Capterra Reviews API — Software Review Data
When reviews are what you are after — not the profile wrapped around them — this source returns the review listing for a product as structured data.
- You send
- A Capterra product reviews URL
- You get back
- The product's reviews
- Coverage
- Software products with public reviews.
- Price
- 5 pts — $5 per 1,000
- Charged only when the listing resolves. A page that returns nothing is not billed.
Ways to get this data
Three approaches teams use today, and where each one runs into trouble.
| Approach | What it takes | Cost | Trade-off |
|---|---|---|---|
| Copying reviews by hand | Read and paste, page after page | Free, and painfully slow | Nobody sustains this past the first hundred |
| Building a scraper | Write it, host it, handle pagination, repair it after layout changes | Engineering time | Ongoing maintenance for a one-off research question |
| NeuralVerge | One request | $5 per 1,000, misses not billed | Returns what the listing publishes at the time you ask |
What you get back
Every field the response returns.
| Field | Type | Description |
|---|---|---|
reviews | array | Every review on the listing page. |
reviews[].author | string | Who wrote it. |
reviews[].rating | number | The rating they gave. |
reviews[].title | string | Review headline. |
reviews[].content | string | Full review text. |
Every source answers in the same shape: a session id, a readable human summary, a structured machine object and the points the call consumed. Learn it once and it holds across every source in the catalog.
How to run it
The same lookup works from the app, the API, or as a tool an agent can call mid-task.
A JSON schema passed as extract_schema_json pins the response shape, so the same fields come back on every call. The Get API Code button in the app gives you the complete command with the schema already filled in.
curl -X POST https://api.neuralverge.ai/functions/v1/run-extract \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"url": "https://www.capterra.com/p/000000/Example/reviews/",
"instructions": "Extract data from Capterra reviews",
"settings": {
"country_code": "us",
"extract_schema_json": "{ ... }"
}
}'What teams use it for
Where this field shows up in an actual workflow.
Extract the themes buyers raise repeatedly, in their own words.
Find the complaint that shows up again and again, and build against it.
Let requests that recur across a category inform your roadmap.
Know what a prospect has already read about the alternative.
Coverage, freshness and limits
What this source covers, how fresh it is, and where it stops.
Software products with public reviews.
Read at request time.
Reviews are published by their authors and returned as they appear, with the source URL and a session id.
- —Reviewers are self-selected, so the distribution is not a survey.
- —Vendors run campaigns to collect reviews, which shapes both volume and timing.
- —A product with few reviews returns few reviews.
Questions, answered
What the listing exposes for that product at the time of the request. Products with long review histories return more than new ones.
Related sources
Try capterra reviews on your own data
One request format across every source in the catalog.