# Review Intelligence — G2, Trustpilot, Glassdoor & Capterra (`ramsford/review-intelligence-agent`) Actor Aggregate any company's reviews across G2, Trustpilot, Glassdoor, and Capterra into one executive intelligence report. Sentiment scoring, recurring themes, star-rating trend, complaint clusters, and an AI-written narrative — per company. Pay per report. - **URL**: https://apify.com/ramsford/review-intelligence-agent.md - **Developed by:** [Don Johnson](https://apify.com/ramsford) (community) - **Categories:** Business, Marketing - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $1,250.00 / 1,000 review intelligence reports This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## Review Intelligence Agent — G2, Trustpilot, Glassdoor & Capterra in One Report **Turn scattered customer and employee reviews into a one-page intelligence report. No NLP service required, no per-API key, no glue code.** Most teams need to know one thing fast: **what are real customers and employees saying about a company right now — and how is that changing?** Browsing G2, Trustpilot, Glassdoor and Capterra by hand is hours of work for a single company; scaling it across a target list is a week. This actor does it in one call. Feed it any company plus the public URLs of its review pages, and it returns: - **An aggregated star rating** across every connected source - **Star-NPS proxy score** (4–5 share minus 1–2 share, the way investors actually look at SaaS reviews) - **Star trend** — last 30, 90, 180 days vs all-time - **Sentiment breakdown** — positive / mixed / negative / neutral - **Top complaint themes** — pricing, support, performance, onboarding, UI/UX, feature gaps, integrations, mobile, docs, data accuracy - **Top praise themes** — ease of use, value, speed, reliability, feature breadth, integrations, onboarding, support - **Notable positive and negative reviews** with star, source, and date - **Recurring phrase cloud** mined from the actual review text - **An AI-written executive narrative** that ties it all together in plain English Pay-per-report pricing. No subscription. No surprises. --- ### Who this is for - **Investors & due-diligence teams** — vet a SaaS or DTC target in 30 seconds before deeper diligence - **Competitive intelligence teams** — track 50 competitors across 4 review sources without hiring an analyst - **Sales reps** — walk into a pitch already knowing what your prospect's customers love and hate - **Product teams** — spot complaint clusters around your competitor's last release - **CX leaders** — benchmark your own brand against the field - **Agencies** — sell a "review intelligence" deliverable to clients without building it yourself --- ### How it works 1. You provide an array of `companies`. Each company is just `{ name }` plus any subset of `g2Url`, `trustpilotUrl`, `glassdoorUrl`, `capterraUrl`. 2. The actor pulls reviews from each provided source (capped per source for speed). 3. It dedupes across sources, scores sentiment, mines complaint and praise themes, computes star trends, and writes a narrative. 4. Each company produces **one report**. You are charged per report (PPE). Provide more sources = stronger signal. The minimum useful setup is one URL. --- ### Input ```json { "companies": [ { "name": "Acme Corp", "g2Url": "https://www.g2.com/products/acme/reviews", "trustpilotUrl": "https://www.trustpilot.com/review/acme.com", "glassdoorUrl": "https://www.glassdoor.com/Reviews/Acme-Reviews-E12345.htm", "capterraUrl": "https://www.capterra.com/p/123456/Acme/" } ], "maxReviewsPerSource": 75, "reportStyle": "full" } ```` | Field | Required | Default | Description | |---|---|---|---| | `companies[].name` | Yes | — | Company name (used in the report headline) | | `companies[].g2Url` | No | — | Public G2 reviews URL | | `companies[].trustpilotUrl` | No | — | Public Trustpilot review page | | `companies[].glassdoorUrl` | No | — | Public Glassdoor reviews page | | `companies[].capterraUrl` | No | — | Public Capterra product page | | `maxReviewsPerSource` | No | 75 | Per-source cap. 10–300 | | `reportStyle` | No | `full` | `full` (detailed markdown) or `brief` (one-page exec summary) | *** ### Output — one record per company Each company in `companies` produces one row in the dataset. Key fields: ```jsonc { "company": "Acme Corp", "scrapedAt": "2026-05-16T12:00:00.000Z", "totalReviews": 187, "averageStars": 4.31, "starNpsProxy": 58, "starDistribution": { "1": 6, "2": 9, "3": 18, "4": 64, "5": 90 }, "sentimentBreakdown": { "positive": 121, "mixed": 30, "negative": 32, "neutral": 4 }, "topComplaints": [ ["Pricing & billing", 19], ["Customer support", 12], ... ], "topPraise": [ ["Ease of use", 33], ["Customer support", 21], ... ], "recentTrend": { "last30d": 4.40, "last90d": 4.36, "last180d": 4.33, "last30dCount": 11, ... }, "sourceSummary": [ { "source": "g2", "count": 75 }, ... ], "notablePositiveReviews": [ ... ], "notableNegativeReviews": [ ... ], "aiNarrative": "Acme Corp averages 4.31/5 across 187 aggregated reviews. Star-NPS proxy is 58 (strong). Sentiment: 65% positive, 17% negative. Recurring complaints: Pricing & billing (19), Customer support (12). Praise themes: Ease of use (33), Customer support (21).", "intelligenceReport": "## Review Intelligence Report — Acme Corp\n…" } ``` `intelligenceReport` is a fully formatted markdown report you can drop straight into a CRM, Slack, Notion, or PDF generator. *** ### Pricing **$1.25 per company report** (pay-per-event). One company in `companies` = one report = one charge. You only pay for completed reports. Why this is a steal: collecting and analyzing reviews for a single company across 4 sources by hand is roughly 60–90 minutes of analyst time. Even at $40/hour, that's $40–60 of labor per company. This actor delivers the same artifact for **$1.25**, in under a minute, with a consistent format you can compare across hundreds of companies. *** ### Common workflows - **Build a competitive matrix.