# TrustRadius $1πŸ’° Reviews, Products, Category & Compare Scraper (`memo23/trustradius-scraper`) Actor πŸ’° $1 per 1,000 results TrustRadius all-in-one scraper β€” product, reviews, category & compare URLs in one actor. Flat per-review rows with full Q\&A sections, reviewer firmographics & LinkedIn URL, dual 0–10/0–5 ratings, awards & featureList. Sitemap-driven bulk mode. Pure HTTP, no browser. - **URL**: https://apify.com/memo23/trustradius-scraper.md - **Developed by:** [Muhamed Didovic](https://apify.com/memo23) (community) - **Categories:** Automation, Agents, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 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. 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 ## TrustRadius Reviews, Products, Categories & Compare Scraper ### How it works ![How TrustRadius Scraper works](https://raw.githubusercontent.com/muhamed-didovic/muhamed-didovic.github.io/main/assets/how-it-works-trustradius.png) All-in-one TrustRadius.com scraper β€” paste any mix of URL kinds in the same input list and the actor auto-classifies each one: | Input | Row(s) emitted | |---|---| | **Any product URL** β€” `/products/{slug}`, `/products/{slug}/reviews`, or `/products/{slug}/reviews/all` | **1 product row + N review rows** β€” all three variants are treated identically. The actor fetches both the product page (rich `SoftwareApplication` JSON-LD with name/description/awards/featureList/vendor + 5 sample reviews with `reviewer.profilePicUrl` + `linkedInUrl` nested) and `/reviews/all` (paginated full review thread, 10 per page). Review count capped by `maxReviewsPerProduct`. | | **Category URL** β€” `/categories/{slug}` (e.g. `collaboration`, `crm`) | **N category-product rows** β€” one per product in the category (`rowType: "category-product"`). Each row carries a nested `categoryAggregate` with description, total count, **FAQs** (from JSON-LD `FAQPage`), and related categories. | | **Compare URL** β€” `/compare-products/{slug-a}-vs-{slug-b}` | 1 compare row: side-by-side products with ratings, vendor info, logos | | **Sitemap URL** β€” `/sitemap_index.xml` | **Bulk discovery** β€” expands the sitemap into product URLs and scrapes the first `maxProductsFromSitemap` (default 50). | Bare product slugs (`slack`) also work. JSON + CSV. > **One product URL β†’ product overview + every review.** You don't need to paste both `/reviews` and `/reviews/all` β€” any product-shaped URL gives you the full coverage. The three variants (`/products/slack`, `/products/slack/reviews`, `/products/slack/reviews/all`) all dedupe to the same canonical URL internally. > **Reviews are flat with the aggregate denormalized into every row.** Every dataset row from a reviews URL is a single review. The thread-level aggregate (rating, awards, features, vendor info, total reviews, pages scraped) lives under each row's `productAggregate` field β€” duplicated on every review row from the same URL, but that keeps each row self-contained and makes billing trivial: one row = one paid `outputrecord` event. > Pure HTTP. No Puppeteer, no Playwright, no headless Chromium. TrustRadius is open (no Cloudflare) so we use a simple impit Firefox fingerprint at concurrency 5. --- TrustRadius's anti-bot posture is far gentler than Capterra's or G2's β€” there's **no Cloudflare gate, no challenge JS, no IP banning** at our request volume. We confirmed this with parallel probes across 9 URL kinds: every one returned 200 on the first impit attempt through Apify Residential US. `robots.txt` is permissive β€” `/products/`, `/categories/`, `/compare-products/`, and `/sitemap_index.xml` are all crawl-allowed. So no warmup, no session rotation, no cookie jar. We fan out parallel requests through a sliding-window scheduler (default concurrency 5). #### Data architecture - **Product / reviews / category pages** use Next.js App-router with `__next_f.push` RSC streaming + comprehensive JSON-LD. We extract structured data from both sources: - `SoftwareApplication` JSON-LD ships `aggregateRating`, `featureList`, `award`, `offers`, **plus 5 fully-structured `review[]` objects** (Person author + Rating + reviewBody + datePublished). - The RSC stream carries `reviewer:{firstName, lastName, jobTitle, companyName, companySize, department, user:{pictureUrl, linkedInProfileUrl, linkedInIsVerified}}` blocks per visible review β€” same brace-balanced extractor we proved on Capterra. - **`/reviews/all?page=N`** is the paginated review thread: 10 visible `
` cards per page, JSON-LD only carries `aggregateRating` here. We DOM-walk articles for title + date + rating + section headings (Q&A) and align them with RSC reviewer blocks for firmographics. - **`/categories/{slug}`** has `ItemList` JSON-LD (product cards), `FAQPage` JSON-LD (editorial Q&A), and `BreadcrumbList` β€” three structured sources we merge into one row per product. - **`/compare-products/{a}-vs-{b}`** is HTML-only (6 MB of editorial content; no embedded data JSON). We extract product info per slug via visible card walking β€” best-effort in v1. --- ### Input Field | Type | Required | Notes --- | --- | --- | --- `startUrls` | `string[]` | yes | Any mix of product / reviews / category / compare / sitemap URLs (or bare product slugs). Auto-classified. `maxItems` | `integer` | no | Safety cap on **total dataset rows**, not URLs. A reviews URL with 100 reviews emits 100 review rows; a category URL with 50 products emits 50 rows. Default `1000`. Free-tier users are capped at `100`. `maxReviewsPerProduct` | `integer` | no | Max individual review rows emitted per reviews URL. TrustRadius paginates 10 per page; Slack has ~10,000 reviews across ~1,000 pages β€” cap aggressively. Default `100`, `0` = no limit. `maxProductsPerCategory` | `integer` | no | Max category-product rows emitted per category URL. Default `50`, `0` = no limit. `maxProductsFromSitemap` | `integer` | no | When you paste a sitemap URL, the actor discovers product URLs and scrapes the first N. Default `50`. `normalizeRatings` | `boolean` | no | Add `averageNormalized` (0–5 scale) alongside native 0–10. Default `true`. `includeReviewSections` | `boolean` | no | Include full per-question `sections[]` on each review row. Adds 1–3 KB per row but captures TrustRadius's unique Q&A structure. Default `true`. `maxConcurrency` | `integer` | no | Parallel HTTP requests. TrustRadius is open β€” concurrency up to 10 is safe. Default `5`. `maxRequestRetries` | `integer` | no | Per-URL retry budget on 5xx/network errors. Default `3`. `proxy` | object | no | Apify Residential US recommended. #### Example input ```json { "startUrls": [ "https://www.trustradius.com/products/slack", "https://www.trustradius.com/categories/collaboration", "https://www.trustradius.com/compare-products/slack-vs-microsoft-teams" ], "maxItems": 100, "maxReviewsPerProduct": 30, "maxProductsPerCategory": 20, "normalizeRatings": true, "includeReviewSections": true, "proxy": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US" } } ```` That yields **52 rows** on Slack: 1 product row (with 5 rich nested review snippets + LinkedIn URLs) + 30 flat review rows (paginated `/reviews/all`, with `productAggregate` nested) + 20 category-product rows + 1 compare. Use `maxItems` / `maxReviewsPerProduct` / `maxProductsPerCategory` to cap per-URL fan-out. *** ### Output schema Four row shapes, distinguished by the `rowType` field: `product`, `review`, `category-product`, `compare`. #### `rowType: "product"` ```jsonc { "rowType": "product", "productUrl": "https://www.trustradius.com/products/slack/reviews", "productSlug": "slack", "name": "Slack", "description": "Slack brings team communication and collaboration into one place…", "applicationCategory": "BusinessApplication", "categories": ["Collaboration"], "rating": { "average": 9, "averageNormalized": 4.5, // 0–5 scale for cross-platform consumers "count": 9979, "bestRating": 10, "worstRating": 1 }, "vendor": { "name": "Salesforce", "url": "https://slack.com/…" }, "offer": { "price": 0, "priceCurrency": "USD", "offerUrl": null }, "awards": [ { "title": "Buyer's Choice 2026", "year": "2026" } ], "features": ["Task Management", "Gantt Charts", "Scheduling", /* +20 