Software Reviews Scraper: Capterra, GetApp, Software Advice, G2

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Reads software reviews from the review pool Capterra, GetApp and Software Advice share (one pool: each review is published on all three, so it is read once), by product or by Capterra category, newest first (G2's feed only roughly so), filtered by star rating and date, each walk checked against the site's own count. Also reads G2's newest reviews per product.

Unofficial; not affiliated with Capterra, GetApp, Software Advice, Gartner or G2. We never log in.

Input

Field	What it does
products	Capterra product URLs (https://www.capterra.com/p/135003/Slack/): the shared pool's reviews. G2 product URLs (https://www.g2.com/products/slack/reviews): G2's newest reviews. A GetApp or Software Advice URL gets a free row asking for the Capterra URL (the same reviews)
categories	Capterra category URLs (https://www.capterra.com/team-communication-software/): the listed products in the site's order, up to maxProductsPerCategory (default 20)
ratings	Star ratings, e.g. ["1","2","3"]. Capterra: each star read separately, checked against the site's count for that star. G2: applied here (its feed has no filter; a half star counts to the star below)
since	Reviews written on or after this day (YYYY-MM-DD)
maxReviewsPerProduct	Default 100, per star when stars are selected; in change-only mode, reviews an earlier run read do not count. Each run starts from the newest review: reviews past the cap that a run did not read are not read later (raise the cap to read further back)
maxReviewsTotal	Default 1,000 for the run
includeProfiles	Default on: one row per Capterra product (rating, review count, the four sub-ratings)
personalData	Default off: reviewer name, job title, LinkedIn verification. Company size, industry and time used are always included
onlyNewSinceLastRun, stateName	Per feed, remember what each product and star has read; the next run delivers only what is new, plus any part an interrupted run left unread. If the memory cannot be read, the run stops with a free state-read-failed row

Recipe, the research use: the 1 to 3 star reviews of the top team-chat tools, with switching reasons.

{ "categories": ["https://www.capterra.com/team-communication-software/"], "ratings": ["1", "2", "3"], "maxReviewsPerProduct": 200 }

Output rows

• review: source (capterra or g2), originSite (where it was written: Capterra, GetApp, SoftwareAdvice, G2), productId, productName, reviewId, reviewUrl (Capterra has no per-review link: the reviews page), rating, the four sub-ratings and recommendationRating (0-10), title, text, pros, cons, adviceToOthers, switchingReasons and switchedFrom, chosenReasons and alternativesConsidered, date (a day for Capterra, a time for G2), incentive and reviewSource (the site's incentive label and wording), companySize, industry, timeUsedProduct, reviewerRole (G2's stated role; Capterra's job title only with personalData), reviewerName / reviewerLinkedInVerified (only with personalData), vendorResponse (as given; null when none).
• product: the Capterra profile above.
• coverage (free): one per product and star (Capterra) or per product (G2), with the site's total, what was read, and why it stopped; a free-plan run's row carries a note when its preview ran out.
• error (free): every input, source or run failure, with a stable reason.
• summary (free): one per run, with renderedReads.

How Capterra is read, and what a free plan gets

Capterra's pages are behind Cloudflare, and from Apify's network our own browser does not pass it. The Actor opens each product's reviews page through a paid render service and, inside that page, walks the page's own review list exactly as the page does: 25 reviews a call, newest first or one star at a time. One paid read covers a product's run (up to ~2,000 reviews; more reads continue where it stopped). That service costs the owner per read, so on a free Apify plan this listing reads up to 25 Capterra reviews a month per account, and the coverage row says so; a paid plan reads them all. G2's feed is read directly, free on every plan. Because every Capterra read costs the same whatever it yields, each read that served Capterra data carries a small read fee (the check event), on top of its reviews: usually one per product a run (a product over ~2,000 reviews takes more), and one per category page listed. A read that served nothing (a refused, missing or unreadable page) is free, and a read the cost ceiling (maxCostUsd) cannot pay its fee for is never made.

