by Custom Workflows AI
Introduction The "High-Level Service Page SEO Blueprint Report" workflow is a powerful, AI-driven solution designed to generate comprehensive SEO content strategies for service-based businesses. By analyzing competitor websites and user intent, this workflow creates a detailed blueprint that outlines the optimal structure, content, and conversion elements for a service page. The workflow leverages the JINA Reader API to extract content from competitor websites and uses Google Gemini AI to perform deep analysis across multiple dimensions: competitor content structure, user intent, strategic opportunities, and conversion optimization. The final output is a professionally formatted Markdown document that provides actionable guidance for creating a high-performing service page that satisfies both user needs and search engine requirements. This workflow eliminates the time-consuming process of manually analyzing competitors and developing content strategies, providing a data-driven foundation for service page creation that would typically require hours of expert analysis. Who is this for? This workflow is designed for digital marketers, SEO specialists, content strategists, and web developers who need to create or optimize service pages for businesses. It's particularly valuable for marketing agencies and freelancers who regularly develop content strategies for clients across various industries. Users should have a basic understanding of SEO concepts, content marketing, and website structure. While technical SEO knowledge is beneficial, the workflow is designed to provide comprehensive guidance even for those with intermediate-level expertise. The ideal user is someone who wants to streamline their content planning process and ensure their service pages are built on data-driven insights rather than guesswork. What problem is this workflow solving? Creating effective service pages that rank well in search engines while converting visitors is a complex challenge that typically requires extensive competitive research, content planning, and conversion optimization expertise. This workflow addresses several key pain points: Time-consuming competitor analysis: Manually analyzing multiple competitor websites to identify content patterns, heading structures, and meta tag strategies can take hours. Difficulty identifying content gaps: Determining what topics competitors are missing that could provide a competitive advantage requires deep analysis and industry knowledge. Balancing SEO and conversion elements: Creating content that satisfies both search engines and user needs while driving conversions is a delicate balance that many struggle to achieve. Lack of structured approach: Many content creators work without a comprehensive blueprint, leading to inconsistent results and missed opportunities. Difficulty translating analysis into actionable recommendations: Even when analysis is performed, turning those insights into a concrete content plan can be challenging. This workflow automates these processes, providing a structured, data-driven approach to service page creation that saves hours of research and planning time. What this workflow does Overview The workflow takes a list of competitor URLs and a target keyword as input, then performs a multi-stage analysis to generate a comprehensive service page blueprint. It extracts and analyzes competitor content, evaluates user intent, identifies strategic opportunities, and creates detailed recommendations for page structure, content, and conversion elements. The final output is a professionally formatted Markdown document that serves as a complete roadmap for creating an effective service page. Process Data Collection: The workflow begins with a form that collects essential information: competitor URLs, target keyword, services offered, brand name, and whether the page is a homepage. Competitor Content Extraction: The workflow processes each competitor URL, using the JINA Reader API to extract the HTML content from each site. Content Structure Analysis: For each competitor site, the workflow extracts and analyzes heading structures, meta tags, schema markup, and recurring phrases (n-grams). Competitor Analysis Report: The AI synthesizes the competitive data to identify patterns in meta titles/descriptions, common outline sections, key heading concepts, and structural elements. User Intent Analysis: The workflow analyzes the target keyword to determine primary and secondary user intents, user personas, and their position in the buyer's journey. Gap Analysis: The AI identifies content overlaps ("table stakes"), content gaps (opportunities), SEO keyword priorities, and potential UX/conversion advantages. Page Outline Generation: Based on the previous analyses, the workflow creates an optimal page structure with H1, H2s, H3s, and potentially H4s, with justifications for each section. UX & Conversion Recommendations: The workflow adds detailed recommendations for calls-to-action, trust signals, copywriting tone, visual elements, and risk reversal strategies. Final Blueprint Creation: All analyses and recommendations are compiled into a comprehensive, well-structured Markdown document that serves as a complete service page blueprint. Setup Download or import the "High-Level Service Page SEO Blueprint Report" workflow JSON file into your n8n