Audience ResearchMarketing StrategyCustomer InsightsMarket ResearchContent Strategy
Conduct Audience Research
T. Krause
Understand who your audience actually is, not who you imagine they are. This prompt designs an audience research plan that surfaces real motivations, language, and decision criteria — then turns that data into actionable marketing direction.
The most expensive marketing mistakes start with assumptions about the audience that nobody ever tested. The persona doc was written in week one, the messaging followed, and the campaigns scaled — and only when results disappointed did anyone notice that the actual buyer is someone slightly different, with different motivations, different objections, and different language. By that point, every marketing asset has been built on the wrong foundation.
Good audience research closes the gap between who you think your audience is and who they actually are. It listens to real customers in their own words, surfaces the decision criteria they use (not the ones marketers think they should use), and produces a research summary specific enough to inform messaging, channel selection, and offer design. This prompt designs that research plan and translates the findings into marketing direction you can act on this week.
What It Does
- Designs a multi-method audience research plan combining customer interviews, review mining, social listening, and competitor analysis — calibrated to your stage and budget.
- Defines the specific questions that surface real motivations, objections, and decision criteria — not the surface-level demographics that produce generic personas.
- Translates raw research into actionable marketing direction: messaging angles, content topics, channel priorities, and offer adjustments.
The Prompt
#CONTEXT:
I need a structured plan to research my audience and turn the findings into actionable marketing direction. I want to move beyond demographic personas and surface what actually motivates my buyers — what they were trying to achieve when they bought, what alternatives they considered, what almost stopped them, and the language they use to describe their problem. The output should be specific enough that I can rewrite my homepage, sales emails, and ad copy with it.
#ROLE:
You are a senior strategist specializing in qualitative customer research for B2B and consumer brands. You understand that demographics are weak predictors of purchase, while job-to-be-done framing, decision triggers, and verbatim language are far stronger. You design research plans that mix interviews, review mining, support transcripts, and competitor signals — and you know how to extract pattern-level insights from raw qualitative data without over-fitting to anecdotes.
#RESPONSE GUIDELINES:
1. Recommend a research plan combining 3–5 methods (customer interviews, review mining, support ticket analysis, social listening, competitor message analysis) sized to my budget and stage.
2. Provide a customer interview script with 10–12 questions that surface real motivations, alternatives considered, decision triggers, and objections.
3. Define what to look for in review mining — which platforms, which types of reviews, and what patterns indicate genuine signal vs. noise.
4. Build an analysis framework that synthesizes findings into 4 dimensions: who they are, what they're hiring the product to do, the language they use, and the decision criteria they actually apply.
5. Translate the findings into 3–5 concrete marketing actions: messaging angles, content topics, channel priorities, and offer changes.
#AUDIENCE RESEARCH CRITERIA:
1. Methods must be calibrated to stage. A pre-launch business needs interviews with adjacent buyers; an established business has its own customer base to mine.
2. Interview questions must be open-ended and behavioral. "Why did you buy?" produces post-rationalized answers; "Walk me through the day you decided to look for a solution" produces real ones.
3. Review mining should target competitor reviews and category reviews, not just my own. Customers describe pain points in competitor reviews that they've already moved past in mine.
4. Findings must be reported as patterns with verbatim quotes. A research summary without quotes is interpretation without evidence.
5. Every insight must connect to a specific marketing action. Insights that don't change what we do next are intellectual exercise, not research.
#INFORMATION ABOUT ME:
- My business and offer: [BUSINESS]
- My current understanding of the audience: [CURRENT_PERSONA]
- Customer base size (if any): [CUSTOMER_BASE]
- Research budget: [BUDGET — e.g., founder time only, $1K, $10K]
- Timeline: [TIMELINE — e.g., 2 weeks, 6 weeks]
- The single biggest question I want answered: [KEY_QUESTION]
#RESPONSE FORMAT:
Research Plan:
- Method 1: [Method] — Why: [purpose] — Effort: [time/cost] — Output: [what you'll get]
- Method 2: ...
Customer Interview Script:
1. [Question] — [What you're listening for]
2. [Question] — ...
Review Mining Plan:
- Platforms: [Where to look]
- Targets: [Whose reviews — your competitors, category leaders]
- Patterns to extract: [What to count, code, and quote]
Analysis Framework:
- Who they are: [Demographic + situational]
- Job-to-be-done: [What they're hiring the product for]
- Language: [Verbatim phrases to use in copy]
- Decision criteria: [What actually drives the buy]
Marketing Actions (Post-Research):
1. Messaging angle: [Recommended pivot]
2. Content topic: [What to publish based on insights]
3. Channel priority: [Where the audience actually lives]
4. Offer adjustment: [Pricing, packaging, or guarantee changes]
5. Sales enablement: [Objections to address explicitly]
Validation Checkpoints:
- [How you'll know the research was sufficient]
- [When to re-run]
How to Use
- Pick a single key question to anchor the research. "Who is my audience?" is too broad; "Why do prospects sign up for the trial but not convert?" is sharp enough that the research can answer it.
- Run 8–12 customer interviews before drawing conclusions. Five interviews surface anecdotes; ten or more surface patterns. Stop when you stop hearing new things.
- Record interviews and use verbatim quotes in your final summary. Paraphrasing flattens the language — and the language is the most valuable part of the research.
- Translate every insight into a specific marketing change. Research that lives only in a Notion doc is research that did not happen.
Example Input
## Information about me
- My business: A SaaS for solo accountants who serve small business clients (1–10 employees)
- Current persona understanding: We assumed our buyer was a solo CPA in their 40s who wanted to grow their practice
- Customer base: ~210 paying customers, mostly via Google search and referrals
- Research budget: Founder time + $500 for incentives
- Timeline: 4 weeks
- Key question: Why do qualified trial users not convert? Our trial-to-paid is 9% and we believe it should be 18–25% based on category benchmarks
Tips
- Listen for the words the customer uses, not the words you wish they used. The phrase "I needed something I didn't have to think about" is worth ten persona attributes — drop it directly into your headline.
- Mine your own support tickets and lost-deal notes first. This data is free, often more honest than interviews, and almost universally underused.
- Interview people who didn't buy, not just people who did. Lost-deal interviews surface objections and pricing perception that converted customers will never tell you.
- Avoid "feature feedback" interviews early on. Asking "what would you want us to add?" produces wish lists, not insights. Ask about the problem, the alternatives, and the moment they decided to act.
- Re-run audience research every 12–18 months. Audiences shift as the category matures — the early-adopter customer who bought you in 2024 has different motivations than the mainstream buyer of 2026.