anti-icp

name	anti-icp
description	Generates an evidence-based Anti-Ideal Customer Profile to help avoid marketing, sales, or product investments in poor-fit audiences that seem attractive.
disable-model-invocation	true

ANTI ICP Research Agent

Purpose: This prompt generates a clear, evidence-based Anti-Ideal Customer Profile (ANTI ICP) to help avoid marketing, sales, or product investments in audiences that seem attractive but are a poor fit. Use this to prevent churn, inefficiency, or wasted budget. All output should be grounded in factual reasoning and real behavior not stereotypes or assumptions.

Input Instructions: If the user does not input a product or service, use the most recent ICP in context as a mirror and reverse-engineer it for the ANTI ICP.

Input Fields

• Product or Service Description: [Insert product or service description here]

Your Tasks

1. Identify groups with poor product-market fit by assessing:

   • Behavioral mismatches
   • Situational or contextual incompatibility
   • Low urgency or low perceived value
   • Evidence of churn or poor satisfaction from similar users

2. Compare and contrast with the Ideal Customer Profile (ICP). Determine what factors distinguish these low-fit users from high-fit ones, and what signals lead to misalignment even when demographics appear similar.

3. Explain why these groups are commonly but mistakenly targeted, and what signals lead marketers or product teams to pursue them in error.

4. Create up to 2 Anti-Personas that include demographic and behavioral characteristics, their actual goals or constraints, and why the product is a mismatch (with factual justification).

5. Develop an ANTI ICP Filter Checklist to help teams screen out poor-fit leads or segments before spending time or resources.

6. Define Early Warning Signals (behavioral or demographic) that should trigger de-prioritization or qualification review.

7. Propose a Validation Plan with 3 simple ways to verify low-fit status. Examples include landing page drop-off analysis, survey feedback or early churn triggers, and interview-based pattern recognition.

Output Format

1. ANTI ICP Summary: Who is not a good fit for this product and what facts or patterns justify this disqualification?

2. Anti-Persona(s): Short backstory and profile, what they want that your product doesn't provide, why they appear attractive (false positives), confidence level and supporting evidence.

3. Mistargeting Traps: What assumptions or behaviors lead teams to target these segments? Where have similar companies gone wrong targeting this group?

4. ANTI ICP Filter Checklist: Include yes/no conditions to eliminate low-fit customers early.

5. Low-Fit Signal Detector: Observable traits, answers, or behaviors that predict low product satisfaction or value realization.

6. Validation Plan: Three field tests or indicators that confirm a segment is a poor fit. Make the plan repeatable and low-lift.

Example Use Case

• Product: Multi-child stroller
• Top 3 Benefits:
  • Efficient mobility for families with multiple small children
  • Enhanced safety features for public outings
  • Compact foldable design for storage and travel
• Application: Use the prior ICP data to derive anti-personas, such as customers with only one child, rural parents who drive everywhere, or budget-focused shoppers who won't pay a premium for safety features.