instance. Create a JINA Reader API key by visiting https://jina.ai/api-dashboard/key-manager. You can claim a free API key that allows up to 1 million tokens. Set up Google Gemini (PaLM) credentials by following the guide at https://docs.n8n.io/integrations/builtin/credentials/googleai/#using-geminipalm-api-key. Update the "Edit Fields" node with: Your JINA Reader API Key Adjust the "Waiting Time" to 20 seconds if using the free Google Gemini API tier (which limits to 5 requests per minute) Optionally change the Gemini model if needed Activate the workflow and start the form trigger. Complete the form with: Competitors (up to 5 direct competitor URLs) Target Keyword (the query related to your service) Services Offered (details of your complete service offerings) Brand Name (your company name) Whether the page is a homepage After processing, download the generated .txt file, which contains the blueprint in Markdown format. How to customize this workflow to your needs Adjust AI parameters: Modify the temperature settings in the Google Gemini Chat Model nodes to control creativity vs. precision in the AI outputs. Customize extraction logic: Edit the "Extract HTML Elements" code node to focus on specific HTML elements that are most relevant to your industry or content type. Modify analysis prompts: Customize the prompts in the various analysis nodes to focus on specific aspects of SEO or content strategy that are most important for your use case. Add industry-specific guidance: Enhance the prompts with industry-specific instructions or examples to make the output more relevant to particular sectors. Integrate with content management systems: Extend the workflow to automatically send the blueprint to content management systems, project management tools, or document storage platforms. Add competitor scoring: Implement a scoring system to evaluate and rank competitors based on specific criteria relevant to your strategy. Expand the analysis: Add additional analysis nodes to evaluate other aspects of competitor websites, such as page speed, mobile-friendliness, or backlink profiles.
by AK Pasnoor
Put your productivity on autopilot with this workflow. How it works This workflow generates a beautifully formatted daily briefing email every morning at 6:00 AM by combining your Todoist tasks and Google Calendar events, summarizing them using GPT-4o, and sending them as a clean HTML email. It includes: Auto-fetching today's tasks and events Formatting them for context Generating a motivational summary with GPT-4o Converting the output into styled HTML Emailing it to you daily Set up steps Connect your Google Calendar and Todoist accounts Set your project ID in the Todoist node Customize the OpenAI prompt or email template if needed Enable the Schedule Trigger to automate daily runs All configuration logic and summaries are explained in sticky notes inside the workflow. No external tools required. Just plug, personalize, and automate your day!
by Jah coozi
Universal Digital Device Support Assistant Transform any device manual into an intelligent AI assistant that provides 24/7 support for your users. This template works with ANY household appliance, electronic device, or technical equipment. 🎯 Use Cases Manufacturers**: Provide instant support for your products Support Teams**: Reduce ticket volume with AI-powered answers Smart Homes**: Centralized help for all devices Personal Use**: Never lose a manual again ✨ Features Universal Compatibility**: Works with any device type Multi-Language Support**: Serve global customers Intelligent Search**: Semantic understanding of user queries Context Awareness**: Remembers conversation history Easy Setup**: Just upload your manual and go 🛠️ What's Included Webhook Endpoint: Receive user queries via API AI Agent: Processes questions intelligently Vector Database: Stores and searches manuals Memory System: Maintains conversation context Upload Pipeline: Easy manual ingestion 📋 Setup Instructions Add Your Credentials: OpenAI API key (or alternative LLM) Pinecone API key (or alternative vector DB) Upload Device Manuals: Use the manual upload trigger Paste manual text or upload PDF System automatically indexes content Configure Webhook: Set your preferred endpoint path Enable CORS if needed Deploy and share URL Optional Customization: Adjust chunk size for your content Modify system prompts for your brand Add additional tools or integrations 🔧 Supported Devices (Examples) Kitchen Appliances (ovens, dishwashers, coffee machines) Home Entertainment (TVs, sound systems, gaming consoles) Smart Home Devices (thermostats, cameras, lights) Computer Equipment (printers, routers, monitors) Power Tools & Garden Equipment Medical Devices And many more! 🌐 Integration Options Embed in your website Connect to chat platforms Mobile app integration Voice assistant compatibility Email support automation 📈 Benefits Reduce support costs by 70% Available 24/7 in multiple languages Consistent, accurate responses Scales infinitely Improves with usage 🔐 Privacy & Security Your data stays in your control Can be deployed on-premise GDPR compliant architecture No data sharing between devices 💡 Pro Tips Upload manuals in sections for better accuracy Include troubleshooting guides and FAQs Add model numbers and specifications Regular updates keep content fresh Start providing world-class device support today!
