# Brand Reputation Report — Reviews, Trends & News Intelligence (`jadey_orbit/brand-reputation-report`) Actor One call, one answer: full reputation intelligence for any company — review trajectory, complaint themes, rising 'scam' search queries, news presence. Built for agents and due diligence. - **URL**: https://apify.com/jadey\_orbit/brand-reputation-report.md - **Developed by:** [Matt Sparks](https://apify.com/jadey_orbit) (community) - **Categories:** Business, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $250.00 / 1,000 reputation report delivereds 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Brand Reputation Report — Reviews, Trends & News Intelligence One call, one answer. Give it a company domain and get a **complete reputation intelligence report**: review trajectory, complaint themes, search-trend red flags, and news presence — computed from three independent sources and distilled into actionable risk signals. Stop paying for 5,000 raw review rows you still have to analyze. This actor does the analysis. ### What's in a report? - **Profile**: TrustScore, star rating, total & last-12-month review volume, categories, claimed status - **Review trajectory**: average rating (analyzed vs last 90 days — is it getting better or worse?), rating distribution, negative share, company reply rate, review velocity - **Complaint & praise themes**: the specific topics customers mention most in negative and positive reviews ("contacted support", "hidden fees", "fast delivery"), mined from review text - **Search signals**: 12-month search-interest trend (rising/stable/declining), rising related queries, and **red-flag queries** — when " scam", " refund", or " alternative" starts rising, you know before it hits the news - **News presence**: 30-day article count, negative-headline count, latest headlines - **Risk signals**: machine-readable flags like `RATING_DECLINING`, `HIGH_NEGATIVE_SHARE`, `SEARCH_RED_FLAGS`, `UNRESPONSIVE` — or `NO_MAJOR_RISK_SIGNALS` ### Example (real output) ```json { "companyDomain": "example-saas.com", "profile": { "trustScore": 2.3, "totalReviews": 417 }, "reviewAnalysis": { "avgRatingAnalyzed": 2.28, "avgRatingLast90Days": 1.95, "negativeShare": 0.64, "replyRate": 0, "complaintThemes": [ { "term": "contacted support", "mentions": 9 }, { "term": "business practices", "mentions": 5 } ] }, "searchSignals": { "interestTrend": "stable", "redFlagQueries": [] }, "newsPresence": { "articleCount30Days": 100, "negativeHeadlines": 10 }, "riskSignals": [ "LOW_TRUST_SCORE: TrustScore 2.3/5", "HIGH_NEGATIVE_SHARE: 64% of recent reviews are 1–2★", "UNRESPONSIVE: company replies to <10% of reviews despite high negativity", "NEGATIVE_PRESS: 10 headline(s) matching risk terms in 30 days" ] } ```` ### Pricing | Event | Price | When charged | |---|---|---| | Actor start | $0.02 | Once per run | | Report generated | $0.25 | Per company report delivered (failed lookups are never charged) | Compare: assembling this yourself means 3 scraper subscriptions + analysis code. One report here costs a quarter. ### Who uses this - **Due diligence** — vet vendors, partners, acquisition targets in one call - **Sales & lead qualification** — walk into calls knowing the prospect's pain points - **Agencies** — reputation snapshots for clients and prospects at scale - **Competitive intelligence** — track competitors' complaint themes quarterly - **AI agents** — a single MCP-callable tool that answers "is this company trustworthy?" with structured evidence ([Apify MCP server](https://docs.apify.com/platform/integrations/mcp)) ### Input ```json { "companies": ["wise.com", "notion.so"], "maxReviewsAnalyzed": 200 } ``` ### Notes - Analysis is fully deterministic — same inputs produce same outputs, no LLM hallucination risk in the numbers. - Sources: public Trustpilot pages, Google Trends, Google News RSS. Only publicly available data. - Companies without a Trustpilot profile return an error item (not charged). - Want more sources (app-store reviews, Reddit, BBB), competitor comparison mode, or webhook alerts on signal changes? Open an issue in the **Issues** tab. # Actor input Schema ## `companies` (type: `array`): Company websites (e.g. wise.com) or Trustpilot review URLs. One report is generated per company. ## `maxReviewsAnalyzed` (type: `integer`): How many recent reviews to analyze for themes and trajectory (more = deeper analysis, slower run). ## `includeTrends` (type: `boolean`): Search-interest trajectory and rising related queries (including scam/refund/lawsuit red-flag queries). ## `includeNews` (type: `boolean`): Recent news headlines mentioning the brand (Google News). ## `proxyConfiguration` (type: `object`): Proxy settings. Residential recommended. ## Actor input object example ```json { "companies": [ "wise.com" ], "maxReviewsAnalyzed": 200, "includeTrends": true, "includeNews": true, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 = { "companies": [ "wise.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("jadey_orbit/brand-reputation-report").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 = { "companies": ["wise.com"] } # Run the Actor and wait for it to finish run = client.actor("jadey_orbit/brand-reputation-report").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 '{ "companies": [ "wise.com" ] }' | apify call jadey_orbit/brand-reputation-report --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jadey_orbit/brand-reputation-report", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Brand Reputation Report — Reviews, Trends & News Intelligence", "description": "One call, one answer: full reputation intelligence for any company — review trajectory, complaint themes, rising 'scam' search queries, news presence. Built for agents and due diligence.", "version": "0.1", "x-build-id": "9g2ZwDLuBlz2Sf0g7" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jadey_orbit~brand-reputation-report/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jadey_orbit-brand-reputation-report", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jadey_orbit~brand-reputation-report/runs": { "post": { "operationId": "runs-sync-jadey_orbit-brand-reputation-report", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jadey_orbit~brand-reputation-report/run-sync": { "post": { "operationId": "run-sync-jadey_orbit-brand-reputation-report", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Company websites (e.g. wise.com) or Trustpilot review URLs. One report is generated per company.", "items": { "type": "string" } }, "maxReviewsAnalyzed": { "title": "Reviews analyzed per company", "minimum": 20, "maximum": 1000, "type": "integer", "description": "How many recent reviews to analyze for themes and trajectory (more = deeper analysis, slower run).", "default": 200 }, "includeTrends": { "title": "Include Google Trends signals", "type": "boolean", "description": "Search-interest trajectory and rising related queries (including scam/refund/lawsuit red-flag queries).", "default": true }, "includeNews": { "title": "Include news presence", "type": "boolean", "description": "Recent news headlines mentioning the brand (Google News).", "default": true }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy settings. Residential recommended.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```