What it promises, and the test that holds it

Promise	Test
A Capterra walk is finished only at exactly the site's count for its filter; a list that ends short is a free review-count-mismatch row	walk.test.ts "one read walks a star filter to the site's count (48 of 48)", "a list that ends before the count"
A star filter returns only that star; a page that ignored it is a free row, before anything is counted	walk.test.ts "a page that ignored the star filter"; parse.test.ts "a whole 1-star walk"
since returns exactly the reviews written on or after the day	walk.test.ts "since: exactly the reviews written on or after the day"
A walk longer than one read continues from the cursor in the next read	walk.test.ts "a walk that needs more pages than one read gave continues in the next read"
Reviews from Capterra, GetApp and Software Advice come once, each saying where it was written	parse.test.ts "from all three Gartner sites"
Reviewer names and job titles stay out unless asked	walk.test.ts "reviewer names and job titles only with personalData"
A free plan gets the 25-review preview and is told what a paid plan reads; a run without the route says so and reads nothing	walk.test.ts "a free-plan preview stops at its rows", "a run without the render route"
A missing product, a refused read, a site release that hid the review list, an unreadable answer: free rows that say so	walk.test.ts "a release that hid the review action, a refused read, a missing product, an unreadable answer"
G2: the feed's newest 25, the star and date filters applied here, no count claimed	walk.test.ts "G2: the feed's newest 25"; parse.test.ts "the G2 feed"
Change-only: a re-run delivers nothing it already delivered; an interrupted run leaves no gap and sends nothing twice	walk.test.ts "a second run delivers nothing", "a walk the run cut short leaves its gap to the next run"; state.test.ts "a cut walk keeps only what it read and marks a gap"
No row is billed twice; caps and the cost ceiling hold under concurrency; failures are free	billing.test.ts (the Sink contract)

Limits

• G2 without a login shows only its newest reviews and page 1 of anything else; this Actor reads its public feed (the newest 25 per product) and never logs in. Its coverage rows carry no count.
• Capterra gives each review a day, not a time.
• GetApp and Software Advice URLs are not translated to Capterra yet: give the Capterra URL.

Known limits (chosen, not built)

• Capterra can briefly refuse the review call for a product read several times within minutes (measured: three refused reads of one product in 20 minutes while other products read cleanly). The run then writes a free blocked row (no second paid read: it was refused too every time) and a later run reads it.
• A free-plan account's monthly 25-row preview is claimed by a write and a read-back in the account's own store (no atomic lock exists there): two free runs of one account started within the same moment could both claim it, at most doubling that month's preview (shared with every listing's free-plan rule since 2026-10-05).
• Two runs of the same change-only feed at once (overlapping schedules with one stateName) each start from the memory as it was and may both deliver the same new reviews; give each schedule its own stateName, or keep its runs from overlapping.
• Capterra gives days, not times: reviews past the cap that were written on the same day as the newest one a change-only run delivered can come in the next run.
• A slow render service can make one read cost more than its fee covers: typical reads take 7-36 s, and a read near the 90 s limit (or a retried one) on the Hobby plan falls below 85%; the owner's cost, never the buyer's.
• A read's fee is charged before its rows are written: if the dataset then refuses them, the fee stays charged.
• On a migration or abort the memory is saved after the walks in progress stop (the save waits up to 5 s for them); a walk still waiting on a slow page after that is saved as unread and its rows may come again next run.
• Change-only memory records each walk when it ends, and is saved once a minute, on migration and abort, and at the end. A hard crash with no warning (no migration or abort event) loses the memory of walks still in progress and of up to the last minute, and a final save that fails three times loses that run's part: the next run may then deliver, and bill, those rows again (the second case says so in a free state-save-failed row). Checkpointing every page and a write-ahead protocol were weighed and not built: platform migrations and aborts are announced and saved first, and no unannounced crash was seen in any run.

Build evidence: docs/BUILD-REPORT.md. Measured source facts: spike/NOTES.md.

