# G2 Scraper - Reviews, Products, Analytics & Discussions (`kaix/g2-scraper`) Actor 🔥 ~$0.05/1K reviews 🔥 Scrape G2.com software reviews, products, analytics, comparisons, and discussions. Faceted filtering, facet-value discovery, 72 review fields, NLP sentiment, switching intelligence. - **URL**: https://apify.com/kaix/g2-scraper.md - **Developed by:** [Kai](https://apify.com/kaix) (community) - **Categories:** E-commerce, AI, Lead generation - **Stats:** 4 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.04 / 1,000 reviews 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 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 ## G2 Scraper Scrape G2.com software reviews, products, analytics, comparisons, and discussions. Rich faceted filtering (primary region, review source, response type, sentiment themes, discount), facet-value discovery, 72 review fields, NLP sentiment themes, and switching intelligence. No proxy needed. ### Why use this scraper? - Scrape a product's full review history (`maxReviewsPerProduct: 0` for no limit), no anti-bot bypass needed. - Structured pros/cons/benefits parsed from each review. - Per-dimension ratings: ease of use, setup, support, security, and more. - NLP-extracted sentiment themes (what users love/hate). - Competitive switching intelligence (what products users switched from and why). - Faceted filtering: narrow reviews by primary region, review source, response type, loved/hated/switching themes, and discount. - Facet-value discovery: list the valid values for any text facet before filtering. - Analytics mode with aggregations, percentiles, and significant terms. - Side-by-side product comparisons in a single request. - Q&A discussion threads per product. ### Use cases - Compare competitors by sentiment, ratings, and switching patterns. - Feed structured review data into NLP / AI pipelines. - Track review trends over time for market research. - Segment reviews by region, company size, review source, or sentiment theme. - Find products by category, vendor, or keyword search. - Search across all reviews for specific topics. ### How to use #### Scrape reviews for a product ```json { "products": ["https://www.g2.com/products/slack/reviews"] } ```` #### Search for products and scrape their reviews ```json { "search": "project management", "maxProducts": 5, "maxReviewsPerProduct": 50 } ``` #### Browse a category ```json { "category": "CRM", "maxProducts": 10, "maxReviewsPerProduct": 20 } ``` #### Browse by vendor ```json { "vendor": "Salesforce", "maxProducts": 5, "maxReviewsPerProduct": 10 } ``` #### Compare products side-by-side ```json { "compare": ["slack", "clickup", "jira"] } ``` #### Get analytics (no individual reviews) ```json { "products": ["slack"], "analytics": true } ``` #### Global review search across all products ```json { "reviewSearch": "terrible customer support", "maxReviews": 50 } ``` #### Find similar reviews ```json { "similarTo": "The API was difficult to integrate and documentation was poor", "maxReviews": 20 } ``` #### Filter by date, rating, and company size ```json { "products": ["slack"], "dateFrom": "2025-01-01", "ratings": ["1", "2"], "companySegment": ["enterprise"], "maxReviewsPerProduct": 100 } ``` #### Filter by facets (region, source, themes) ```json { "products": ["slack"], "primaryRegions": ["Americas"], "sourceTypes": ["organic"], "responseTypes": ["video"], "maxReviewsPerProduct": 50 } ``` #### Discover valid facet values Returns the distinct values for each facet to the `metadata` dataset, so you know what to pass to the facet filters above. No reviews are scraped in this mode. ```json { "enumFields": ["source_type", "response_type"] } ``` #### Search within reviews with highlights ```json { "products": ["slack"], "reviewSearch": "customer support", "includeHighlights": true, "maxReviewsPerProduct": 20 } ``` #### Include Q\&A discussions ```json { "products": ["slack"], "maxReviewsPerProduct": 10, "includeDiscussions": true } ``` ### Input | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `products` | string\[] | | Product URLs, slugs, or category URLs | | `search` | string | | Find products by keyword | | `category` | string | | Browse products by G2 category | | `vendor` | string | | Browse products by vendor name | | `compare` | string\[] | | Compare products side-by-side (analytics) | | `maxProducts` | number | `10` | Max products in search/category/vendor mode | | `sortBy` | select | `DATE_DESC` | `DATE_DESC`, `DATE_ASC`, `RATING_DESC`, `RATING_ASC`, `HELPFUL_DESC`, `G2_DEFAULT` | | `ratings` | string\[] | `["1","2","3","4","5"]` | Filter by star rating; values `"1"`–`"5"` | | `maxReviewsPerProduct` | number | `20` | Max reviews per product (0 = unlimited) | | `companySegment` | string\[] | | `small_business`, `mid_market`, `enterprise` | | `dateFrom` | string | | ISO date, reviews from this date | | `dateTo` | string | | ISO date, reviews until this date | | `primaryRegions` | select\[] | | `Americas`, `Asia Pacific`, `EMEA` | | `sourceTypes` | string\[] | | Filter by how the review was collected; use `enumFields` to list valid values | | `responseTypes` | string\[] | | Filter by review medium (e.g. `text`, `video`) | | `loveThemes` | string\[] | | Filter by themes reviewers praised | | `hateThemes` | string\[] | | Filter by themes reviewers criticized | | `switchingThemes` | string\[] | | Filter by reasons reviewers switched products | | `discounts` | string\[] | | Filter by reported discount | | `reviewSources` | string\[] | | Filter by review source channel | | `reviewSearch` | string | | Search within review text. Alone = global search | | `similarTo` | string | | Find reviews similar to this text | | `reviewIds` | string\[] | | Fetch specific reviews by ID | | `maxReviews` | number | `100` | Max reviews for global/similar search | | `enumFields` | select\[] | | Discover distinct values for facets; writes to the `metadata` dataset instead of scraping reviews | | `analytics` | boolean | `false` | Return aggregation analytics instead of reviews | | `collapseByProduct` | boolean | `false` | One review per product in global search | | `includeNonPublic` | boolean | `false` | Include non-public/rejected reviews | | `includeDiscussions` | boolean | `false` | Fetch Q\&A discussion threads per product | | `includeHighlights` | boolean | `true` | Highlight matching text in search results | At least one input mode is required (`products`, `search`, `category`, `vendor`, `reviewSearch`, `similarTo`, `reviewIds`, `compare`, `enumFields`, or `analytics`). Filters apply to all matched reviews. ### Output #### Datasets | Dataset | When | Content | |---------|------|---------| | `reviews` (default) | Most modes | Individual review records | | `products` | Product-based modes | Product profiles | | `analytics` | `analytics` or `compare` mode | Aggregation statistics | | `discussions` | `includeDiscussions: true` | Q\&A threads | | `metadata` | `enumFields` mode | Distinct facet values | #### Review fields ```json { "id": "13038740", "productId": 3437, "productName": "Slack", "reviewUrl": "https://www.g2.com/products/slack/reviews/13038740", "title": "One-Click Integrations That Just Work for slack", "pros": "Integration with other apps has to be 1 click", "cons": "UI when you send the messages. The typing window should be adjustable", "benefits": "connect and chatting with the team One-Click Integrations That Just Work for slack", "rawText": "Integration with other apps has to be 1 click\nUI when you send the messages. The typing window should be adjustable\nconnect and chatting with the team One-Click Integrations That Just Work for slack", "responseType": "text", "nps": 8, "npsScore": 4, "easeOfUse": 5, "easeOfSetup": 5, "easeOfAdmin": 5, "easeOfDoingBusinessWith": 4, "meetsRequirements": 5, "qualityOfSupport": 3, "securityConfidence": 3, "securityImportance": 7, "direction": null, "userName": "Sameer