by Jimleuk
This n8n template demonstrates the beginnings of building your own n8n-powered WhatsApp chatbot! Under the hood, utilise n8n's powerful AI features to handle different message types and use an AI agent to respond to the user. A powerful tool for any use-case! How it works Incoming WhatsApp Trigger provides a way to get messages into the workflow. The message received is extracted and sent through 1 of 4 branches for processing. Each processing branch uses AI to analyse, summarize or transcribe the message so that the AI agent can understand it. The supported types are text, image, audio (voice notes) and video. The AI Agent is used to generate a response generally and uses a wikipedia tool for more complex queries. Finally, the response message is sent back to the WhatsApp user using the WhatsApp node. How to use Once you have setup and configured your WhatsApp account, you'll need to activate your workflow to start processing messages. Good to know: Large media files may negatively impact workflow performance. Requirements WhatsApp Buisness account Google Gemini for LLM. Gemini is used specifically because it can accept audio and video files whereas at time of writing, many other providers like OpenAI's GPT, do not. Customising this workflow For performance reasons, consider detecting large audio and video before sending to the LLM. Pre-processing such files may allow your agent to perform better. Go beyond and create rich and engagement customer experiences by responding using images, audio and video instead of just text!
by Ranjan Dailata
Who this is for? This workflow is designed for professionals and teams who need real-time, structured insights from Perplexity Search results without manual effort. What problem is this workflow solving? This n8n workflow solves the problem of automating Perplexity Search result extraction, cleanup, summarization, and AI-enhanced formatting for downstream use like sending the results to a webhook or another system. What this workflow does Automates Perplexity Search via Bright Data Uses Bright Data’s proxy-based SERP API to run a Google Search query programmatically. Makes the process repeatable and scriptable with different search terms and regions/zones. Cleans and Extracts Useful Content The Readable Data Extractor uses LLM-based cleaning to remove HTML/CSS/JS from the response and extract pure text data. Converts messy, unstructured web content into structured, machine-readable format. Summarizes Search Results Through the Gemini Flash + Summarization Chain, it generates a concise summary of the search results. Ideal for users who don’t have time to read full pages of search results. Formats Data Using AI Agent The AI Agent acts like a virtual assistant that: - Understands search results Formats them in a readable, JSON-compatible form Prepares them for webhook delivery Delivers Results to Webhook Sends the final summary + structured search result to a webhook (could be your app, a Slack bot, Google Sheets, or CRM). Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). Update the Perplexity Search Request node with the prompt you wish to perform the search. Update the Webhook HTTP Request node with the Webhook endpoint of your choice. How to customize this workflow to your needs 1. Change the Perplexity Search Input Default: It searches a fixed query or dataset. Customize: Accept input from a Google Sheet, Airtable, or a form. Auto-trigger searches based on keywords or schedules. 2. Customize Summarization Style (LLM Output) Default: General summary using Google Gemini or OpenAI. Customize: Add tone: formal, casual, technical, executive-summary, etc. Focus on specific sections: pricing, competitors, FAQs, etc. Translate the summaries into multiple languages. Add bullet points, pros/cons, or insight tags. 3.Choose Where the Results Go Options: Email, Slack, Notion, Airtable, Google Docs, or a dashboard. Auto-create content drafts for WordPress or newsletters. Feed into CRM notes or attach to Salesforce leads.
