Customer Research Skill
Mandatory Content Standards
- Match output length to the skill, request, and deliverable type. Use concise answers for quick checks, structured detail for audits and plans, and full-length output only when the user asks for a complete deliverable.
- Write in a way that sounds like a knowledgeable human wrote it. No robotic or templated phrasing.
- Use short sentences. One idea per sentence. One focus per paragraph.
- Use active voice. Never passive constructions.
- Address the reader directly using "you" and "your."
- Use bullet points only when they genuinely improve readability.
- Replace all em dashes with commas, parentheses, semicolons, or a new sentence. No hidden Unicode characters.
- End every sentence with a period.
- No hashtags, emojis, or asterisks.
- No introductory or closing filler phrases such as "in conclusion," "in summary," or "in a world where."
- No warnings, notes, or disclaimers. Stick to requested output.
- No AI cliches: no "game-changer," "unlock," "leverage," "dive into," "delve," "cutting-edge," "transformative," "revolutionize."
- No excessive adjectives or adverbs. Let specifics do the work.
- No broad generalizations. Every claim tied to specific context.
- Use specific examples, data, and scenarios.
- Pose at least one thought-provoking question per skill.
- Mobile-friendly: short paragraphs, clear headers, scannable.
- Practical and actionable. Every section connects to a next step.
What This Skill Does
This skill helps you plan, execute, and synthesize customer research. It covers the full research process, from identifying what you need to know, to collecting data across multiple sources, to turning raw input into messaging your customers will recognize as their own words.
Good customer research is the foundation of every marketing decision that works. Without it, you write copy that sounds like you, not like your customer. You build features people don't use. You target the wrong channels. You miss the language that actually triggers a purchase.
The question worth sitting with before starting: what decision are you trying to make, and what would you need to believe to make it confidently?
Part 1: Define the Research Question
Before collecting any data, get specific about what you need to learn.
Vague research produces vague insights. "Understand our customers better" is not a research question. These are:
- Why do customers choose us over [specific competitor]?
- What does a customer's workflow look like before they start using our product?
- What outcome does a customer expect within the first 30 days?
- What makes a customer cancel, even when they liked the product?
Write your research question down before you collect anything. Every data source and interview question you use should connect back to it.
Types of Research by Decision Stage
Different decisions require different research methods.
Early-stage (pre-product or pre-messaging): You need exploratory research. Open-ended interviews. Watering hole observation. No surveys yet. You don't know enough to write good survey questions.
Mid-stage (you have users, refining positioning): You need both qualitative and quantitative. Interviews plus surveys. Review mining. Support ticket analysis.
Late-stage (optimizing existing channels): You need specific, targeted data. Conversion surveys. Exit surveys. Cohort analysis of behavior.
Match your method to your stage.
Part 2: Ideal Customer Profile (ICP) Research
Your ICP is not a demographic profile. It is a description of the specific type of company or person who gets the most value from your product and is the easiest to retain.
Start with your existing customers, not hypothetical ones.
Step 1: Pull Your Best Customers
Define "best" concretely:
- Highest lifetime value.
- Lowest churn rate.
- Fastest time to activation.
- Most likely to refer others.
Pull 10 to 20 of these customers and look for patterns. What industry are they in? What size is their team? What job title holds the budget? What triggered them to buy?
Step 2: Interview Your Best Customers
Talk to five to eight of your best customers directly. You will find more useful signal in five conversations than in 500 survey responses.
Use this as a starting framework for ICP interviews:
- "Walk me through what was happening in your work right before you started looking for a solution like ours."
- "What had you tried before finding us, and what wasn't working about those options?"
- "What made you decide to try our product specifically?"
- "What does success look like for you, and how would you know if we failed you?"
- "Who else on your team uses this, and how would you describe what we do to them?"
Listen for specific situations, not abstract opinions. "I needed a way to send reports to clients without giving them access to our internal tools" is far more useful than "I needed something efficient."
Step 3: Document the ICP Profile
After interviews, write a structured ICP document:
Firmographic profile: Industry, company size (revenue or headcount), geography, business model (SaaS, agency, e-commerce, etc.).
Role profile: Job title, seniority level, team structure, who they report to, who reports to them.
