Structured review data from Capterra covering 40,000+ business software products. Every record includes ratings, full review text, pros and cons, reviewer details, and dates — built for product teams, analysts, and sales intelligence workflows.
Track competitor ratings and review sentiment across Capterra. Identify feature gaps and positioning opportunities from real user feedback.
Aggregate and compare reviews across software categories to support procurement, vendor selection, or market entry decisions.
Extract structured themes from thousands of user reviews to understand what drives satisfaction and churn in specific software segments.
Identify businesses actively evaluating software in your category as a signal for targeted outreach.
Understand the competitive landscape of any software category — who the players are, how they're rated, and what users say.
Compare your product's Capterra performance against competitors on ratings, review volume, and specific feature feedback.
Every record is structured and ready to join against your CRM, data warehouse, or enrichment pipeline.
| Field | Type | Description | Coverage |
|---|---|---|---|
| review_id | string | Unique review identifier | 100% |
| product_name | string | Name of the reviewed software | 99%+ |
| product_category | string | Capterra software category | 95%+ |
| product_url | string | Capterra product page URL | 99%+ |
| review_rating | float | Overall star rating out of 5 | 99%+ |
| review_title | string | Review headline from user | 90%+ |
| review_text | string | Full review body text | 88%+ |
| pros | string | What the reviewer liked | 85%+ |
| cons | string | What the reviewer disliked | 83%+ |
| review_date | date | Date review was submitted | 97%+ |
| reviewer_name | string | Reviewer display name | 88%+ |
| reviewer_profile | string | Reviewer profile info where available | 60%+ |
| author_companysize | string | Company size of the reviewer | 97%+ |
| author_image_url | string | Reviewer's profile image URL | 0.1%+ |
| author_industry | string | Industry of the reviewer | 90%+ |
| author_likehood_recommend | float number | Likelihood to recommend the product | 90%+ |
| author_name | string | Name of the reviewer | 99%+ |
| author_previous_product | string | Previously used product | 6%+ |
| author_role | string | Job role of the reviewer | 80%+ |
| author_switching_reason | string | Reason for switching products | 10%+ |
| author_verified_linkedin | string | Verified LinkedIn profile status | 0.2%+ |
| product_description | string | Description of the product | 100.0% |
| product_review_count | string | Total number of product reviews | 99%+ |
| reviewer_source | string | Source of the review | 0.6%+ |
| review_url | string | URL of the original review | 100.0% |
Coverage = percentage of records with that field populated. Download sample to inspect full schema →
We work around your infrastructure, not the other way around.
Complete records as a bulk file in your preferred format.
Filtered by any field in the schema.
Weekly or monthly delta updates.
Real-time access against specific identifiers.
Delivered in whatever format your pipeline accepts.
Flat file for Excel, Python, or any data tool.
Nested records for databases or pipelines.
Direct drop into your cloud storage or warehouse.
Download a free sample or talk to us about a custom subset for your use case.