by Franz
🕸️ Dynamic Website Change Monitor with Smart Email Alerts Never miss important website updates again! This workflow automatically tracks changes on dynamic websites (think React apps, JavaScript-heavy sites) and sends you instant email notifications when something changes. Perfect for keeping tabs on competitors, monitoring product updates, or staying on top of important announcements. ✨ What makes this special? 🚀 Handles Dynamic Websites: Uses Firecrawl API to scrape JavaScript-rendered content that basic scrapers can't touch 📧 Smart Email Alerts: Only sends notifications when content actually changes (no spam!) 📊 Historical Tracking: Keeps a complete log of all changes in Google Sheets 🛡️ Bulletproof: Continues working even if one part fails ⚡ Ready to Deploy: Webhook-triggered, perfect for cron jobs or external schedulers 🎯 Perfect for monitoring: Competitor pricing pages Job board postings Product availability updates News sites for breaking stories API documentation changes Terms of service updates 🛠️ What you'll need to get started: API Accounts & Keys: Firecrawl Account 🔥 Sign up at firecrawl.dev Grab your API key from the dashboard Create a "Bearer Auth" credential in n8n Google Cloud Setup ☁️ Enable Google Sheets API Enable Gmail API Set up OAuth2 credentials Add both as credentials in n8n Google Sheets Document 📋 Create a new spreadsheet Add two tabs: "Log" and "comparison" Follow the structure outlined in the workflow notes 🚀 How it works: Webhook receives trigger → Starts the monitoring process Firecrawl scrapes website → Gets fresh content (even JavaScript-rendered!) Smart comparison → Checks against previously stored content Change detected? → If yes, send email + log everything Update storage → Prepares for next monitoring cycle ⚙️ Setup Steps: Import this workflow into your n8n instance Configure credentials for Firecrawl, Google Sheets, and Gmail Update the target URL in the Firecrawl node Set your email address in the Gmail node Create your Google Sheets with the required structure Test it manually first, then activate! 🎨 Customize it your way: Target any website** by updating the URL Change email templates** to match your style Adjust monitoring frequency** with external cron jobs Switch between markdown/HTML** extraction formats Fine-tune change detection** sensitivity 🔧 Troubleshooting: Firecrawl errors?** Check your API key and rate limits Google Sheets issues?** Verify OAuth permissions and sheet structure Email not sending?** Check Gmail API quotas and spam folders Webhook problems?** Make sure the workflow is activated Ready to never miss another website change? Let's get this automation running! 🎉
by Dr. Firas
Google Maps Data Extraction Workflow for Lead Generation This workflow is ideal for sales teams, marketers, entrepreneurs, and researchers looking to efficiently gather detailed business information from Google Maps for: Lead generation Market analysis Competitive research Who Is This Workflow For? Sales professionals** aiming to build targeted contact lists Marketers** looking for localized business data Researchers** needing organized, comprehensive business information Problem This Workflow Solves Manually gathering business contact details from Google Maps is: Tedious Error-prone Time-consuming This workflow automates data extraction to increase efficiency, accuracy, and productivity. What This Workflow Does Automates extraction of business data (name, address, phone, email, website) from Google Maps Crawls and extracts additional website content Integrates OpenAI to enhance data processing Stores structured results in Google Sheets for easy access and analysis Uses Google Search API to fill in missing information Setup Import the provided n8n workflow JSON into your n8n instance. Set your OpenAI and Google Sheets API credentials. Provide your Google Maps Scraper and Website Content Crawler API keys. Ensure SerpAPI is configured to enhance data completeness. Customizing This Workflow to Your Needs Adjust scraping parameters: Location Business category Country code Customize Google Sheets output format to fit your current data structure Integrate additional AI processing steps or APIs for richer data enrichment Final Notes This structured approach ensures: Accurate and compliant data extraction** from Google Maps Streamlined lead generation Actionable and well-organized data ready for business use 📄 Documentation: Notion Guide Demo Video 🎥 Watch the full tutorial here: YouTube Demo
by Obsidi8n
How it works: Send notes from Obsidian via Webhook to start the audio conversion OpenAI converts your text to natural-sounding audio and generates episode descriptions Audio files are stored in Cloudinary and automatically attached to your notes in Obsidian A professional podcast feed is generated, compatible with all major podcast platforms (Apple, Spotify, Google) Set up steps: Install and configure the Post Webhook Plugin in Obsidian Set up Custom Auth credentials in n8n for Cloudinary using the following JSON: { "name": "Cloudinary API", "type": "httpHeaderAuth", "authParameter": { "type": "header", "key": "Authorization", "value": "Basic {{Buffer.from('your_api_key:your_api_secret').toString('base64')}}" } } Configure podcast feed metadata (title, author, cover image, etc.) Note: The second flow is a generic Podcast Feed module that can be reused in any '[...]-to-Podcast' workflow. It generates a standard RSS feed from Google Sheets data and podcast metadata, making it compatible with all major podcast platforms.