Use it from n8n, MCP, the API or a schedule

Built to be called by a workflow, not only from the Store form. The Actor is vonsensey/software-reviews-scraper; every snippet below sends {}, which runs the defaults shown on the form — replace it with your own input.

n8n

Install the Apify community node (@apify/n8n-nodes-apify under Settings → Community Nodes, or search "Apify" on n8n Cloud). Add Apify → Run Actor with Actor vonsensey/software-reviews-scraper and your input JSON, then Apify → Get Dataset Items on the run's defaultDatasetId and pipe the rows anywhere. For scheduled runs, the On new Apify Event trigger fires when a run of this Actor finishes.

MCP (Claude, Cursor, VS Code, any MCP client)

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=vonsensey/software-reviews-scraper",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

Your agent then calls vonsensey/software-reviews-scraper as a tool with the same input the form takes and reads the dataset back.

REST API (one call, rows in the response)

curl -X POST "https://api.apify.com/v2/acts/vonsensey~software-reviews-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" -d '{}'

Python

from apify_client import ApifyClient
client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("vonsensey/software-reviews-scraper").call(run_input={})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row)

JavaScript

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('vonsensey/software-reviews-scraper').call({});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Make, Zapier, LangChain, CrewAI

The Apify app in Make and Zapier has a Run an Actor module: pick vonsensey/software-reviews-scraper. In LangChain and CrewAI the Apify tool wrappers take the same Actor id. A daily schedule needs nothing but the Console: Schedules → Create → this Actor → cron, and the dataset fills on its own.

Use cases

• Find out why buyers leave a competitor. Read the 1 to 3 star reviews of a category's top products: every row carries pros, cons, the reviewer's switching reasons and the product they switched from.
• Watch the new reviews of your own product. Turn on onlyNewSinceLastRun and schedule it: each run delivers only the Capterra and G2 reviews it has not delivered before, plus any part an interrupted run left unread.
• Benchmark a software category. Give a Capterra category URL and get its listed products in the site's order, each with a profile row: rating, review count and the four sub-ratings.
• Build a review dataset you can trust. Every Capterra walk is checked against the site's own count for its filter; a list that ends short is a free review-count-mismatch row, never a silent gap.
• Segment feedback by buyer. Company size, industry and time used come on every review; reviewer names and job titles only when you turn on personalData.

Run it on a schedule

A one-off pull answers a question; a schedule answers it every day without you. Open Schedules in the Apify Console, point a cron at this Actor, and the dataset keeps filling on its own — no server, no cron box, no babysitting. Everything here is built to be re-run: you are billed per review delivered, and the FAQ below says exactly what a scheduled run that finds nothing new costs.

FAQ

Do GetApp and Software Advice reviews come too?

Yes. Capterra, GetApp and Software Advice publish one shared review pool, so each review comes once, with originSite saying where it was written. Give the Capterra URL: a GetApp or Software Advice URL gets a free row asking for it.

How much of G2 does it read?

G2's public feed: the newest 25 reviews per product, with the star and date filters applied here and no count claimed. Without a login G2 shows only its newest reviews, and this Actor never logs in.

What does a scheduled run that finds nothing new cost?

On G2, nothing: there is no start fee and reviews are billed only when delivered. On Capterra, each read that served Capterra data carries a small read fee (the check event), usually one per product a run, whether or not a review is new. A read that served nothing is free, and a read the cost ceiling (maxCostUsd) cannot pay for is never made.

What does a free Apify plan get?

G2's feed on every plan, and up to 25 Capterra reviews a month per account; the coverage row says when the preview ran out. A paid plan reads them all.

Am I billed for failures?

No. A missing product, a refused read, a page that hid the review list or an unreadable answer is a free row with a stable reason, and no row is billed twice.

Is this an official Capterra, Gartner or G2 product?

No. Unofficial: not affiliated with Capterra, GetApp, Software Advice, Gartner or G2. It reads public review pages and never logs in.

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Something wrong, or a field you need that is missing? Open an issue on the Issues tab — it is read and it gets fixed. If this saved you time, a rating on the Store page helps the next person find it.