5,000 zip codes — we scope, build, and operate the pipeline. Tell us what you need.
