Bring these inputs
Anonymized interviews, product reviews, support tickets and customer questions.
Use approved, minimized data. Replace personal details with anonymous IDs.
Work through the lesson
- Gather a small, diverse sample: buyers, people who returned products and shoppers who did not buy. Remove names and order details before uploading.
- Ask AI to group jobs, triggers, objections and desired outcomes. Require a source ID for each observation and keep minority views visible.
- Write personas around a situation and buying task. Demographics alone rarely explain why someone needs the product.
- Interview customers about a recent purchase: what happened, what alternatives they considered and what nearly stopped them. Use those answers to challenge the AI’s draft.
- Create a one-page brief with language to use, proof needed, objections to answer and evidence still missing.
Try this prompt
Replace the bracketed fields with your own evidence.
Analyze these anonymized records [records]. Group buying situations, triggers, desired outcomes and objections. Cite record IDs. Separate observed evidence, inference and unanswered questions. Do not invent customers, quotes, demographics or market size. Draft two buyer briefs and five interview questions.
Worked example
For a travel organizer, “packing for a three-day work trip with one bag” is more actionable than “women aged 25–45.” It suggests a capacity demonstration and an honest size guide.
Before you use the result
- Quotes match the originals.
- A human has checked the clusters.
- The brief includes contradictory evidence.
Complete the exercise
Create the deliverable described at the top of this lesson. Save the input evidence, your edited output, unresolved questions and the name of the reviewer in your workbook.