G.", "country": "India", "region": "Asia", "primaryRegion": "Asia Pacific", "companySegment": 180, "companySegmentLabel": "Mid-Market (51-1000 emp.)", "industry": 313, "industryLabel": "Information Technology and Services", "role": 6, "roleLabel": "Consultant", "loveTheme": null, "loveThemeHumanized": null, "loveThemeParentHumanized": null, "hateTheme": null, "hateThemeHumanized": null, "hateThemeParentHumanized": null, "switchedFromOtherProduct": "unknown", "switchedFromProductIds": null, "switchedReason": null, "switchingThemes": null, "switchingThemesNested": null, "submittedAt": "2026-06-26T17:10:48.781-05:00", "publishedAt": "2026-06-26T19:30:00.900-05:00", "reviewSource": "user_profile", "sourceType": "user_profile", "helpful": 0, "englishAvailable": true, "contractLength": null, "discount": null, "price": 5, "status": "approved", "isPublic": true, "published": true, "productPaidProfile": false, "productIds": [3437], "categoryIds": [2174, 2360, 2363], "defaultSort": 8.525176115868225, "templateKeyword": "react", "videoReviewSubmittedAt": null, "editionIds": [], "expertiseIds": [], "serviceLocation": null, "contractLengthWeight": null, "discountWeight": null, "everApproved": true, "isInLimbo": false, "read": false, "reportable": true, "userUpdatedAt": "2026-06-26T17:10:48.965-05:00", "highlightedSnippets": null, "scrapedAt": "2026-06-28T06:00:34.982Z" } ``` #### Analytics output Aggregated over all of a product's reviews. `nps`/`easeOfUse`/etc. each carry `avg`, `stdDev`, `min`, `max`, and `count`; the full record also includes `easeOfSetup`, `easeOfAdmin`, `qualityOfSupport`, `meetsRequirements`, `easeOfDoingBusinessWith`, `securityConfidence`, `securityImportance`, `direction`, `topHateThemes`, `uniquelyHated`, and `bySourceType`. The theme, demographic, and `reviewsOverTime` arrays are trimmed below for brevity. ```json { "productId": 3437, "productName": "Slack", "productSlug": "slack", "totalReviews": 20201, "totalHelpfulVotes": 69, "nps": { "avg": 9.211870699470323, "stdDev": 1.1668658162744323, "min": 0, "max": 10, "count": 20201 }, "easeOfUse": { "avg": 6.549680122289532, "stdDev": 0.7953808393082141, "min": 1, "max": 7, "count": 17663 }, "ratingDistribution": { "1": 40, "2": 93, "3": 468, "4": 3646, "5": 15954 }, "npsPercentiles": { "p10": 8, "p25": 9, "p50": 10, "p75": 10, "p90": 10 }, "uniqueCountries": 140, "uniqueIndustries": 145, "topLoveThemes": [ { "theme": "Chat", "count": 3436, "sampleReviews": [{ "title": "Slack Review", "userName": "Hunter C.", "npsScore": 4 }] }, { "theme": "Collaboration", "count": 2254, "sampleReviews": [{ "title": "\"Ping\" From Your Creative Side", "userName": "Daniel G.", "npsScore": 5 }] } ], "uniquelyLoved": [ { "theme": "Chat", "score": 3.472215696777018, "count": 3436 }, { "theme": "Collaboration", "score": 1.2096931571663356, "count": 2254 } ], "switchingReasons": [ { "reason": "Ease of use", "count": 126 }, { "reason": "Communication Features", "count": 108 } ], "bySegment": [ { "code": 179, "label": "Small Business (50 or fewer emp.)", "count": 8191 }, { "code": 180, "label": "Mid-Market (51-1000 emp.)", "count": 8141 }, { "code": 181, "label": "Enterprise (>1000 emp.)", "count": 3516 } ], "byRegion": [ { "region": "Americas", "count": 12760 }, { "region": "Asia Pacific", "count": 4821 }, { "region": "EMEA", "count": 2526 } ], "reviewsOverTime": [ { "month": "2014-02", "count": 1 }, { "month": "2026-06", "count": 73 } ] } ``` #### Facet values output (`metadata` dataset) ```json { "field": "source_type", "type": "enum_values", "values": [ "ai_assisted_review", "api_collect", "g2_incentivized", "g2_nonincentivized", "g2gives", "influitive", "organic", "pop_up", "referral", "review_referral", "review_widget", "stale_reviews_callout", "thank_you_page", "un_survey", "unincentivized", "user_profile", "vendor", "vendor_nonincentivized", "vendor_self", "vendor_self_nonincentivized", "vendor_self_sendoso" ], "count": 21 } ``` ### Limitations - Reviewer job