# App Review Competitive Report — Head-to-Head Comparison (`nexgenwatch/app-review-competitive-report`) Actor - **URL**: https://apify.com/nexgenwatch/app-review-competitive-report.md - **Developed by:** [NexGen Watch](https://apify.com/nexgenwatch) (community) - **Categories:** Business, Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $16,750.00 / 1,000 competitive reports 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/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 ## App Review Competitive Report — Head-to-Head Sentiment, Themes, Complaints **Stop paying $50–100+/month for a review-intelligence subscription to compare your app against the competition.** This actor delivers a full **head-to-head competitive read across up to 5 apps** — the same deep per-app analysis *plus* the positioning layer — **per report, on demand, with no subscription.** Apps in, one competitive intelligence report out. | | Typical review-intelligence SaaS | App Review Competitive Report | |---|---|---| | Pricing | **$50–100+/month**, every month | **$25.00 / report** (FREE tier), pay only when you run | | Scope | One seat, rate-limited comparisons | **Up to 5 apps compared head-to-head, per report** | | Commitment | Annual/monthly lock-in | None — per report | | Break-even | — | Run a competitive read **every week (~$100/mo at FREE, less on volume tiers)** — and only in the weeks you actually need it | If a PM, ASO consultant, or agency pulls **one competitive read per week**, that's ~$100/month at the FREE tier (and less on BRONZE/SILVER/GOLD) — versus $50–100+/month for an always-on seat you rarely max out, per analyst. One report already covers a 5-app landscape that a single-app tool would bill you five runs for. ### What you get in one report Feed it **2 to 5 apps** (each `app_id` + `store`, optional `country`/`company_label`). For **every app** it fetches up to **1,000 public reviews** (logged-out, public data only) and runs the full **ngd-lexicon-v1** deep analysis — then adds the head-to-head layer: **Per app (same depth as the single-app deep report):** - **Full sentiment breakdown** — positive / neutral / negative split, average sentiment score, average star rating - **Theme clustering** — the terms and phrases reviewers actually use, ranked by mentions - **Complaint ranking** — negative-review clusters ranked by frequency, each with its share of negatives and a real example quote - **Feature-request extraction** — reviews that ask for something, clustered into the most-requested asks - **Trend vs prior period** — automatic median split, with sentiment and rating deltas **Head-to-head positioning (across all apps):** - **Relative sentiment leaderboard** — apps ranked by sentiment score, positive %, negative %, and average rating - **Shared vs unique themes** — what reviewers raise across the whole category vs what's specific to one app - **Shared vs unique complaints** — the pain everyone shares vs the pain that's yours (or your competitor's) alone - **Winner by dimension** — who leads on sentiment, rating, fewest complaints, developer responsiveness, and raised demand - **Overall composite positioning** — a single ranked standing across the leaderboard dimensions - **Rendered markdown competitive brief** — the whole comparison as a readable report (a dataset field *and* a key-value-store record), ready to paste into a deck, battlecard, or ticket ### Output - One **`competitive_summary`** dataset record — the full head-to-head report (leaderboard, shared/unique diffs, winners, composite ranking, roster) plus the rendered markdown brief. - One **`app_report`** dataset record per compared app — the full deep analysis for that app. - Markdown briefs are also written to the key-value store (`COMPETITIVE_` for the comparison, `REPORT___` per app). ### Input | Field | Required | Description | |---|---|---| | `targets` | yes | Array of **2 to 5** apps. Each: `app_id` (Apple numeric id or Google Play package), `store` (`apple` or `google_play`), optional `country` (default `us`), `language` (Google Play, default `en`), `company_label` (display name) | | `max_reviews` | no | Cap on public reviews fetched **per app** (default/max 1000) | | `max_themes` | no | Max theme and complaint clusters per app (default 12) | ### Method — deterministic, transparent, model-included Analysis runs the **ngd-lexicon-v1** engine: a transparent lexicon plus a rating prior — the identical engine used across the review-intelligence fleet, so scores are comparable app-to-app. It is fully **deterministic** — the same reviews always produce the same competitive report. **No external LLM, no API key to bring, no "AI" black box.** The model is included in the price. ### Pricing - **Actor start:** $0.05 (one-time, platform-reserved). - **`competitive_report`:** **$25.00** per report at the FREE tier (BRONZE $22.50 · SILVER $20.00 · GOLD $16.75). Charged **exactly once, only after the full competitive report over at least 2 apps is successfully built and delivered.