Trigger events: What happened in their business that made them start looking? Common triggers include a team size crossing a threshold, a new hire in a specific role, a failed audit, losing a major client, or hitting a capacity wall.
Alternatives considered: Which competitors or substitutes did they evaluate? What made those fall short?
Success definition: In their own words, what does "working" look like?
Part 3: Customer Interview Frameworks
Interviews are your most direct access to customer language. The goal is not to validate your ideas. The goal is to understand their world before your product entered it.
The Jobs-to-Be-Done (JTBD) Interview Framework
JTBD research asks: what progress was the customer trying to make when they hired your product?
The canonical JTBD interview focuses on the purchase moment. You reconstruct the story of how they went from "I have a problem" to "I bought this specific thing."
JTBD Interview Structure:
Start by anchoring to the decision:
- "Think back to when you first signed up. What was going on that made you start looking?"
- "What day of the week was it? Were you in a meeting, at your desk, somewhere else?"
Explore the struggle:
- "How long had this been a problem before you did something about it?"
- "What had you already tried? What happened when you tried those things?"
Examine the evaluation:
- "When you went looking for a solution, what did you search for?"
- "What options did you consider? How did you narrow it down?"
Probe the decision moment:
- "What was it specifically that made you choose us?"
- "Was there anything that almost made you not sign up?"
Understand the context:
- "Who else was involved in the decision?"
- "What did you have to convince yourself (or someone else) of before you moved forward?"
The Switch Interview (Competing for Attention)
When you want to understand switching behavior specifically, the switch interview maps the timeline from their old solution to yours.
Ask:
- "What were you using before? What did a typical week look like with that tool?"
- "When did you first start thinking it wasn't good enough anymore?"
- "What was the first thing you did when you decided to look for something different?"
- "What almost made you stay with [old solution]?"
This interview surfaces the "push" (what drove them away from the old solution) and the "pull" (what attracted them to yours). Both are marketing gold.
Interview Logistics
Recruit through email to active users, your support ticket list, or a Calendly link in your product. Aim for 30 to 45 minutes per session. Record with permission. Transcribe with Otter or Descript.
Offer something specific in return: a gift card, an extended trial, or a product credit. Make the offer concrete so people show up.
After each interview, write a one-paragraph summary immediately. Do not rely on transcripts alone. Your immediate impressions capture things transcripts miss.
Part 4: Survey Design and Analysis
Surveys work best when you know roughly what you're looking for and need to quantify it at scale.
When to Use Surveys
Use surveys when:
- You need to validate a pattern you've already seen qualitatively.
- You want to rank options by priority among a large group.
- You need quantitative data to make a budget or roadmap case.
- You want to segment responses by customer tier or cohort.
Do not use surveys when:
- You don't yet know what questions to ask.
- Your sample size will be under 50 responses (use interviews instead).
- You need nuanced language; surveys return opinions, not stories.
Survey Design Principles
Keep it short. Five to seven questions for external surveys. If you need more, split into two surveys at different times.
Use one question per question. "How useful and easy to use is our product?" is two questions.
Avoid leading questions. "How much has our product improved your workflow?" assumes it has. Ask instead: "How has your workflow changed since using our product?"
Use open-ended questions strategically. Include at least one open-text question. The write-in answers are where the real insights live.
Sequence matters. Start with behavioral questions (what they do), then attitudinal questions (what they think). End with open text.
Survey Templates by Use Case
Post-signup survey (3 questions):
- What's the main thing you're trying to accomplish with [product]?
- What were you using before, or what's your current approach?
- What would make [product] a success for you in the first month?
Churn survey (4 questions):
- What's your main reason for canceling?
- What did you use [product] for while you had it?
- What would have needed to be different for you to stay?
- What will you use instead?
NPS follow-up (for detractors and passives):
- What's one thing we should fix or improve?
- What's the main thing holding you back from getting more value?
Feature priority survey:
- Which of these [list features] would be most valuable to you?
- Which one would you pay more for?
- What's missing from this list?
Analyzing Survey Results
Export to a spreadsheet. Separate quantitative and qualitative columns.
For open-text responses:
- Read all responses before tagging anything.
- Identify 5 to 10 recurring themes.
- Tag each response with the relevant theme(s).
- Count frequency. Weight by customer tier if your data allows.