titles and avatar URLs are not available. - `industry` and `role` are returned as numeric category codes with a human-readable label for common values only; they are not available as filters. - `country` and `region` are not available as filters because their values are not normalized across languages. Use `primaryRegion` (`Americas` / `Asia Pacific` / `EMEA`) for consistent geography filtering. - `similarTo` returns at most 1,000 reviews per run (a single relevance-ranked fetch; it does not paginate). - A product's `reviewCount` reflects G2's total across all reviews; review scraping and analytics return only public, approved reviews, so their counts are typically lower. - Some reviews have unstructured text (no clear pros/cons/benefits separation). # Actor input Schema ## `products` (type: `array`): G2 product URLs (e.g. https://www.g2.com/products/slack/reviews) or just slugs (e.g. slack). Also accepts category URLs. ## `maxReviewsPerProduct` (type: `integer`): Maximum number of reviews to scrape per product. Set to 0 for no limit (all reviews). ## `sortBy` (type: `string`): How to sort reviews. ## `ratings` (type: `array`): Only include reviews with these star ratings. Leave empty for all ratings. ## `companySegment` (type: `array`): Filter by company size. ## `dateFrom` (type: `string`): ISO date, only reviews submitted on or after this date. ## `dateTo` (type: `string`): ISO date, only reviews submitted on or before this date. ## `primaryRegions` (type: `array`): Filter by reviewer primary region. ## `sourceTypes` (type: `array`): Filter by how the review was collected (e.g. organic, g2\_incentivized). Discover values via enumFields: source\_type. ## `responseTypes` (type: `array`): Filter by review medium (e.g. text, video). Discover values via enumFields: response\_type. ## `loveThemes` (type: `array`): Filter by what reviewers liked (e.g. Automation, Analytics). Discover values via enumFields: love\_theme\_humanized. ## `hateThemes` (type: `array`): Filter by what reviewers disliked. Discover values via enumFields: hate\_theme\_humanized. ## `switchingThemes` (type: `array`): Filter by why reviewers switched products. Discover values via enumFields: switching\_theme\_humanized. ## `discounts` (type: `array`): Filter by reported discount. Discover values via enumFields: discount. ## `reviewSources` (type: `array`): Filter by review source channel. Discover values via enumFields: review\_source. ## `reviewSearch` (type: `string`): Full-text search within review text. When used without products, searches globally across all products. ## `search` (type: `string`): Find products by keyword search (e.g. 'project management'). ## `category` (type: `string`): Find products in a G2 category (e.g. 'CRM', 'Project Management'). ## `vendor` (type: `string`): Find all products by vendor name (e.g. 'Salesforce'). ## `maxProducts` (type: `integer`): Maximum products to scrape in search/category/vendor mode. ## `compare` (type: `array`): Compare products side-by-side with analytics (e.g. \['slack', 'teams', 'discord']). ## `analytics` (type: `boolean`): Return aggregation analytics per product instead of individual reviews. ## `enumFields` (type: `array`): Return the distinct values for these review facets (saved to the metadata dataset) instead of scraping reviews. Use the values to populate the reviewer-facet filters. ## `similarTo` (type: `string`): Find reviews similar to this text. ## `reviewIds` (type: `array`): Fetch specific reviews by their G2 review ID. ## `maxReviews` (type: `integer`): Max total reviews for global search or similar mode. Set to 0 for no limit. ## `collapseByProduct` (type: `boolean`): Deduplicate global search results to one review per product. ## `includeDiscussions` (type: `boolean`): Also fetch Q\&A discussion threads per product. ## `includeHighlights` (type: `boolean`): Include highlighted matching snippets when using reviewSearch. ## `includeNonPublic` (type: `boolean`): Include