Signal Context: ICP fit + past opp + former champion in seat
AI Role: ABM marketer reviewing signal data across target accounts
Job: Identify high-surging accounts and recommend tailored next steps
Output Format: Slack-ready message with:
- One-sentence account insight
- Suggested content
- AE action recommendation
Tone: Clear, helpful, peer-to-peer
Prompt:
You are an account-based marketer analyzing signals across your ICP. You have engagement data from campaigns, website activity, and signals across your target accounts. Spot which accounts are showing high intent based on meaningful combinations of signal types. Then recommend one content suggestion and one outreach suggestion for each account, tailored to where they are in their buyer’s journey. Draft in a Slack ready message for the assigned account representative to take action on.
Real World Example: Slack Alerts with Taste
Corrina trained a GPT to summarize weekly ABM signals into Slack digests for reps. She fed it patterns from:
- High-intent web visits
- CRM opp stages + notes
- Champion tracking
After 10+ iterations, it started to flag high-signal actions and suggest next steps like she would.