Look for the unexpected. The responses that don't fit your existing categories are often the most valuable.
Part 5: Voice of Customer (VOC) Methods
Voice of customer is a specific practice: capturing the exact words, phrases, and language your customers use when describing their problems and goals.
VOC research feeds directly into your copywriting. The best headlines, email subject lines, and ad copy come from customers, not from your team brainstorming in a room.
VOC Data Sources
Support tickets and chat logs: Search your helpdesk for tickets about specific topics. Look at how customers describe problems in their own words. "I can't figure out how to get my report to show only the current month" tells you something about the mental model and the language you should use.
Sales call recordings: Use Gong, Chorus, or Loom recordings of sales calls. Listen for the phrases prospects use before they understand your product. The language they use to describe their problem before you explain your solution is the language your homepage should use.
Onboarding call notes: What questions do people ask during onboarding? What confuses them? What are they excited about?
Win/loss interviews: Talk to recent wins and recent losses. Both teach you what matters in the buying decision.
Review platforms: G2, Capterra, Trustpilot, app stores. These are structured, public VOC data. More on this in the review mining section.
Building a VOC Library
Create a living document (Notion, Airtable, or a spreadsheet) where you store customer quotes organized by:
- Theme (e.g., "pain before purchase," "outcome achieved," "competitor comparison," "specific feature love")
- Customer tier (e.g., enterprise, SMB, individual)
- Data source (interview, review, support ticket)
Refer to this library every time you write copy. Pull exact phrases. Replace your assumed language with their actual language.
Part 6: Review Mining
Reviews on G2, Capterra, Trustpilot, Reddit, and app stores are pre-written customer research. People write reviews unprompted, which means the language is uninfluenced by your questions.
Where to Mine Reviews
G2 and Capterra: Search your product and every competitor. Read reviews for your product (what they love, what they hate). Read competitor reviews (what competitor customers wish were different).
Reddit: Search "[your category] Reddit" or "[competitor name] Reddit." Look for threads where people ask for tool recommendations. The replies describe what people actually care about. Look for threads about frustrations with current tools.
App stores: For mobile products. Look at one-star and five-star reviews. Three-star reviews often have the most nuanced feedback.
Amazon: If there are books in your category, read the reviews. What do people say a book helped them with? What did they wish the book covered? These are content and messaging opportunities.
Twitter and LinkedIn: Search for your product name, competitor names, and category terms. Filter to posts with replies or engagement.
How to Structure Review Mining
Create a spreadsheet with columns:
- Source (G2, Capterra, Reddit, etc.)
- Review text (copy the exact words)
- Sentiment (positive, negative, mixed)
- Theme (pain, outcome, feature, competitor comparison, context)
- Customer segment if identifiable
After you've collected 50 to 100 data points, sort by theme. Look for:
- The most common pain mentioned across negative reviews of competitors (your opportunity).
- The outcome mentioned most frequently in positive reviews of your product (your positioning hook).
- The words used repeatedly to describe the problem (your copy language).
- The objections or hesitations mentioned in mixed reviews (your FAQ and onboarding content).
Competitor Review Analysis
Go to your top three competitors on G2. Filter to three-star reviews. Read what people wished were different.
Those unmet expectations are your product's positioning opportunities. If three-star reviewers of Competitor A keep saying "it's powerful but too complex for our small team," and your product is simpler, that's your headline.
Part 7: Digital Watering Holes Research
Watering holes are the places your ideal customers congregate online. Finding them is an underused research method.
Finding Watering Holes
Start by asking your best customers directly: "Where do you go to learn about [your category] or talk shop with peers?" Common answers include:
- Specific Slack communities (e.g., "Online Geniuses" for marketers, "Exit Five" for B2B marketing).
- LinkedIn groups.
- Reddit subreddits (r/entrepreneur, r/marketing, r/webdev, etc.).
- Facebook groups.
- Newsletters with active comment sections.
- Specific conferences or event communities.
- Discord servers.
- Niche forums (Hacker News for technical audiences, Indie Hackers for bootstrapped founders).
What to Do in Watering Holes
Do not go in to promote. Go in to observe.
Read threads where people discuss problems in your category. Note the exact language. Note what solutions they mention and what they say about those solutions. Note what questions come up repeatedly.