** If fewer than 2 apps yield reviews, or analysis can't run, the run fails and **you are charged nothing.** ### Notes - Public, logged-out data only. No login, no private endpoints. - Cost-bounded: memory/time caps, a bounded per-page request-attempt budget, and a hard per-app review/output cap. - An app that returns no public reviews is skipped and listed under `skipped_targets`; the report still runs as long as at least 2 apps have data. # Actor input Schema ## `targets` (type: `array`): The apps to compare head-to-head. Provide between 2 and 5 targets. Each target is an object with app_id and store, plus optional country, language and company_label. ## `max_reviews` (type: `integer`): Hard cap on public reviews fetched for EACH app (max 1000). ## `max_themes` (type: `integer`): Maximum theme and complaint clusters returned per app. ## `proxy_configuration` (type: `object`): Optional Apify proxy settings; a fresh session is requested for every retry. ## Actor input object example ```json { "targets": [ { "app_id": "284882215", "store": "apple", "country": "us", "company_label": "Facebook" }, { "app_id": "389801252", "store": "apple", "country": "us", "company_label": "Instagram" } ], "max_reviews": 1000, "max_themes": 12, "proxy_configuration": { "useApifyProxy": true } } ```` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "targets": [ { "app_id": "284882215", "store": "apple", "country": "us", "company_label": "Facebook" }, { "app_id": "389801252", "store": "apple", "country": "us", "company_label": "Instagram" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("nexgenwatch/app-review-competitive-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 = { "targets": [ { "app_id": "284882215", "store": "apple", "country": "us", "company_label": "Facebook", }, { "app_id": "389801252", "store": "apple", "country": "us", "company_label": "Instagram", }, ] } # Run the Actor and wait for it to finish run = client.actor("nexgenwatch/app-review-competitive-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 '{ "targets": [ { "app_id": "284882215", "store": "apple", "country": "us", "company_label": "Facebook" }, { "app_id": "389801252", "store": "apple", "country": "us", "company_label": "Instagram" } ] }' | apify call nexgenwatch/app-review-competitive-report --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgenwatch/app-review-competitive-report", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "App Review Competitive Report — Head-to-Head Comparison", "version": "0.1", "x-build-id": "prViknlyMlrtOadsA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgenwatch~app-review-competitive-report/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgenwatch-app-review-competitive-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgenwatch~app-review-competitive-report/runs": { "post": { "operationId": "runs-sync-nexgenwatch-app-review-competitive-report", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgenwatch~app-review-competitive-report/run-sync": { "post": { "operationId": "run-sync-nexgenwatch-app-review-competitive-report", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "targets" ], "properties": { "targets": { "title": "Apps to compare (2 to 5)", "type": "array", "description": "The apps to compare head-to-head. Provide between 2 and 5 targets. Each target is an object with app_id and store, plus optional country, language and company_label.", "items": { "type": "object", "properties": { "app_id": { "title": "App ID", "type": "string", "description": "Apple: the numeric track id (e.g. 284882215). Google Play: the package name (e.g. com.spotify.music)." }, "store": { "title": "Store", "type": "string", "description": "Which public store to pull reviews from: apple or google_play.", "enum": [ "apple", "google_play" ] }, "country": { "title": "Country", "type": "string", "description": "Two-letter storefront country code (default us)." }, "language": { "title": "Language", "type": "string", "description": "Two-letter language code, used for Google Play (default en)." }, "company_label": { "title": "Company / app label", "type": "string", "description": "Optional display label for this app in the competitive report (e.g. the company or product name)." } }, "required": [ "app_id", "store" ] } }, "max_reviews": { "title": "Maximum reviews per app", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Hard cap on public reviews fetched for EACH app (max 1000).", "default": 1000 }, "max_themes": { "title": "Maximum themes / complaints per app", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum theme and complaint clusters returned per app.", "default": 12 }, "proxy_configuration": { "title": "Proxy configuration", "type": "object", "description": "Optional Apify proxy settings; a fresh session is requested for every retry.", "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 } } } } } } } } } } ```