by Ranjan Dailata
Who is this for? This workflow automates the process of querying Bing's Copilot Search, extracting structured data from the results, summarizing the information, and sending a notification via webhook. It leverages the Microsoft Copilot to retrieve search results and integrates AI-powered tools for data extraction and summarization. What problem is this workflow solving? Data Analysts and Researchers: Who need to gather and summarize information from Bing search results efficiently. Developers and Engineers: Looking to integrate Bing search data into applications or services. Digital Marketers and SEO Specialists: Interested in monitoring search engine results for specific keywords or topics. What this workflow does Manually extracting and summarizing information from search engine results can be time-consuming and error-prone. This workflow automates the process by: Performing Bing searches using Bright Data's Bing Search API. Extracting structured data from the search results. Summarizing the extracted information using AI tools. Sending the summarized data to a specified endpoint via webhook. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). Update the Perform a Bing Copilot Request node with the prompt you wish to perform the search. Update the Structured Data Webhook Notifier node with the Webhook endpoint of your choice. Update the Summary Webhook Notifier node with the Webhook endpoint of your choice. How to customize this workflow to your needs Modify Search Queries: Adjust the search terms to target different topics or keywords. Change Data Extraction Logic: Customize the extraction process to capture specific data points from the search results. Alter Summarization Techniques: Integrate different AI models or adjust parameters to change how summaries are generated. Update Webhook Endpoints: Direct the summarized data to different endpoints as required. Schedule Workflow Runs: Set up automated triggers to run the workflow at desired intervals.
by Agentick AI
This n8n workflow automates the process of collecting job and decision-maker data, crafting AI-generated referral messages, and drafting them in Gmail—all using a combination of Apify, Google Sheets, LLMs, and email APIs. Use cases Auto-sourcing job postings from LinkedIn via Apify Identifying decision-makers at relevant companies Auto-drafting custom referral request messages using AI Exporting structured data to Google Sheets and drafting Gmail messages for outreach Good to know You can customize the filtering logic to target specific cities or companies. Message creation uses the Gemini 2.0 Flash model and LangChain’s output parser for structured messages. Email data is fetched using Anymailfinder, but can be replaced with other providers like Hunter.io. Gmail API drafts the message, but you need to enable Gmail API access from your Google Cloud console. How it works Trigger A Schedule Trigger runs the automation daily. Job Data Extraction Apify pulls job listings using a predefined actor. The HTTP response is split and structured using the Split Out node. Store Job Data Job listings are saved to a Google Sheet. The node maps key fields like title, company, location, and poster info. Decision-Maker Discovery Another Apify actor pulls decision-maker data from LinkedIn. This is split and filtered (e.g., by city or company name). Store Contacts Contact details (name, title, location, etc.) are appended to another Google Sheet (n8n-sheet). Message Generation A LLM Chain uses Gemini 2.0 Flash to generate short, custom LinkedIn messages. The message respects rules like tone, length (<100 words), and personalization. Parse & Merge AI Output The output is structured using Structured Output Parser and merged with contact data. Save Final Messages The final headline and body are stored back into Google Sheets (n8n-sheet). Email Discovery Get Email IDs node hits Anymailfinder API using the LinkedIn profile link. Draft in Gmail Using Gmail API, the message is drafted in your inbox with