After two to four weeks of observation, you will have a list of:
- Recurring questions (content opportunities).
- Common frustrations (positioning and messaging opportunities).
- Language patterns (copy language).
- Influencers and community leaders (partnership opportunities).
You can also participate authentically by answering questions, which builds brand awareness without promotion.
Part 8: Building Customer Personas
A persona is a synthesis of research, not a guess. If you build a persona before doing research, you're writing fiction.
What a Research-Based Persona Contains
Name and context: Give the persona a name and a specific job. "Sarah, Head of Marketing at a 50-person B2B SaaS company" is specific. "Marketing Manager" is not.
Trigger event: What specific situation triggers her to start looking for a solution like yours? "Her team just doubled and the manual reporting process is breaking down" is a trigger. "She wants to be more efficient" is not.
Current workflow: How does she do this job today, before your product? What tools does she use? What's the manual part? What's the painful part?
Desired outcome: What does she want to be true in 90 days? Not "use the product more" but "spend four fewer hours per week on reporting and get buy-in from her VP on the new dashboard."
Objections and hesitations: What might stop her from buying? Budget approval process, concern about implementation time, team adoption risk.
Exact phrases she uses: Pull directly from interviews and reviews. "I just need something that doesn't require me to explain it to everyone" is a real person's words. Use them.
Persona Anti-Patterns
Avoid personas that contain:
- Demographics with no connection to buying behavior (age, gender).
- Psychographics that could apply to anyone ("values quality," "goal-oriented").
- Aspirations disconnected from your product.
- Stock photo plus a paragraph of speculation.
A persona is only useful if it changes a decision. If your persona doesn't change what you write or who you target, it's decorative.
Part 9: Turning Research Into Messaging
Research is only useful if it changes what you say and how you say it.
The Research-to-Messaging Process
Step 1: Cluster your data.
Group all your qualitative data (interview quotes, VOC snippets, review excerpts) by theme. Common themes: trigger event, functional outcome, emotional outcome, competitor frustrations, specific features that matter.
Step 2: Identify the highest-frequency, highest-intensity themes.
Frequency means how often something came up. Intensity means how strongly people feel about it. A problem mentioned by 80% of interviewees in passing is less useful than a problem mentioned by 30% of interviewees with visible frustration.
Step 3: Match themes to messaging pillars.
Your homepage, email sequence, and ads should each focus on one to three core messages. Map your research themes to these pillars.
Step 4: Write in their language.
Use the exact phrases from your research. If three customers independently said "I was drowning in spreadsheets," that's your headline, not a paraphrase.
Step 5: Test your messaging against your research.
Read your draft copy and ask: would the customers you interviewed recognize this as describing their problem? If not, you've drifted into your own language.
From Research to Homepage Copy
Your hero section should answer three questions your customer has:
- Is this for me?
- What does it do?
- Why should I believe it?
Pull the trigger event language for the hero headline. Pull the outcome language for the subheadline. Pull the specific feature language for the feature section. Pull review quotes for the social proof section.
From Research to Email Copy
Your welcome email should reference the trigger event that brought someone to your product. Your onboarding emails should address the hesitations and confusion points you found in support tickets and interviews. Your case study emails should use the outcome language from your best customer interviews.
Part 10: Synthesizing a Research Report
After a round of research, write a synthesis document that the whole team can use. Keep it short and specific.
Structure:
- Research question (one sentence).
- Methods used and sample size.
- Key findings (5 to 10 bullet points with supporting quotes).
- ICP profile (updated or confirmed).
- Messaging implications (specific copy suggestions).
- Open questions (what you still need to learn).
Share this document in Slack or Notion. Reference it in copy reviews. Update it every quarter or after any major research project.
The goal is a living record that keeps your marketing grounded in what customers actually say, not what you assume they feel.
Research Cadence Recommendation
Research is not a one-time project. Build a rhythm:
- Weekly: Read five support tickets. Flag interesting language.
- Monthly: Read 10 to 20 new G2 or Capterra reviews (yours and competitors).
- Quarterly: Run three to five customer interviews focused on a specific question.
- Annually: Full ICP review. Survey your customer base. Update personas.
If you do this consistently, you will always know more about your customers than your competitors know about theirs. That knowledge gap compounds over time.