more */], "reviewSnippets": [ /* up to 5 fully-structured reviews from JSON-LD */ ], "breadcrumbs": [ /* ... */ ], "scrapedAt": "2026-05-12T17:36:00.000Z" } ``` #### `rowType: "review"` (one per individual review) ```jsonc { "rowType": "review", "reviewsUrl": "https://www.trustradius.com/products/slack/reviews/all", "productSlug": "slack", "productName": "Slack", "reviewId": null, // TrustRadius doesn't surface stable IDs on /reviews/all "title": "Slack Review", "reviewUrl": "https://www.trustradius.com/products/slack/reviews", "rating": { "average": 10, // native 0–10 "averageNormalized": 5, // 0–5 normalized "count": 1, "bestRating": 10, "worstRating": 1 }, "text": "So we use it for daily collaboration, just notifications…", "pros": null, "cons": null, "publishedAt": "2026-05-12T01:30:29.251Z", // ISO 8601 β€” cleaner than Capterra's "May 31, 2024" // Reviewer firmographics β€” RICHER than Capterra (companyName + department + LinkedIn URL) "reviewer": { "name": "Sapna Nayak", "firstName": "Sapna", "lastName": "Nayak", "jobTitle": "Senior Salesforce Administrator", "jobType": "Administrator", "companyName": "Side", // ← Capterra doesn't surface company NAME "companySize": "51-200 employees", "department": "Other", // ← richer than Capterra "industry": null, "profileUrl": null, "profilePicUrl": "https://media.trustradius.com/profile-photos/…jpeg", // when available "linkedInUrl": "https://www.linkedin.com/in/sapna-nayak-…", // ← UNIQUE to TrustRadius "linkedInVerified": null }, // Per-question Q&A β€” UNIQUE to TrustRadius "sections": [ { "title": "Use Cases and Deployment Scope", "responses": [ { "question": "Use Cases and Deployment Scope", "answer": "So we use it for daily collaboration, just notifications for different things…" } ] }, { "title": "Pros", "responses": [{ "question": "Pros", "answer": "Real-time messaging | File sharing | Channel organization" }] }, { "title": "Cons", "responses": [{ "question": "Cons", "answer": "Search can be slow for large workspaces" }] } /* + more sections per review */ ], "incentive": null, // "Incentivized" when TrustRadius flags it "source": "TrustRadius", "trusted": null, // Thread-level aggregate (same on every review row from the same reviews URL) "productAggregate": { "rating": { "average": 9, "averageNormalized": 4.5, "count": 9980, "bestRating": 10, "worstRating": 1 }, "awards": [{ "title": "Buyer's Choice 2026", "year": "2026" }], "features": ["Task Management", "Gantt Charts", /* +21 */], "vendor": { "name": "Salesforce", "url": "https://slack.com/…" }, "totalReviewsEmitted": 30, "pagesScraped": 3 }, "scrapedAt": "2026-05-12T17:36:00.000Z" } ``` #### `rowType: "category-product"` (one per product in the category) ```jsonc { "rowType": "category-product", "categoryUrl": "https://www.trustradius.com/categories/collaboration", "categorySlug": "collaboration", "productSlug": "slack", "productUrl": "https://www.trustradius.com/products/slack", "name": "Slack", "description": "Slack brings team communication into one place…", "rating": { "average": 9, "averageNormalized": 4.5, "count": null, "bestRating": 10, "worstRating": 1 }, "vendor": { "name": "Salesforce", "url": "…" }, "logoUrl": "https://media.trustradius.com/product-logos/…png", "sponsored": null, "categoryAggregate": { "categoryUrl": "https://www.trustradius.com/categories/collaboration", "categorySlug": "collaboration", "categoryName": "Collaboration Tools", "description": "Collaboration tools help teams work together…", "totalProductsOnPage": 25, "faqs": [ // ← TrustRadius ships editorial Q&A as JSON-LD FAQPage { "question": "What is collaboration software?", "answer": "…" }, { "question": "How much does it cost?", "answer": "…" } ], "relatedCategories": [{ "name": "Web Conferencing", "url": "…" }, /* +29 */] }, "scrapedAt": "2026-05-12T17:36:00.000Z" } ``` #### `rowType: "compare"` ```jsonc { "rowType": "compare", "compareUrl": "https://www.trustradius.com/compare-products/slack-vs-microsoft-teams", "title": "Microsoft Teams vs Slack", "products": [ { "productSlug": "slack", "productUrl": "https://www.trustradius.com/products/slack", "name": "Slack", "rating": { "average": 9, "averageNormalized": 4.5, /* … */ }, "vendor": null, "logoUrl": "https://media.trustradius.com/product-logos/…png" }, { "productSlug": "microsoft-teams", "productUrl": "https://www.trustradius.com/products/microsoft-teams", "name": "Microsoft Teams", "rating": { "average": 8.6, "averageNormalized": 4.3, /* … */ }, /* … */ } ], "scrapedAt": "2026-05-12T17:36:00.000Z" } ``` > **Compare row is best-effort in v1.0.