# Programmatic SEO Opportunity Mapper (`monty15/programmatic-seo-opportunity-mapper`) Actor Turn competitor sitemaps into a scored, prioritized programmatic-SEO opportunity matrix — deterministic title/meta/slug suggestions, schema type, and optional AI-citability scoring. No API key required. - **URL**: https://apify.com/monty15/programmatic-seo-opportunity-mapper.md - **Developed by:** [Monty](https://apify.com/monty15) (community) - **Categories:** SEO tools, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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 ## Programmatic SEO Opportunity Mapper Turn competitor sitemaps into a scored, prioritized programmatic-SEO opportunity matrix — with deterministic title, meta description, slug, schema type, and optional AI-citability scoring. No API key required. ### What it does 1. Crawls your target domain's sitemap to build your current coverage set. 2. Crawls each competitor's sitemap, filters obvious ecommerce product/SKU URLs by default, and clusters their SEO/editorial page families using Jaccard similarity (same engine as the Competitor Sitemap Content Gap Analyzer). 3. Computes the coverage gap: competitor families you don't yet cover. 4. Scores and ranks each opportunity with a deterministic heuristic score (`priority_heuristic`) and action (`auto` / `review` / `skip`). 5. Generates a starter title, meta description, URL slug, and Schema.org type for each opportunity — deterministically, no LLM. 6. Optionally fetches the top competitor URL for each row and attaches an AI-citability score (0–100) and grade (A–D) using the same adapter as the GEO Readiness Auditor. ### Use after `apify/google-search-scraper` Wave-2 MVP: sitemap-only. SERP enrichment (real volume / difficulty / competitor URLs from `apify/google-search-scraper`) back-fills in Wave 3. ### Inputs | Field | Type | Default | Notes | |---|---|---|---| | `targetDomain` | string | — | **Required.** Your domain. | | `competitorDomains` | array | — | **Required.** 1–10 competitor domains. | | `maxRows` | integer | 500 | Hard cap on output rows. | | `maxUrlsPerDomain` | integer | 1000 | Hard cap on sitemap URLs read per domain before filtering. | | `urlFocus` | string | `content` | `content` filters obvious product/category/SKU pages for ecommerce SEO/editorial opportunities. Use `all` only when you intentionally want product/assortment URL gaps. | | `crawlPages` | boolean | false | Fetch pages for richer topics (slower). | | `similarityThreshold` | number | 0.6 | Jaccard threshold to merge families. | | `includeAIGeoReadiness` | boolean | false | Attach citability score/grade per row. | ### Output (one row per opportunity) ```json { "topic": "best running shoes for men", "keyword": "best running shoes for men", "modifier": "best", "page_type": "comparison", "search_intent": "commercial", "competitor_urls": ["https://competitor-a.com/best-running-shoes-for-men"], "source_urls": ["competitor-a.com"], "missing_from_target": true, "priority_heuristic": 230.0, "priority_action": "auto", "est_effort_hours": 3, "pseo_template_suggestion": "comparison-guide", "title": "Best Running Shoes for Men - example.com", "meta_description": "Compare best running shoes for men with expert analysis...", "recommended_slug": "best-running-shoes-for-men", "internal_link_targets": ["...sibling families..."], "schema_type": "Article", "member_topics": ["best running shoes for men", "best running shoes for women"], "topic_count": 2, "provenance": {"source_url": "...", "extractor_method": "sitemap_xml", "status": "ok", "caveats": ["..."]}, "status": "ok" } ```` Rows with `status != ok` (blocked / not\_found / timeout) are reconcilable failures, not run crashes. ### Promises - A ranked, deduped opportunity matrix derived from your and competitor sitemaps. - Ecommerce-safe default focus: product/category/SKU pages are filtered unless `urlFocus=all`. - Starter title / meta description / slug / schema type for every row. - Provenance on every row — you can trace every recommendation to a source URL. - No-key run path: runs completely without any external API. - Robots honored before any third-party fetch; per-domain delay ≥ 1 s. ### Non-promises - `priority_heuristic` is a deterministic keyword heuristic — **not** a search-volume or difficulty ranking. No P1–P4 tiers are shown without real volume data. - This actor does not scrape Google. Bring a `apify/google-search-scraper` dataset for SERP enrichment (Wave 3). - Difficulty without provider data is omitted, labeled as such. # Actor input Schema ## `targetDomain` (type: `string`): The domain you want to grow. Its sitemap defines what you already cover. ## `competitorDomains` (type: `array`): 1–10 competitor domains. Their sitemaps are crawled to find opportunities you are missing. ## `maxRows` (type: `integer`): Hard cap on output rows (bounds compute and cost). ## `maxUrlsPerDomain` (type: `integer`): Hard cap on sitemap URLs read per domain before filtering. ## `urlFocus` (type: `string`): Default content mode filters obvious ecommerce product/category/SKU pages so results emphasize SEO/editorial opportunities. Use all only when you intentionally want assortment/product URL gaps. ## `crawlPages` (type: `boolean`): When on, fetch each page for titles/headings instead of inferring topics from URL slugs. Slower but more accurate. ## `similarityThreshold` (type: `number`): Jaccard similarity (0–1) required to merge two topics into one family. Lower = bigger families. ## `includeAIGeoReadiness` (type: `boolean`): When on, fetch the top competitor URL for each opportunity and attach a citability score (0–100) and grade (A–D) using the same adapter as the GEO Readiness Auditor. Robots-honored, capped at 50 page fetches. ## Actor input object example ```json { "targetDomain": "example.com", "competitorDomains": [ "competitor-a.com", "competitor-b.com" ], "maxRows": 500, "maxUrlsPerDomain": 1000, "urlFocus": "content", "crawlPages": false, "similarityThreshold": 0.6, "includeAIGeoReadiness": 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 = { "targetDomain": "example.com", "competitorDomains": [ "competitor-a.com", "competitor-b.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("monty15/programmatic-seo-opportunity-mapper").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 = { "targetDomain": "example.com", "competitorDomains": [ "competitor-a.com", "competitor-b.com", ], } # Run the Actor and wait for it to finish run = client.actor("monty15/programmatic-seo-opportunity-mapper").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 '{ "targetDomain": "example.com", "competitorDomains": [ "competitor-a.com", "competitor-b.com" ] }' | apify call monty15/programmatic-seo-opportunity-mapper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=monty15/programmatic-seo-opportunity-mapper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Programmatic SEO Opportunity Mapper", "description": "Turn competitor sitemaps into a scored, prioritized programmatic-SEO opportunity matrix — deterministic title/meta/slug suggestions, schema type, and optional AI-citability scoring. No API key required.", "version": "1.0", "x-build-id": "cC51YIEZ0ne4piI0r" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/monty15~programmatic-seo-opportunity-mapper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-monty15-programmatic-seo-opportunity-mapper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/monty15~programmatic-seo-opportunity-mapper/runs": { "post": { "operationId": "runs-sync-monty15-programmatic-seo-opportunity-mapper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/monty15~programmatic-seo-opportunity-mapper/run-sync": { "post": { "operationId": "run-sync-monty15-programmatic-seo-opportunity-mapper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "targetDomain", "competitorDomains" ], "properties": { "targetDomain": { "title": "Your domain", "type": "string", "description": "The domain you want to grow. Its sitemap defines what you already cover." }, "competitorDomains": { "title": "Competitor domains", "type": "array", "description": "1–10 competitor domains. Their sitemaps are crawled to find opportunities you are missing.", "items": { "type": "string" } }, "maxRows": { "title": "Max opportunity rows", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Hard cap on output rows (bounds compute and cost).", "default": 500 }, "maxUrlsPerDomain": { "title": "Max sitemap URLs per domain", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Hard cap on sitemap URLs read per domain before filtering.", "default": 1000 }, "urlFocus": { "title": "URL focus", "enum": [ "content", "all" ], "type": "string", "description": "Default content mode filters obvious ecommerce product/category/SKU pages so results emphasize SEO/editorial opportunities. Use all only when you intentionally want assortment/product URL gaps.", "default": "content" }, "crawlPages": { "title": "Fetch each page (richer topics)", "type": "boolean", "description": "When on, fetch each page for titles/headings instead of inferring topics from URL slugs. Slower but more accurate.", "default": false }, "similarityThreshold": { "title": "Clustering similarity threshold", "minimum": 0, "maximum": 1, "type": "number", "description": "Jaccard similarity (0–1) required to merge two topics into one family. Lower = bigger families.", "default": 0.6 }, "includeAIGeoReadiness": { "title": "Include AI / GEO citability score", "type": "boolean", "description": "When on, fetch the top competitor URL for each opportunity and attach a citability score (0–100) and grade (A–D) using the same adapter as the GEO Readiness Auditor. Robots-honored, capped at 50 page fetches.", "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 } } } } } } } } } } ```