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Plan an account-based marketing program for target accounts

An ABM plan with account selection, tiers, buying-committee messaging, coordinated plays, and measurement.

Marketing & BrandFew-ShotStandardMarketingSalesResearchPlan

The prompt

Help me plan an account-based marketing (ABM) program. What we sell and typical deal size: [DETAILS] ICP: [industry, size, tech stack, triggers] Candidate accounts: [PASTE LIST or describe how to build one] Buying committee: [roles usually involved, e.g. economic buyer, champion, IT, procurement] Sales team involvement: [number of reps, their capacity] Budget and tools: [e.g. LinkedIn ads, intent data, direct mail, none] Build: 1. Account selection criteria and tiers: Tier 1 (1:1, a handful of accounts), Tier 2 (1:few, clustered by industry or use case), Tier 3 (1:many, programmatic). 2. For each tier: research depth, personalization level, channels, and budget per account. 3. Buying-committee messaging: what each role cares about, their likely objections, and the proof they need. 4. Coordinated plays over 90 days: ads, content, outreach sequences, events, direct mail, executive outreach, with who owns each step (marketing vs. sales). 5. Signals that move an account forward or trigger sales action (engagement, intent, new hires, funding). 6. Measurement: account engagement, meetings with target accounts, pipeline and win rate vs. non-ABM accounts, deal velocity. Avoid using lead volume as the success metric. Return the tier table, a sample Tier 1 account plan template, and a weekly marketing-sales sync agenda. Don't invent facts about named accounts or people; mark research still to do as [RESEARCH].

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • DETAILS
  • industry, size, tech stack, triggers
  • PASTE LIST or describe how to build one
  • number of reps, their capacity
  • e.g. LinkedIn ads, intent data, direct mail, none
  • RESEARCH

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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