We extract software categories, pricing tiers, feature lists, vendor details, and user review corpora from Capterra. 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 Software Listings objects from capterra.com. All fields typed and schema-versioned.
"product_id": "135002", "name": "Salesforce Sales Cloud", "vendor": "Salesforce", "category": "CRM Software", "overall_rating": 4.4, "review_count": 18241, "starting_price": 25.0, "free_trial": true, "deployment_type": "['Cloud', 'SaaS', 'Web-Based']"
| # | product_id | name | vendor | category | sub_category | overall_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from capterra.com. All fields typed and schema-versioned.
"review_id": "REV-948271", "product_id": "135002", "reviewer_role": "Director of Sales", "company_size": "51-200 employees", "overall_rating": 5, "ease_of_use": 4, "pros": "Highly customisable reporting engine.", "cons": "Steep learning curve for new reps.", "review_date": "2026-02-14"
| # | review_id | product_id | reviewer_name | reviewer_role | company_size | industry |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Plans objects from capterra.com. All fields typed and schema-versioned.
"product_id": "135002", "plan_name": "Professional", "price": 80.0, "currency": "USD", "billing_cycle": "per user/month, billed annually", "contact_for_pricing": false, "feature_list": "['Lead Registration', 'Rules-Based Lead Scoring']"
| # | product_id | plan_name | price | currency | billing_cycle | user_limit |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Feature Matrices objects from capterra.com. All fields typed and schema-versioned.
"product_id": "135002", "category": "CRM Software", "feature_name": "Pipeline Management", "is_supported": true, "add_on_required": false, "scraped_at": "2026-05-12T10:14:00Z"
| # | product_id | category | feature_name | is_supported | add_on_required | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Vendor Profiles objects from capterra.com. All fields typed and schema-versioned.
"vendor_id": "V-1029", "vendor_name": "Salesforce", "website": "https://www.salesforce.com", "hq_location": "San Francisco, CA", "year_founded": 1999, "total_products": 14, "verified_vendor": true
| # | vendor_id | vendor_name | website | hq_location | year_founded | employee_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our Capterra scraper navigates complex directory structures, lazy-loaded review paginations, and strict anti-bot measures to deliver structured competitive intelligence.
Extract product names, descriptions, deployment types, support options, and training modalities across all 900+ Capterra categories.
Capture full text pros and cons, sub-ratings (ease of use, value for money), reviewer demographics, and company size data.
Extract starting prices, billing cycles, free trial availability, and detailed plan matrices where published.
Scrape category-specific feature checklists to build comprehensive product comparison databases.
Extract vendor details, headquarters, founding year, and portfolio of associated software products.
Capture the 'Alternatives to X' lists to map out competitor graphs and market positioning.
Map how products are classified across primary and secondary software categories.
Identify whether tools support desktop, mobile, cloud, or on-premise deployments, plus API availability.
Run one-off bulk exports or configure continuous pipelines at weekly or monthly cadences with change-detection.
Brief in. Clean data out.
Provide category URLs, specific software profiles, or vendor names. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for capterra.com.
Schema validation, null-rate checks, and sample review datasets before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Capterra protects its directory with aggressive bot mitigation. Here is how we maintain data flow without interruption.
Capterra employs strict Cloudflare protections. Our crawlers use residential ISP proxies combined with Playwright stealth plugins to generate valid browser fingerprints and solve JavaScript challenges automatically.
Reviews and feature matrices are loaded dynamically via XHR requests. We run full Playwright browser sessions to trigger lazy-loads and intercept the underlying API payloads for clean data extraction.
Premium vendor profiles often feature different layouts than standard listings. Our selector strategy uses multiple fallback chains to ensure data extraction succeeds regardless of the profile tier.
Top products have thousands of reviews spanning hundreds of pages. We manage stateful pagination traversal, ensuring complete corpus extraction without dropping records or triggering rate limits.
For ongoing competitor tracking, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
SaaS companies track competitor feature additions, pricing changes, and market positioning across specific categories.
Product marketing teams analyse pricing models, tiers, and free-trial availability to optimise their own pricing structures.
Product managers scrape feature matrices to identify missing capabilities in their own software compared to category leaders.
Data science teams process review text, pros, and cons to identify common user pain points and feature requests.
Sales teams identify companies using specific software stacks based on reviewer demographics and industry data.
Private equity firms evaluate software category growth, review velocity, and vendor saturation to identify acquisition targets.
"Capterra holds the definitive graph of B2B software features, pricing models, and user sentiment — but extracting it requires navigating aggressive anti-bot protections."
Most teams underestimate the investment required: reliable Capterra scraping requires bypassing Cloudflare turnstiles, full JavaScript rendering for lazy-loaded reviews, and daily selector maintenance to handle layout variations. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our capterra.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across US/UK/EU regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About capterra.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available directory and review information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated software, pricing, and review data. We do not extract personal data beyond public reviewer names, circumvent authentication walls, or access gated vendor dashboards.
We use residential ISP proxies, full Playwright browser sessions with stealth modifications, and automated solver integrations. This allows our crawlers to generate valid browser fingerprints and pass JavaScript challenges consistently.
Yes. We extract the complete text for pros, cons, and overall comments, along with categorical ratings like 'Ease of Use' and 'Customer Service', reviewer demographics, and the date of submission.
Full category refreshes can be configured at weekly or monthly cadences. For targeted competitor monitoring (e.g., tracking 50 specific software products), we can run daily pipelines to capture new reviews and pricing changes instantly.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series record for pricing tiers, allowing you to track when competitors alter their pricing models or feature inclusions.
Our minimum engagements typically start with a defined set of categories or a list of specific software profiles. Contact us with your target scope (e.g., all CRM and Marketing Automation tools) for a precise quote.
Absolutely. We provide a sample run of up to 50 software profiles and their associated reviews as part of the pre-engagement scoping process — so you can validate schema fit and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off software category dump or a continuous review-monitoring feed across 10K products — we scope, build, and operate the pipeline. Tell us what you need.