** TrustRadius compare pages are HTML-rendered editorial articles (no embedded JSON data block). We DOM-walk the visible cards per slug β€” good for slug + name + rating + logo, but vendor info may be partial. For full data, scrape each product separately. *** ### Pricing Pay-per-event. **Reviews and category-products are billed flat** β€” each is its own dataset row, one `outputrecord` event per row. Cost = `rows Γ— outputrecord-price`. No nested-array arithmetic. Event | When | Suggested rate \--- | --- | --- `outputrecord` | Once per dataset row pushed β€” `product`, `review`, `category-product`, `compare`. Thread/category aggregate is nested INSIDE each flat row. | configured on the actor page `additional-data` | Once per nested item inside a product / compare row only (features, awards, review snippets, breadcrumb categories, compared products). Reviews and category-products are never billed here. | **$0.75 per 1,000 items** ($0.00075 each) *** ### What makes this richer than the competition We surveyed all 16 TrustRadius actors on Apify Store (May 2026). The top specialist (`zen-studio/trustradius-review-scraper`, 25 users) covers **reviews only**. Same gap we filled for Capterra. Capability | Competitor actors | **This actor** \--- | --- | --- Product + reviews + category + compare in **one actor** | ❌ (reviews-only is the norm) | βœ… Sitemap-driven bulk discovery | ❌ | βœ… URL auto-classification (paste any mix) | ❌ | βœ… **Per-question `sections[]` Q\&A** captured on every review | partial (1 actor mentions Q\&A, partial coverage) | βœ… **Reviewer LinkedIn URL** | ❌ | βœ… **Reviewer company name** (not just size) | ❌ | βœ… **Reviewer department** | ❌ | βœ… Dual **0–10 native + 0–5 normalized** ratings | ❌ | βœ… Capterra-style **awards** (Buyer's Choice etc.) | ❌ | βœ… Category **FAQ** extraction (from JSON-LD `FAQPage`) | ❌ | βœ… Flat-per-review billing (1 review = 1 paid row) | mixed | βœ… *** ### Notes & limitations - **TrustRadius is open** β€” no Cloudflare, no warmup needed. Apify Residential US works first-attempt at 100%. - **Reviews pagination** auto-walks `/reviews/all?page=N` until empty or `maxReviewsPerProduct` hits. Slack has ~10,000 reviews across ~1,000 pages β€” set caps appropriately. - **Compare extraction** is best-effort in v1.0 β€” TrustRadius compare pages ship as HTML-only editorial. v1.1 will follow per-product fetches for richer compare rows (same pattern that worked on Capterra). - **`reviewer.profilePicUrl` / `linkedInUrl` data-source notes.** These fields are surfaced **on the product page (`/products/{slug}/reviews`)** β€” the 5 reviews shipped via JSON-LD + RSC carry full reviewer.user blocks (profile pic + LinkedIn URL + verification flag). On the paginated `/products/{slug}/reviews/all?page=N`, TrustRadius ships a slimmer payload that does **not** include these fields β€” reviewer firmographics (name, company, jobTitle, department, companySize) are still 100%-filled, but profile pic + LinkedIn URLs come back null. If you need full reviewer enrichment, prefer the `/reviews` URL over `/reviews/all`. - **Sitemap mode** is conservative β€” only walks `maxProductsFromSitemap` URLs to avoid runaway costs. Buyers wanting full-catalog scrapes should run multiple sitemap calls with `maxItems` set high. *** ### Support Issues, feature requests, or custom output shapes? Open a ticket on the actor's Apify page or message the maintainer. # Actor input Schema ## `startUrls` (type: `array`): Paste any mix of: β€’ Product URLs β€” `https://www.trustradius.com/products/{slug}` (any of `/products/{slug}`, `/products/{slug}/reviews`, or `/products/{slug}/reviews/all` work β€” each emits 1 product row + N flat review rows automatically) β€’ Category URLs β€” `https://www.trustradius.com/categories/{slug}` β€’ Compare URLs β€” `https://www.trustradius.com/compare-products/{slug-a}-vs-{slug-b}` β€’ Sitemap URL β€” `https://www.trustradius.com/sitemap_index.xml` (bulk discovery) Bare product slugs (e.g. `slack`) also work. Each entry is auto-classified. ## `maxItems` (type: `integer`): Safety cap on total dataset rows. Product / compare URLs emit 1 row each. A reviews URL emits 1 row per individual review; a category URL emits 1 row per product listed. Sitemap URLs can expand to thousands β€” start small. Each emitted row = one paid `outputrecord` event. ## `maxReviewsPerProduct` (type: `integer`): Maximum review rows emitted per reviews URL. TrustRadius paginates 10 reviews per page on `/reviews/all`; Slack has ~10,000 reviews across ~1,000 pages β€” cap aggressively. Set 0 for no limit. ## `maxProductsPerCategory` (type: `integer`): Maximum category-product rows emitted per category URL. Set 0 for no limit. ## `maxProductsFromSitemap` (type: `integer`): When you paste a sitemap index URL (`/sitemap_index.xml`), the actor discovers product URLs and scrapes the first N. Recommended cap when exploring the catalog. ## `normalizeRatings` (type: `boolean`): TrustRadius uses a 0–10 scale. Enable to also emit a 0–5 normalized rating field (`ratingNormalized`) on every row for cross-platform comparison with Capterra / G2 / Trustpilot consumers. ## `includeReviewSections` (type: `boolean`): When enabled, every review row carries the full `sections[]` array β€” each section has its title + list of `{question, answer}` pairs. Adds ~1–3 KB per row but captures TrustRadius's unique structured-Q\&A feature. Disable for compact CSV exports. ## `maxConcurrency` (type: `integer`): Parallel HTTP requests. TrustRadius is open (no Cloudflare), so concurrency up to 10 is safe. ## `maxRequestRetries` (type: `integer`): Per-URL retry budget on 5xx / network errors. ## `proxy` (type: `object`): Apify residential proxy is recommended (US country). TrustRadius accepts datacenter IPs too, but residential is more reliable for high-volume runs. ## Actor input object example ```json { "startUrls": [ "https://www.trustradius.com/products/slack", "https://www.trustradius.com/categories/collaboration", "https://www.trustradius.com/compare-products/slack-vs-microsoft-teams" ], "maxItems": 1000, "maxReviewsPerProduct": 100, "maxProductsPerCategory": 50, "maxProductsFromSitemap": 50, "normalizeRatings": true, "includeReviewSections": true, "maxConcurrency": 5, "maxRequestRetries": 3, "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } ``` # 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 = { "startUrls": [ "https://www.trustradius.com/products/slack", "https://www.trustradius.com/categories/collaboration", "https://www.trustradius.com/compare-products/slack-vs-microsoft-teams" ], "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }; // Run the Actor and wait for it to finish const run = await client.actor("memo23/trustradius-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "startUrls": [ "https://www.trustradius.com/products/slack", "https://www.trustradius.com/categories/collaboration", "https://www.trustradius.com/compare-products/slack-vs-microsoft-teams", ], "proxy": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US", }, } # Run the Actor and wait for it to finish run = client.actor("memo23/trustradius-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ "https://www.trustradius.com/products/slack", "https://www.trustradius.com/categories/collaboration", "https://www.trustradius.com/compare-products/slack-vs-microsoft-teams" ], "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }' | apify call memo23/trustradius-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=memo23/trustradius-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TrustRadius $1πŸ’° Reviews, Products, Category & Compare Scraper", "description": "πŸ’° $1 per 1,000 results TrustRadius all-in-one