Fully personalized 1:1 ABM program: a Replit + Claude workflow. (How to deploy AI to generate pipeline, not just scale broken tactics) 1. Fix account blindness & data silos Many GTM teams struggle with account blindness: - Sales are unaware of marketing touchpoints with target accounts (beyond "leads from gated PDFs/webinars") - Marketing never gets sales’ insights to create relevant content and personalize campaigns - Data sits in disconnected tools I've been prototyping a solution with Replit’s Agent 3 + Connectors: - Pull the target account & buyer list from HubSpot - Connect all account data from siloed systems With this 360° account view , Replit can now help me: - Prioritize accounts deserving a 1:1 approach (Step 2) - Run additional deep research of top accounts (via Claude) - Prepare 1:1 personalized campaign (Step 3) - Push all this info back to HubSpot so it's available to sales 2. Prioritize accounts based on signals and insights We now have a custom Replit dashboard with a combined view of: a) Engagement signals - High-intent website visits from Dealfront - Detailed webinar engagement from Goldcast - Buyer contributions to content collabs b) Account insights from our own and Claude's deep research c) Insider information - challenges and priorities shared by target buyers via - Content collabs - Webinar polls/Q&As/registration forms - Social and email conversations - Transcribed interviews and calls d) Buying committee engagement & relationships. Individual buyers engaged via - Social and email convos - Webinars (incl. questions they asked, polls submitted) - Newsletter This makes it easy to prioritize accounts deserving a 1:1 approach. 3. Build the 1:1 campaign Replit can use the collected data and additional research to prompt Claude assistants trained to draft: - Account "love letters" - 1:1 personalized solutions & business cases - 1:1 Content hubs - 1:1 personalized messages to use to reach out to buyers based on signals, and to distribute this account-specific content --- There is no "magic AI agentic workflow" driving pipeline on an auto-pilot, despite the AI circus in our LinkedIn feeds. This only works because we: 1. Use deep insights and research about the target ICP segment as input for AI 2. Always request quotes to prevent hallucination and preserve buyer language 3. Give AI detailed playbooks based on processes we have proven and refined through many iterations. Pilot → document & refine → prompt 4. Show AI what 'good looks like' with examples of high-quality output (quality benchmarks) 5. Build in human feedback loops and (AI + human) quality checks Caveat: This is still POC with some manual plumbing & steps. But it shows how teams can stop using AI to scale broken tactics and mediocre content, and start building real pipeline with AI-powered workflows. P.S. If not familiar, Replit lets non-coders build apps & automations on top of your data with connectors (https://replit.com)