subject and body auto-filled. How to use Update Apify actor inputs to specify roles, companies, or locations. Replace the manual Schedule Trigger with a webhook or form input if desired. Update the Google Sheets document and sheet name in the relevant nodes. Add your Gmail and Anymailfinder credentials in n8n settings. Requirements Google Sheets API access Gmail API access Apify account Gemini API key (via Google AI Studio) Anymailfinder (or alternate email discovery API) Customizing this workflow This framework is highly modular. You can: Add more filters for company size, role, or hiring urgency Use alternate LLMs (OpenAI, Claude, etc.) Switch output channels (Slack, WhatsApp, etc.) Plug in different CRM tools for follow-ups
by Leonard
Open Deep Research - AI-Powered Autonomous Research Workflow Description This workflow automates deep research by leveraging AI-driven search queries, web scraping, content analysis, and structured reporting. It enables autonomous research with iterative refinement, allowing users to collect, analyze, and summarize high-quality information efficiently. How it works 🔹 User Input The user submits a research topic via a chat message. 🧠 AI Query Generation A Basic LLM generates up to four refined search queries to retrieve relevant information. 🔎 SERPAPI Google Search The workflow loops through each generated query and retrieves top search results using the SerpAPI API. 📄 Jina AI Web Scraping Extracts and summarizes webpage content from the URLs obtained via SerpAPI. 📊 AI-Powered Content Evaluation An AI Agent evaluates the relevance and credibility of the extracted content. 🔁 Iterative Search Refinement If the AI finds insufficient or low-quality information, it generates new search queries to improve results. 📜 Final Report Generation The AI compiles a structured markdown report, including sources with citations. Set Up Instructions 🚀 Estimated setup time: ~10-15 minutes ✅ Required API Keys:** SerpAPI → For Google Search results Jina AI → For text extraction OpenRouter → For AI-driven query generation and summarization ⚙️ n8n Components Used:** AI Agents with memory buffering for iterative research Loops to process multiple search queries efficiently HTTP Requests for direct API interactions with SerpAPI and Jina AI 📝 Recommended Enhancements:** Add sticky notes in n8n to explain each step for new users Implement Google Drive or Notion Integration to save reports automatically 🎯 Ideal for: ✔️ Researchers & Analysts - Automate background research ✔️ Journalists - Quickly gather reliable sources ✔️ Developers - Learn how to integrate multiple AI APIs into n8n ✔️ Students - Speed up literature reviews 🔗 Completely free and open-source! 🚀
by Keith Rumjahn
Who's this for? If you own a website and need to analyze your Google analytics data If you need to create an SEO report on which pages are getting most traffic or how your google search terms are performing If you want to grow your site based on suggestions from data Use case Instead of hiring an SEO expert, I run this report weekly. It checks compares the data from this week to the week before: Views based on countries The top performing pages Google search console performance Watch youtube tutorial here Get my SEO A.I. agent system here Read my detailed case study here How it works The workflow gathers google analytics for the past 7 days then it gathers the data for the week before for comparison. It does this 3 times to get: views per country, engagement per page and google search console results for organic search results. The google analytics nodes has already chosen the correct dimensions and metrics. At the end, it passes the data to openrouter.ai for A.I. analyse. Finally it saves to baserow. How to use this Input your Google analytics credentials Input your property ID Input your Openrouter.ai credentials Input your baserow credentials You will need to create a baserow database with columns: Name, Country Views, Page Views, Search Report, Blog (name of your blog). Created by Rumjahn