scraper β€” product, reviews, category & compare URLs in one actor. Flat per-review rows with full Q&A sections, reviewer firmographics & LinkedIn URL, dual 0–10/0–5 ratings, awards & featureList. Sitemap-driven bulk mode. Pure HTTP, no browser.", "version": "0.1", "x-build-id": "YWH7h3kLhNROAWk8a" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/memo23~trustradius-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-memo23-trustradius-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/memo23~trustradius-scraper/runs": { "post": { "operationId": "runs-sync-memo23-trustradius-scraper", "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/memo23~trustradius-scraper/run-sync": { "post": { "operationId": "run-sync-memo23-trustradius-scraper", "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": [ "startUrls" ], "properties": { "startUrls": { "title": "TrustRadius URLs", "type": "array", "description": "Paste any mix of:\nβ€’ Product URLs β€” `https://www.trustradius.com/products/{slug}` (any of `/products/{slug}`, `/products/{slug}/reviews`, or `/products/{slug}/reviews/all` work β€” each emits 1 product row + N flat review rows automatically)\nβ€’ Category URLs β€” `https://www.trustradius.com/categories/{slug}`\nβ€’ Compare URLs β€” `https://www.trustradius.com/compare-products/{slug-a}-vs-{slug-b}`\nβ€’ Sitemap URL β€” `https://www.trustradius.com/sitemap_index.xml` (bulk discovery)\n\nBare product slugs (e.g. `slack`) also work. Each entry is auto-classified.", "items": { "type": "string" } }, "maxItems": { "title": "Max dataset rows to emit", "minimum": 1, "type": "integer", "description": "Safety cap on total dataset rows. Product / compare URLs emit 1 row each. A reviews URL emits 1 row per individual review; a category URL emits 1 row per product listed. Sitemap URLs can expand to thousands β€” start small. Each emitted row = one paid `outputrecord` event.", "default": 1000 }, "maxReviewsPerProduct": { "title": "Max reviews per product", "minimum": 0, "type": "integer", "description": "Maximum review rows emitted per reviews URL. TrustRadius paginates 10 reviews per page on `/reviews/all`; Slack has ~10,000 reviews across ~1,000 pages β€” cap aggressively. Set 0 for no limit.", "default": 100 }, "maxProductsPerCategory": { "title": "Max products per category", "minimum": 0, "type": "integer", "description": "Maximum category-product rows emitted per category URL. Set 0 for no limit.", "default": 50 }, "maxProductsFromSitemap": { "title": "Max products from a sitemap URL", "minimum": 0, "type": "integer", "description": "When you paste a sitemap index URL (`/sitemap_index.xml`), the actor discovers product URLs and scrapes the first N. Recommended cap when exploring the catalog.", "default": 50 }, "normalizeRatings": { "title": "Include 0–5 normalized ratings", "type": "boolean", "description": "TrustRadius uses a 0–10 scale. Enable to also emit a 0–5 normalized rating field (`ratingNormalized`) on every row for cross-platform comparison with Capterra / G2 / Trustpilot consumers.", "default": true }, "includeReviewSections": { "title": "Include per-question Q&A on reviews", "type": "boolean", "description": "When enabled, every review row carries the full `sections[]` array β€” each section has its title + list of `{question, answer}` pairs. Adds ~1–3 KB per row but captures TrustRadius's unique structured-Q&A feature. Disable for compact CSV exports.", "default": true }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 10, "type": "integer", "description": "Parallel HTTP requests. TrustRadius is open (no Cloudflare), so concurrency up to 10 is safe.", "default": 5 }, "maxRequestRetries": { "title": "Max request retries", "minimum": 0, "type": "integer", "description": "Per-URL retry budget on 5xx / network errors.", "default": 3 }, "proxy": { "title": "Proxy configuration", "type": "object", "description": "Apify residential proxy is recommended (US country). TrustRadius accepts datacenter IPs too, but residential is more reliable for high-volume runs.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```