non-public and rejected reviews. ## Actor input object example ```json { "products": [ "https://www.g2.com/products/slack/reviews" ], "maxReviewsPerProduct": 20, "sortBy": "DATE_DESC", "ratings": [ "1", "2", "3", "4", "5" ], "maxProducts": 10, "analytics": false, "maxReviews": 100, "collapseByProduct": false, "includeDiscussions": false, "includeHighlights": true, "includeNonPublic": false } ``` # 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 = { "products": [ "https://www.g2.com/products/slack/reviews" ] }; // Run the Actor and wait for it to finish const run = await client.actor("kaix/g2-scraper").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 = { "products": ["https://www.g2.com/products/slack/reviews"] } # Run the Actor and wait for it to finish run = client.actor("kaix/g2-scraper").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 '{ "products": [ "https://www.g2.com/products/slack/reviews" ] }' | apify call kaix/g2-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kaix/g2-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "G2 Scraper - Reviews, Products, Analytics & Discussions", "description": "🔥 ~$0.05/1K reviews 🔥 Scrape G2.com software reviews, products, analytics, comparisons, and discussions. Faceted filtering, facet-value discovery, 72 review fields, NLP sentiment, switching intelligence.", "version": "0.1", "x-build-id": "09Pt0q1i9kcpBy5Jy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kaix~g2-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kaix-g2-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/kaix~g2-scraper/runs": { "post": { "operationId": "runs-sync-kaix-g2-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/kaix~g2-scraper/run-sync": { "post": { "operationId": "run-sync-kaix-g2-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", "properties": { "products": { "title": "Product URLs or slugs", "type": "array", "description": "G2 product URLs (e.g. https://www.g2.com/products/slack/reviews) or just slugs (e.g. slack). Also accepts category URLs.", "items": { "type": "string" } }, "maxReviewsPerProduct": { "title": "Max reviews per product", "minimum": 0, "type": "integer", "description": "Maximum number of reviews to scrape per product. Set to 0 for no limit (all reviews).", "default": 20 }, "sortBy": { "title": "Sort reviews by", "enum": [ "DATE_DESC", "DATE_ASC", "RATING_DESC", "RATING_ASC", "HELPFUL_DESC", "G2_DEFAULT" ], "type": "string", "description": "How to sort reviews.", "default": "DATE_DESC" }, "ratings": { "title": "Star ratings to include", "type": "array", "description": "Only include reviews with these star ratings. Leave empty for all ratings.", "items": { "type": "string", "enum": [ "1", "2", "3", "4", "5" ], "enumTitles": [ "1 star", "2 stars", "3 stars", "4 stars", "5 stars" ] }, "default": [ "1", "2", "3", "4", "5" ] }, "companySegment": { "title": "Company size filter", "type": "array", "description": "Filter by company size.", "items": { "type": "string", "enum": [ "small_business", "mid_market", "enterprise" ], "enumTitles": [ "Small Business", "Mid-Market", "Enterprise" ] } }, "dateFrom": { "title": "Reviews from date", "type": "string", "description": "ISO date, only reviews submitted on or after this date." }, "dateTo": { "title": "Reviews to date", "type": "string", "description": "ISO date, only reviews submitted on or before this date." }, "primaryRegions": { "title": "Primary region", "type": "array", "description": "Filter by reviewer primary region.", "items": { "type": "string", "enum": [ "Americas", "Asia Pacific", "EMEA" ], "enumTitles": [ "Americas", "Asia Pacific", "EMEA" ] } }, "sourceTypes": { "title": "Review source type", "type": "array", "description": "Filter by how the review was collected (e.g. organic, g2_incentivized). Discover values via enumFields: source_type.", "items": { "type": "string" } }, "responseTypes": { "title": "Response type", "type": "array", "description": "Filter