#54 · How to Run $100K+ Performance Based AI Automation Offers

youtube ↗AI & Automation

How can I collect chatbot conversations into a spreadsheet by session ID and automatically add extracted names and emails to our CRM?

You don’t need to parse the chat yourself. Add a line to your prompt asking the model to capture name and email when they appear and output them directly. Then, in the workflow, map the model’s JSON response to a Google Sheet: create a row with columns for the session ID, the raw message, and the extracted name/email. Use the ‘Add Row’ action, select your spreadsheet, and map the fields from the node output (message, response, session ID) to the appropriate columns. This eliminates manual parsing and lets you store each chat session in the sheet automatically.

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Related answers

youtube ↗AI & Automation

What did you say about personalizing messages – is that referring to enrichment, and how should I handle it?

Personalizing messages ties into enrichment. After you verify leads, you’ll have a CSV or Google Sheet of contacts. Dump that file into a Google Drive folder, set up a watcher that triggers a flow (using Make, N8N, or another no‑code platform). The flow reads each row and runs an enrichment automation powered by AI, adding relevant details to each contact. This adds a personal touch without manual effort. While there may be extra costs for the enrichment service, at $6,000 a month in revenue you could comfortably spend $500‑$1,000 on automation that saves you countless hours and makes the business run smoother.

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youtube ↗AI & Automation

What is the elegant way to build a proper knowledge base?

It depends on your purpose – you don’t need a knowledge base for everything, but it’s useful for letting an AI answer business‑specific questions that would otherwise require a database query. For example, I would feed all publicly available information about me, my company (Left Click Software), and our major case studies into the system. I’d host the chatbot on a platform like Botpress or NLU and connect it directly to Claude via API. The system prompt would contain a simple template with a few conversation routes to keep answers constrained. All the data would be embedded in a vector store such as Pinecone, and Claude would query Pinecone for the top five to ten matches before responding. This is standard RAG: each incoming message triggers the system prompt, a Pinecone similarity search, injection of the results into the prompt, and then the answer. The key is to be specific – you can’t feed everything – and to consider security, since exposing internal data through a public model can leak sensitive information.

knowledge baseragai
youtube ↗AI & Automation

I've gone through your NAT tutorials to create workflows, but my budget is tight—I can't subscribe to every tool. Which workflow should I prioritize learning before pitching on Upwork and doing cold emails?

Great idea. I think you should probably get a naden subscription—make sure it's naden cloud—and get Appy. The reason you get Appy is because if you have Appy and Google Sheets, you can do a million things. Then get one of the AI model families, like Claude from Anthropic, load it up with some credits, or get ChatGPT, or the GPT suite via the OpenAI API. That should get you about 80% of the way there, and you can do a lot with that. For the rest, any mail finder or Phantom Buster—just add a few credits and you'll have email enrichment flows capable as well. The mic I'm using is the Samsung Q2U. Thanks, Ahmed.

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