Capture leads on WhatsApp and save them to Sheets
An n8n WhatsApp agent asks leads for their name and email and automatically saves them to Google Sheets, shown in a demo.
An OpenClaw agent researches prospects, writes personalized cold emails, sends scheduled follow-ups and logs interactions to HubSpot.
An OpenClaw agent researches prospects, writes personalized cold emails, sends scheduled follow-ups and logs interactions to HubSpot.
The author defined the ideal customer, tone and a 50-emails-a-day cap in a SOUL.md file. He added Apollo for prospect lists, browser research for personalization hooks, a cold-outreach skill, and the HubSpot MCP server. The agent runs every 4 hours: researches prospects, sends emails, follows up, logs to HubSpot and posts a Slack summary. A human takes over at the first positive reply.
Over 60 days the author reports about 8-12 meetings a month at roughly $18 a month in total costs. He admits the agent invents facts about prospects at times and struggles with complex deals and nuanced objections.
Hallucinated research is a real risk, so spot-check the first 20-30 emails before trusting the agent. Using a cheap model for research and a stronger one for writing cut API costs from $22 to about $9 a month.
Act as my SDR. For each prospect in [list or CSV path], research their company and role, then write a personalized cold email for [my product] and a follow-up for [number] days later. Show me all drafts first. Only after I approve them should you send on the schedule I confirm, and log each interaction in [HubSpot or CRM].
An n8n WhatsApp agent asks leads for their name and email and automatically saves them to Google Sheets, shown in a demo.
An n8n agent handles customer WhatsApp messages, searches info, checks the calendar, logs to Sheets or Notion, and replies by WhatsApp and email.
A Lindy agent researches YouTube ideas and scripts, and another emails a brief on discovery-call contacts 10 minutes before meetings; complex content stayed on Make.