by review medium (e.g. text, video). Discover values via enumFields: response_type.", "items": { "type": "string" } }, "loveThemes": { "title": "Loved themes", "type": "array", "description": "Filter by what reviewers liked (e.g. Automation, Analytics). Discover values via enumFields: love_theme_humanized.", "items": { "type": "string" } }, "hateThemes": { "title": "Hated themes", "type": "array", "description": "Filter by what reviewers disliked. Discover values via enumFields: hate_theme_humanized.", "items": { "type": "string" } }, "switchingThemes": { "title": "Switching themes", "type": "array", "description": "Filter by why reviewers switched products. Discover values via enumFields: switching_theme_humanized.", "items": { "type": "string" } }, "discounts": { "title": "Discount", "type": "array", "description": "Filter by reported discount. Discover values via enumFields: discount.", "items": { "type": "string" } }, "reviewSources": { "title": "Review source channel", "type": "array", "description": "Filter by review source channel. Discover values via enumFields: review_source.", "items": { "type": "string" } }, "reviewSearch": { "title": "Search within reviews", "type": "string", "description": "Full-text search within review text. When used without products, searches globally across all products." }, "search": { "title": "Search products", "type": "string", "description": "Find products by keyword search (e.g. 'project management')." }, "category": { "title": "Browse by category", "type": "string", "description": "Find products in a G2 category (e.g. 'CRM', 'Project Management')." }, "vendor": { "title": "Browse by vendor", "type": "string", "description": "Find all products by vendor name (e.g. 'Salesforce')." }, "maxProducts": { "title": "Max products", "minimum": 1, "type": "integer", "description": "Maximum products to scrape in search/category/vendor mode.", "default": 10 }, "compare": { "title": "Compare products", "type": "array", "description": "Compare products side-by-side with analytics (e.g. ['slack', 'teams', 'discord']).", "items": { "type": "string" } }, "analytics": { "title": "Analytics mode", "type": "boolean", "description": "Return aggregation analytics per product instead of individual reviews.", "default": false }, "enumFields": { "title": "Discover facet values", "type": "array", "description": "Return the distinct values for these review facets (saved to the metadata dataset) instead of scraping reviews. Use the values to populate the reviewer-facet filters.", "items": { "type": "string", "enum": [ "source_type", "response_type", "love_theme_humanized", "hate_theme_humanized", "switching_theme_humanized", "discount", "review_source" ] } }, "similarTo": { "title": "Find similar reviews", "type": "string", "description": "Find reviews similar to this text." }, "reviewIds": { "title": "Fetch reviews by ID", "type": "array", "description": "Fetch specific reviews by their G2 review ID.", "items": { "type": "string" } }, "maxReviews": { "title": "Max reviews (global/similar search)", "minimum": 0, "type": "integer", "description": "Max total reviews for global search or similar mode. Set to 0 for no limit.", "default": 100 }, "collapseByProduct": { "title": "One review per product", "type": "boolean", "description": "Deduplicate global search results to one review per product.", "default": false }, "includeDiscussions": { "title": "Include discussions", "type": "boolean", "description": "Also fetch Q&A discussion threads per product.", "default": false }, "includeHighlights": { "title": "Include search highlights", "type": "boolean", "description": "Include highlighted matching snippets when using reviewSearch.", "default": true }, "includeNonPublic": { "title": "Include non-public reviews", "type": "boolean", "description": "Include non-public and rejected reviews.", "default": false } } }, "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 } } } } } } } } } } ```