Vorlagen für Keyword-Recherche zu Zielgruppenfragen

• •Google Sheets API-Anmeldedaten
• •OpenAI API Key

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              "content": "=Output format:\nA list of 50 keywords in a JSON array called \"keywords\". each keyword in the array has an additional element which represents intent. Intent is either informational, navigational, commercial, transactional.\n\nYour Task:\nWhen analyzing the target customer profile, think through what they would actually type into Google, Bing, or other search engines. Consider their pain points, goals, research habits, and decision-making process. Think about both their professional research queries and their more casual, exploratory searches.\n\nkeywords should be short matching typical queries in search engines. It should not be elaborative questions and act as keywords to build upon for further keyword research. Do not return navigational keywords.\n\nTarget customer profile:\n {{ $json.customer_profile }}"
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              "content": "=Output format:\nA list of 50 questions in a JSON array called \"questions\". each question in the array has an additional element which represents intent. Intent is either informational, navigational, commercial, transactional.\n\nYour Task:\nWhen analyzing the target customer profile, think through what questions they would actually ask ChatGPT, Claude, or Google AI Mode. Consider how they would phrase requests for investment advice, research help, analysis, and decision support. Think about their natural conversation patterns, the context they'd provide, and how they'd iterate on responses. Draw from your deep understanding of search behavior patterns from SEMrush and Ahrefs data to predict conversational AI query evolution.\n\nGenerate question examples - focusing on natural conversational queries, multi-turn interactions, and the specific ways this audience leverages AI for investment research and decision-making, backed by your professional marketing intelligence expertise.\n\nTarget customer profile:\n {{ $json.customer_profile }}"
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              "content": "You are an Answer Engine Optimization (AEO) specialist and conversational AI researcher who works for a cutting-edge digital marketing consultancy. You have an MBA in Digital Marketing and many years of experience analyzing search behavior across traditional SEO and emerging conversational AI platforms.\n\nYour Background:\n- You're a certified expert in SEMrush, Ahrefs, and other premium marketing intelligence tools \n- You've managed keyword research campaigns with budgets exceeding $500K annually across fintech and investment sectors\n- You understand the nuances of search intent classification (informational, navigational, commercial, transactional) and how this translates to conversational AI queries \n- You've studied thousands of ChatGPT, Claude, and Google AI Mode conversations across various industries, with particular focus on financial services\n- You're an expert in competitive intelligence, using tools like SEMrush's 3+ billion keyword database and Ahrefs' backlink analysis to understand market landscapes \n- You stay current with LLM capabilities and how users adapt their questioning styles accordingly\n\nYour Tool Expertise:\n- Advanced SEMrush user: Keyword Magic Tool, Topic Research, Market Explorer, and Brand Monitoring\n- Ahrefs power user: Keywords Explorer, Content Explorer, and Site Explorer for competitive analysis \n- Proficient with Answer The Public, SpyFu, and emerging AEO-specific tools\n- Experience with Google Search Console, Google Analytics, and Google Ads Keyword Planner integration\n- Understanding of how traditional keyword metrics (search volume, difficulty, CPC) translate to conversational AI query patterns\n\nYour Approach:\n- You think in terms of natural language queries and conversational flows, but with deep understanding of underlying search intent\n- You understand that AI users ask follow-up questions and iterate on their queries, creating conversation threads rather than isolated searches\n- You recognize that people are more verbose and context-heavy when talking to AI vs. search engines, often providing personal financial situations\n- You know users often ask for comparisons, explanations, and step-by-step guidance from LLMs, especially for complex investment decisions\n\nYour Personality:\n- Curious about human-AI interaction patterns and emerging query behaviors in financial services\n- Forward-thinking about how conversational AI is changing information discovery and purchase decisions\n- Analytical but focused on natural language patterns rather than traditional keyword density metrics\n- Empathetic to how users build trust and rapport with AI assistants for financial advice\n- Excited about the shift from \"search\" to \"ask\" mentality, especially in high-stakes financial decisions\n- Data-driven decision maker who validates hypotheses with actual tool data and user behavior analytics"
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        "content": "## Audience Problem Keyword Research Workflow\n### This n8n template generates relevant keywords and questions from a a customer profile. Keyword data is enriched from ahref and everything is stored in a Google Sheet. This is great for market and customer research. Understanding search intent for a well defined audience and gives relevant actionable data in a fraction of time that manual research takes.\n\n### How it works\n* We'll define a customer profile in the 'Data' node\n* We use an OpenAI LLM to fetch relevant search intent as keywords and questions\n* We use an SEO MCP server to fetch keyword data from ahref free tooling\n* The fetched data is stored in the Google sheet\n\n### How to use\n* Make a copy of [this](https://docs.google.com/spreadsheets/d/10SEHuy5bYMrq_j1Tr2HBcM9I4O6ShYVV_k2tKEfxteI/edit?usp=sharing) Google Sheet and add it in all Google Sheet nodes\n* Make sure that n8n has read & write permissions for your Google sheet. For my self-hosted n8n instance I was using a [Google Service Account](https://docs.n8n.io/integrations/builtin/credentials/google/service-account/)\n* Add your OpenAI account ([API Key](https://docs.n8n.io/integrations/builtin/credentials/openai/#using-api-key)) in the LLM nodes\n* Add your customer profile in the 'Data' node\n* Add MCP credentials for [seo-mcp](https://github.com/cnych/seo-mcp). Make sure you set the environments correctly:\n```json\n\"command\": \"uvx\",\n\"args\": [\"--python\", \"3.10\", \"seo-mcp\"],\n\"env\": {\n  \"CAPSOLVER_API_KEY\": \"CAP-xxxxxx\"\n}\n```\n* Execute workflow :)\n\n### Requirements\n* CapSolver account and API key ([register here](https://dashboard.capsolver.com/passport/register?inviteCode=p-4Y_DjQymvt)) to use [seo-mcp](https://github.com/cnych/seo-mcp)\n* Google Drive account"
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