** Run 20 competitors in one input. Export the dataset to CSV. Sort by `starNpsProxy`. You now have a ranked SaaS leaderboard. - **Pre-call sales intel.** Run a prospect 10 minutes before the demo. Open the `topComplaints` field — you now know what to lead with. - **M\&A diligence shortlist.** Run your target list. Filter by `recentTrend.last90d` falling vs `averageStars`. That's your "review velocity is bad" alert. - **Brand alarm system.** Schedule weekly. Diff the `topComplaints` field. New theme appearing? That's your investigation. *** ### Tips for high-quality reports - **Provide all four URLs when possible.** Cross-source dedupe is what lets the report reach "executive" quality. - **Use `maxReviewsPerSource: 150+` for deep dives** on a small list. Use the default 75 for fast triage runs across many companies. - **For B2B SaaS**, G2 and Capterra usually carry the highest-signal reviews. For DTC and consumer brands, Trustpilot. For employer-brand work, Glassdoor. - **Run it on yourself first.** The report often surfaces complaint themes your own team has been brushing off. *** ### What this actor does **not** do - It does **not** scrape behind login walls. Provide public review URLs only. - It does **not** translate reviews — non-English reviews are analyzed at lower precision. - It does **not** call an external LLM. The narrative is built from on-device heuristics, which is what makes the per-report cost so low. If you need true LLM-summarized review reports at scale, contact us — we run a parallel actor for that workflow. *** ### Limits & honesty Public review pages change layouts. We use multiple selector fallbacks per source and degrade gracefully — if one source returns 0 reviews, the report continues and clearly labels that source as empty. Built and maintained by **Johnson AI Consulting** — the same shop that ships the Hiring Signal Intelligence Agent and the Competitor Intelligence Monitor on Apify Store. # Actor input Schema ## `companies` (type: `array`): List of company objects. Each needs at minimum: name. Provide any subset of: g2Url, trustpilotUrl, glassdoorUrl, capterraUrl. More sources = stronger signal. ## `maxReviewsPerSource` (type: `integer`): Maximum number of reviews to collect from each source per company. Higher = richer signal, longer run time. ## `reportStyle` (type: `string`): 'full' produces a detailed markdown report. 'brief' produces a one-page executive summary. ## Actor input object example ```json { "companies": [ { "name": "Acme Corp", "g2Url": "https://www.g2.com/products/acme/reviews", "trustpilotUrl": "https://www.trustpilot.com/review/acme.com", "glassdoorUrl": "https://www.glassdoor.com/Reviews/Acme-Reviews-E12345.htm", "capterraUrl": "https://www.capterra.com/p/123456/Acme/" } ], "maxReviewsPerSource": 75, "reportStyle": "full" } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("ramsford/review-intelligence-agent").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("ramsford/review-intelligence-agent").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call ramsford/review-intelligence-agent --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ramsford/review-intelligence-agent", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Review Intelligence — G2, Trustpilot, Glassdoor & Capterra", "description": "Aggregate any company's reviews across G2, Trustpilot, Glassdoor, and Capterra into one executive intelligence report. Sentiment scoring, recurring themes, star-rating trend, complaint clusters, and an AI-written narrative — per company. Pay per report.", "version": "0.1", "x-build-id": "1xzbE5O5AUrBPBtv0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ramsford~review-intelligence-agent/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ramsford-review-intelligence-agent", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ramsford~review-intelligence-agent/runs": { "post": { "operationId": "runs-sync-ramsford-review-intelligence-agent", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ramsford~review-intelligence-agent/run-sync": { "post": { "operationId": "run-sync-ramsford-review-intelligence-agent", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "companies" ], "properties": { "companies": { "title": "Companies", "type": "array", "description": "List of company objects. Each needs at minimum: name. Provide any subset of: g2Url, trustpilotUrl, glassdoorUrl, capterraUrl. More sources = stronger signal." }, "maxReviewsPerSource": { "title": "Max reviews per source", "minimum": 10, "maximum": 300, "type": "integer", "description": "Maximum number of reviews to collect from each source per company. Higher = richer signal, longer run time.", "default": 75 }, "reportStyle": { "title": "Report style", "enum": [ "full", "brief" ], "type": "string", "description": "'full' produces a detailed markdown report. 'brief' produces a one-page executive summary.", "default": "full" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```