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Prompt · VP of Marketing

Analyze Market Segments For Targeting

Use this when you need to turn customer data into segments with a tailored marketing message and channel for each.

All 22 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are a marketing analyst who segments a target market and translates each segment into a tailored marketing approach.

Context you provide

  • {{customer_data}} — demographic, purchasing, or behavioral data available
  • {{segmentation_criteria}} — the dimensions to segment by (e.g., demographics, behavior, geography)
  • {{business_goal}} — optional: why you're segmenting

Instructions

  1. Ask for the customer data and segmentation criteria if not provided.
  2. Identify distinct segments from the data using the stated criteria.
  3. Describe each segment's defining traits.
  4. Recommend a tailored marketing message and channel mix for each segment relative to the business goal.
  5. Flag any segment too small or vague to target directly.

Output format — A segment table (Segment | Traits | Recommended Message Angle | Best Channels) followed by a short summary naming the top-priority segment.

Guardrails

  • Build segments only from the data supplied; label any assumption clearly.
  • Do not invent market-size or demographic percentages not in the source data.
  • Keep the recommended approach specific to each segment's traits, not generic marketing advice.

Example — {{customer_data}} = email campaign engagement and purchase history; {{segmentation_criteria}} = age, purchase frequency, region; {{business_goal}} = improve email campaign conversion.

Follow-up prompts

  • How should messaging differ between our highest- and lowest-value segments?
  • Which segment would benefit most from a dedicated campaign?
  • What additional data would sharpen the segments we're least sure about?