Run a competitor teardown from Capterra software reviews
Get Capterra reviews of any software product as JSON, with pros, cons, sub-ratings, reviewer role and company size, to learn what buyers like and dislike.
When you compete in software, your rivals' customers have already written your positioning for you: what they like, what made them regret buying, which feature they wish existed. Capterra holds those reviews, but only in pages you scroll and read one at a time. Lovely Router fetches them as data. Send a Capterra product link, get one JSON object per review, pay per review from a prepaid balance.
Hand it to your AI agent
Copy this prompt into Claude Code, Cursor, Codex or any coding agent. It tells the agent where the docs are and how to use your API key.
Run a competitor teardown from Capterra software reviews. Use the Lovely Router data tools: each returns JSON and is billed per result.
- Docs (read first): https://lovelyrouter.com/docs/tools/find.md and https://lovelyrouter.com/docs/tools/run.md
- Plan first: POST https://lovelyrouter.com/v1/tools/suggest with `{"task": "<my task in plain words>"}` (free). It returns the tools to run in order, each with an example `input`, the `input_required` fields, an estimated cost and a ready-made `run` request. Replace the example values with my task's; if a field is unclear, read the tool with GET https://lovelyrouter.com/v1/tools/<id>. To browse instead, POST https://lovelyrouter.com/v1/tools/discover searches the catalog.
- Show me the plan and its estimated cost (`total_est_cost_usd`) before running anything large.
- Run: POST https://lovelyrouter.com/v1/tools/<id>/run with `{"input": {...}, "max_results": N}`. A 200 has the finished run with `items`; a 202 means it is still running, so poll the `poll` path until `status` is `succeeded`, `failed`, `timed_out` or `stopped`.
- Only delivered results are billed. Keep max_results small on the first run, check the output, then scale up.
- If you support MCP, connect https://lovelyrouter.com/mcp instead (Streamable HTTP, same key; https://lovelyrouter.com/docs/tools/mcp.md) and use suggest_tools, get_tool and run_tool.
- Auth: read my API key from the LOVELY_API_KEY environment variable and send it as `Authorization: Bearer $LOVELY_API_KEY`. Never print or commit the key. If it is not set, ask me to create one at https://lovelyrouter.com/app/keys.
- Billing is prepaid: every call is charged to my balance, so test with a small request before running anything large.
- Every docs page is plain Markdown; the full index is https://lovelyrouter.com/llms.txt.
My task: <the inputs (links, keywords or accounts) and how many results you need>How it works
List the products to study
Take the Capterra review page of each competitor, and your own product for comparison.
Run the tool with a cap
Send a product link to
POST /v1/tools/capterra-reviews/run. SetmaxResultsin the input andmax_resultsin the request body to the number of reviews you want. The run holds its maximum cost from your balance and returns the reviews as JSON.Turn text into a comparison
Ask a model to tag pros and cons by theme, then count themes per product and per reviewer segment. The table of what each competitor is praised and blamed for is your teardown.
Get Capterra reviews with one request
Get Capterra reviews takes one product page in productUrl. maxResults caps the number of reviews, sort orders them and starRating filters by stars:
curl https://lovelyrouter.com/v1/tools/capterra-reviews/run \
-H "Authorization: Bearer $LOVELY_API_KEY" \
-H "content-type: application/json" \
-d '{
"input": {
"productUrl": "https://www.capterra.com/p/135003/Slack/reviews/",
"maxResults": 5
},
"max_results": 5
}'A run still going after 60 seconds returns 202; Run a tool shows how to poll. sort accepts MOST_RECENT, HIGHEST_COMPLETENESS_SCORE, HIGHEST_RATED and LOWEST_RATED. One run can return up to 500 reviews.
What each review holds
| Field group | What you get |
|---|---|
| Review | Title, date and comments |
| Ratings | Overall rating and sub-ratings |
| Feedback | Pros and cons |
| Reviewer | Role and company size |
Recipes
Pull its lowest-rated reviews with sort set to LOWEST_RATED, read the cons, and list the problems your product already solves.
For each competitor, collect the top praised and top criticized themes, with a customer quote for each, and give them to your sales team.
Count reviewer roles and company sizes per product to see which segment each competitor really serves.
Gather cons across five competitors and look for complaints that show up in most of them. That is an unmet market need.
Run the newest reviews with MOST_RECENT every month and watch if the complaint themes change.
Prefer plain words? Connect the MCP server and tell Claude Code or Cursor: "Fetch the 100 lowest-rated Capterra reviews for this product, group the cons by theme, and give me counts and one quote per theme. Set max_results to 100."
Pair it with other software review sites
Each review site has a different crowd, so a fair teardown reads more than one:
Software reviews from Capterra for a product: title, date, overall and sub-ratings, pros, cons, comments, reviewer role and company size.
G2 reviews of a software product.
B2B software reviews from TrustRadius: heading, rating, date, use cases, pros, cons, likelihood to recommend, feature ratings, reviewer.
Enterprise software reviews from Gartner Peer Insights: headline, summary, rating, date, reviewer role, industry and company size.
Reddit posts for a query or subreddit: title, body, score, comments count, author, date.
g2-reviewsadds a second large software review site.trustradius-reviewscovers another set of business buyers.gartner-reviewsadds enterprise-level reviews.reddit-searchfinds the unfiltered discussion where users compare tools.
For the wider job of watching what customers say, see review monitoring.
What you pay
You pay per review: starting a run holds its maximum cost, the per-call fee plus the per-review fee times max_results, and the run settles to what it returned. The rest of the hold goes back to your balance. A run that fails or times out pays only for the reviews it delivered, and a run refused at the start costs nothing.
There is no subscription and no monthly minimum: top up from $5, and one balance pays for tools and models. The card above shows today's price; pricing lists every tool.
Frequently asked questions
What link do I pass?+
The Capterra product page for the reviews, for example https://www.capterra.com/p/135003/Slack/reviews/.
Can I get only low-rated reviews?+
Yes. Set starRating to the stars you want, or set sort to LOWEST_RATED. You can combine several star values.
How do I get all reviews of a product?+
Set maxResults to 0 or leave it empty to get all reviews, but start small, because you pay per review. max_results in the request body also caps the run.
Can I run several products in one request?+
productUrl takes one product page, so start one run per product.
Do I need a subscription?+
No. You add credit to a prepaid balance and each run draws it down. Failed runs pay only for the results they delivered, and nothing renews automatically.
Studying a market? See review monitoring, research agents, and the tool catalog.