# Agency Website Opportunity Audit (`digital-ai-lab.de/agency-website-opportunity-audit`) Actor Audit websites for lead-capture gaps, trust signals, conversion blockers, automation opportunities, and agency-ready pitch angles. - **URL**: https://apify.com/digital-ai-lab.de/agency-website-opportunity-audit.md - **Developed by:** [Digital AI Lab](https://apify.com/digital-ai-lab.de) (community) - **Categories:** Lead generation, Automation, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $50.00 / 1,000 website audits 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 ## Agency Website Opportunity Audit Audit websites for lead-capture gaps, trust signals, conversion blockers, automation opportunities, and agency-ready pitch angles. This Actor is built for web agencies, SEO consultants, RevOps consultants, automation agencies, and freelancers who need a fast first-pass audit before prospecting or client discovery calls. It crawls a homepage plus high-signal same-domain pages such as contact, pricing, services, about, customers, and booking pages. It returns one dataset item per website with an opportunity score, grade, issues, strengths, top fixes, automation opportunities, a pitch angle, optional outreach email, and a Markdown audit. Typical workflow: run 5-100 prospect URLs, export the dataset to a CRM or Google Sheet, sort by opportunity score, and use the Markdown audit as sales-call preparation. ### Best use cases - Find concrete website improvement opportunities before an agency sales call. - Score prospect websites for lead generation and conversion potential. - Generate quick audit notes for outbound emails. - Identify missing analytics, lead capture, trust proof, chat, and automation signals. - Feed structured website-audit data into CRMs, Google Sheets, Airtable, Make, Zapier, n8n, or AI agents. ### Input ```json { "startUrls": [ "https://www.apify.com", "https://example.com" ], "auditGoal": "lead-generation", "targetIndustry": "B2B services", "maxPagesPerSite": 3, "includePitchEmail": true, "includeRawSignals": false } ```` ### Output Each result is pushed to the default dataset: ```json { "url": "https://example.com/", "status": "ok", "auditGoal": "lead-generation", "targetIndustry": "B2B services", "companyName": "Example Studio", "opportunityScore": 82, "grade": "B", "primaryOpportunity": "Lead capture path is weak or missing", "issues": ["No visible contact form or booking path found"], "strengths": ["Primary call to action is visible"], "topFixes": ["Add a low-friction lead capture path: short form, booking link, or quote request"], "automationOpportunities": ["Lead capture workflow: form or booking intake routed to CRM and email follow-up"], "agencyPitchAngle": "Example Studio already has enough public website signal to start a useful audit conversation...", "pitchEmail": { "subject": "Example Studio website - quick opportunity", "body": "Hi,\n\nI reviewed Example Studio's public website..." }, "auditMarkdown": "## Example Studio - Website Opportunity Audit\n\n...", "confidence": 0.68, "pagesAnalyzed": ["https://example.com/", "https://example.com/contact"], "contacts": { "emails": [], "socialLinks": [] } } ``` ### What it checks - Primary CTA visibility - Contact form or booking path - Public email or phone signal - Analytics and conversion measurement - Chat or marketing automation signal - Trust, legal, customer, or proof content - Structured data signal - Thin content and noindex signals ### Pricing This Actor is designed for pay-per-event pricing. One charged event equals one website opportunity audit written to the default dataset. The primary event is `Website audit`. ### Tips for better results - Use canonical homepage URLs. - Set `maxPagesPerSite` to 3-5 for quick prospect audits. - Increase `maxPagesPerSite` when auditing larger websites. - Use a specific `targetIndustry` to make recommendations and pitch language more relevant. - Review pitch emails before sending. They are meant as editable starting points. - Works well with Google Sheets, Airtable, n8n, Make, Zapier, CRMs, and AI-agent workflows. ### Search keywords Website audit API, prospect website audit, lead capture audit, agency prospect research, conversion audit, website automation audit, CRM enrichment. ### Limitations - This Actor uses public website signals only. - JavaScript-heavy websites may expose limited static HTML without browser rendering. - Audit scores are deterministic heuristics, not a full UX, SEO, or legal review. - This Actor should not be used for spam. It is designed for legitimate sales preparation, website auditing, and agency workflows. # Actor input Schema ## `startUrls` (type: `array`): One or more websites to audit. Use canonical homepage URLs when possible. ## `auditGoal` (type: `string`): Choose the primary agency or sales use case. ## `targetIndustry` (type: `string`): Optional industry context used in recommendations and pitch language. ## `maxPagesPerSite` (type: `integer`): Maximum number of same-domain pages to fetch for each website. ## `includePitchEmail` (type: `boolean`): Generate a short agency outreach email based on detected website gaps. ## `includeRawSignals` (type: `boolean`): Include sampled page text and extracted technical signals in each dataset item. ## Actor input object example ```json { "startUrls": [ "https://www.apify.com" ], "auditGoal": "lead-generation", "targetIndustry": "B2B services", "maxPagesPerSite": 3, "includePitchEmail": true, "includeRawSignals": false } ``` # 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 = { "startUrls": [ "https://www.apify.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("digital-ai-lab.de/agency-website-opportunity-audit").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 = { "startUrls": ["https://www.apify.com"] } # Run the Actor and wait for it to finish run = client.actor("digital-ai-lab.de/agency-website-opportunity-audit").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 '{ "startUrls": [ "https://www.apify.com" ] }' | apify call digital-ai-lab.de/agency-website-opportunity-audit --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=digital-ai-lab.de/agency-website-opportunity-audit", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Agency Website Opportunity Audit", "description": "Audit websites for lead-capture gaps, trust signals, conversion blockers, automation opportunities, and agency-ready pitch angles.", "version": "0.1", "x-build-id": "7Y954fmrNRBCIqH2b" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/digital-ai-lab.de~agency-website-opportunity-audit/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-digital-ai-lab.de-agency-website-opportunity-audit", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/digital-ai-lab.de~agency-website-opportunity-audit/runs": { "post": { "operationId": "runs-sync-digital-ai-lab.de-agency-website-opportunity-audit", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/digital-ai-lab.de~agency-website-opportunity-audit/run-sync": { "post": { "operationId": "run-sync-digital-ai-lab.de-agency-website-opportunity-audit", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Website URLs", "minItems": 1, "maxItems": 50, "type": "array", "description": "One or more websites to audit. Use canonical homepage URLs when possible.", "items": { "type": "string" } }, "auditGoal": { "title": "Audit goal", "enum": [ "lead-generation", "conversion-optimization", "automation-opportunities", "sales-prep" ], "type": "string", "description": "Choose the primary agency or sales use case.", "default": "lead-generation" }, "targetIndustry": { "title": "Target industry", "type": "string", "description": "Optional industry context used in recommendations and pitch language.", "default": "B2B services" }, "maxPagesPerSite": { "title": "Max pages per site", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum number of same-domain pages to fetch for each website.", "default": 3 }, "includePitchEmail": { "title": "Include pitch email", "type": "boolean", "description": "Generate a short agency outreach email based on detected website gaps.", "default": true }, "includeRawSignals": { "title": "Include raw signals", "type": "boolean", "description": "Include sampled page text and extracted technical signals in each dataset item.", "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 } } } } } } } } } } ```