# Capterra Reviews Scraper (`usestring/capterra-reviews`) Actor

Collect 25 Capterra reviews per software product - overall rating, three sub-ratings, pros and cons.

- **URL**: https://apify.com/usestring/capterra-reviews.md
- **Developed by:** [String](https://apify.com/usestring) (community)
- **Categories:** Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.75 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Capterra Reviews Scraper — four sub-ratings per review

This Actor scrapes Capterra software reviews. Give it a Capterra product reference such as
`135003-Slack` and the Capterra Reviews Scraper returns **25 reviews** for that product with the
overall rating **and the three sub-ratings Capterra collects separately** — ease of use, customer
service and value for money — plus pros and cons as two fields.

No Capterra account, login or cookies are used — this reads what a logged-out visitor sees. Measured
at **25 reviews per product, one Capterra request each**.

### What it returns

| Field | Type | Notes |
| --- | --- | --- |
| `reviewId` | string | Capterra's own review ID — use it to de-duplicate |
| `productSlug` | string | The product slug from the reference given, e.g. `Slack` |
| `productName` | string | Capterra's display name, e.g. `monday.com` — the slug cannot reproduce it |
| `title` | string | The review headline |
| `rating` | number | Overall stars out of 5 |
| `easeOfUse` | number | Ease-of-use sub-rating out of 5 |
| `customerService` | number | Customer-service sub-rating out of 5 |
| `valueForMoney` | number | Value-for-money sub-rating out of 5 |
| `pros` | string | The reviewer's Pros text |
| `cons` | string | The reviewer's Cons text |
| `reviewerName` | string | As published by Capterra |
| `reviewerRole` | string | The reviewer's job title |
| `companySize` | string | Employee band as Capterra states it, e.g. `11-50 employees` |
| `industry` | string | The reviewer's industry |
| `publishedAt` | string | Review date normalised to `YYYY-MM-DD` |
| `sourceUrl`, `collectedAt` | string | Provenance for every row |

A sub-rating the reviewer did not score comes back empty rather than as `0`, because Capterra's own
scale starts at 1 and uses zero as its "not rated" sentinel.

### Input

```json
{ "products": ["135003-Slack", "147657-monday-com"], "maxItems": 1000 }
```

| Field | Description |
| --- | --- |
| `products` | Capterra product references — see the format below. Required, 1–100. |
| `maxItems` | Cap on dataset items. Default 1000. Free plans stop at 250 requests and 250 results — see below. |
| `concurrency` | Products fetched in parallel. Default 2, maximum 5. |

**A Capterra product is addressed by numeric ID *and* name slug together — a bare product name does
not resolve.** Slack is `135003-Slack`, not `slack`. Open the product on Capterra and read both parts
out of the URL: `https://www.capterra.com/p/135003/Slack/reviews/` gives the ID `135003` and the slug
`Slack`. All of these forms are accepted and resolve to the same fetch:

- `135003-Slack`
- `135003/Slack`
- `p/135003/Slack`
- `https://www.capterra.com/p/135003/Slack/`
- `https://www.capterra.com/p/135003/Slack/reviews/`

A reference missing either half, and any URL on a host other than `capterra.com`, is rejected and
reported as a failed target instead of aborting the run.

### Use cases

- Competitor monitoring across a software category, with sub-ratings not just an overall score
- Finding where a rival scores well on ease of use but badly on value for money
- Pulling verbatim pros and cons into win/loss research and battlecards
- Segmenting feedback by `companySize` and `industry` before a positioning change
- Tracking your own product's review sentiment over time on a schedule

### Reliability

Reviews are read from the page state Capterra's own React app hydrates from, which is the only source
on the page carrying the per-review sub-ratings, pros and cons, and reviewer attributes as values.
The rendered review cards show every number as a star widget, and Capterra's schema.org block lists
the same 25 reviews with author, title and overall rating only.

A product that cannot be read is recorded in the run's `SUMMARY` under `failures` rather than
silently returning fewer rows, and a run where every product failed exits with an error.

There are no retries by design: the String Unblocker owns proxy rotation and anti-bot solver
selection, so a retry loop here would only re-roll the same block.

### Frequently asked questions

**How do I find the right Capterra product identifier?** Open the product's Capterra page and take
both parts of the URL. `https://www.capterra.com/p/135003/Slack/reviews/` becomes `135003-Slack`. The
numeric ID alone or the name alone will not reach a page.

**How many Capterra reviews does it return per product?** 25 — one Capterra request per product. Ten
products therefore return roughly 250 rows.

**Does it page through every review on a product?** No. The Capterra Reviews Scraper reads the first
page of reviews only, so it does not return a product's full review history.

**Do I need a Capterra account, API key or cookies?** No. Only the public, logged-out review page is
read.

**Does it return the individual sub-ratings?** Yes — `easeOfUse`, `customerService` and
`valueForMoney` come back as separate numbers alongside the overall `rating`.

**Is there a link to each individual review?** No. Capterra publishes no per-review permalink; a
`/reviews/<id>/` URL redirects back to the product page, so no review URL is emitted. Use
`sourceUrl` for the product's review page and `reviewId` to key a row.

### Limitations

One page of reviews per product — this is not a full review-history crawler, and there is no date,
rating or sort filter. No product-level fields (pricing, feature lists, alternatives, overall score)
and no per-review permalink are collected. Only `capterra.com` URLs are accepted.

### Free plan limit

Runs started from an Apify **free plan** stop at **250 requests and 250 results**, and the run
reports that it reached the limit. Any paid plan runs the full input and `maxItems` you set.

The limit exists because this Actor fetches through our own infrastructure, which Apify does not
cover for free-plan runs. It binds on requests as well as results so that a large input list cannot
spend those fetches for rows the run will not return.

# Actor input Schema

## `products` (type: `array`):

Capterra addresses a product by numeric ID and name slug together, so a bare product name does not resolve. Use 135003-Slack, 135003/Slack, p/135003/Slack or a full https://www.capterra.com/p/135003/Slack/reviews/ URL - both halves come from the product's own Capterra URL.

## `maxItems` (type: `integer`):

Global cap on dataset items. Runs started from an Apify free plan stop at 250 requests and 250 results; any paid plan runs the full amount.

## `concurrency` (type: `integer`):

Targets fetched in parallel.

## Actor input object example

```json
{
  "products": [
    "135003-Slack"
  ],
  "maxItems": 1000,
  "concurrency": 2
}
```

# Actor output Schema

## `results` (type: `string`):

Collect 25 Capterra reviews per software product - overall rating, three sub-ratings, pros and cons.

## `summary` (type: `string`):

Item count, failure count and every target that failed, with its error.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "products": [
        "135003-Slack"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("usestring/capterra-reviews").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "products": ["135003-Slack"] }

# Run the Actor and wait for it to finish
run = client.actor("usestring/capterra-reviews").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "products": [
    "135003-Slack"
  ]
}' |
apify call usestring/capterra-reviews --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,usestring/capterra-reviews"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/awiWBhMjvuLU22wFN/builds/4SgKZ7tSeYGmEHfdL/openapi.json