Customer Interviews
5-10 conversations about problems, constraints, and alternatives
- Direct insights
- Real vocabulary
- Clear pain points
Early-stage startups often lack clear ICPs and firm category definitions. This guide shows how to do credible, data-driven keyword research before product-market fit—by mining problems, jobs-to-be-done, competitor SERPs, and zero-volume demand signals—then clustering, validating, and prioritizing topics with a lean, AI-assisted workflow.
When you're early and unsure about target customers or categories, you can still do high-signal keyword research. This playbook starts from problems and jobs-to-be-done, uses competitor SERPs and user-generated language to find real demand, then clusters topics by intent and validates them with SERP evidence.
| Step | What You Do | Key Signals |
|---|---|---|
| Map Problems & Jobs-to-be-Done | Interview target users; extract problems and vocabulary | Verbatim phrases, constraints, alternatives |
| Mine Public Language | Scan forums, communities, app reviews, Q&A sites | Problem phrasing, synonyms, objections, outcomes |
| Seed & Expand | Start with problem phrases; expand via autosuggest and related searches | Long-tail variants, questions, comparisons |
| Competitor SERP Analysis | Analyze pages that rank; note content types and gaps | Intent fit, authority requirements, content patterns |
| Cluster & Label Intent | Group by problem and intent (informational, comparative, transactional) | Pillar candidates, supporting content, funnel alignment |
| Validate by SERP | Check page types ranking, SERP features, authority needed | Buildability, content requirements, opportunity assessment |
5-10 conversations about problems, constraints, and alternatives
Reddit, Slack groups, industry communities for raw language
Scrape reviews for pains, outcomes, and competitor mentions
Use autosuggest and People Also Ask for question variants
Analyze top ranking pages for content type and depth
Aggregate themes from user questions and prospect interactions
Generate theme summaries and candidate seed phrases from anonymized excerpts
Group expanded terms by problem and intent; create draft cluster maps
Inventory SERP features for representative queries and content requirements
Create outline templates with FAQs and internal link suggestions
Identify recurring phrases and terminology across multiple sources
No PII in prompts; human verification of facts; SERP validation required
| Intent | SERP Clues | Recommended Content | Notes |
|---|---|---|---|
| Informational (Learn) | How-to guides, PAA, long-form articles | Guides, checklists, FAQs, glossary | Use supporting posts to feed pillars |
| Comparative (Evaluate) | Best-of lists, vs pages, roundups | Comparison pages, alternatives, buying guides | High conversion assist; unbiased tone |
| Transactional (Act) | Product pages, pricing snippets, reviews | Landing pages with clear CTAs, pricing | Link from informational with relevant anchors |
| Local (Near Me) | Map pack, local directories, service pages | Location pages, GBP optimization, citations | NAP consistency and local proof required |
Match SERP preferences for guides, lists, or landing pages
Evaluate if you can compete with current ranking domains
Determine update frequency needed for topic relevance
Identify concepts, tools, and frameworks in top results
Plan for FAQs, video, comparison tables, and local signals
Define pillar/supporting relationships and link paths
| Factor | Definition | Weight | Assessment Guide |
|---|---|---|---|
| Impact | Expected business outcome and conversion potential | 35% | Relevance to core problem, funnel stage, volume potential |
| Effort | Content, SME, design, and engineering requirements | 20% | Content type complexity, asset needs, approval dependencies |
| Confidence | Evidence strength from SERP analysis and user language | 25% | SERP feature match, page-type fit, interview validation |
| Time-to-Value | Speed to first observable signals and traction | 20% | Publishing timeline, indexing speed, early signal potential |
Conduct interviews, mine public language, extract verbatim phrases
Analyze SERPs, validate content fit, cluster by intent and topics
Create detailed briefs, publish pilot pages, implement internal links
Track early signals, optimize snippets, plan next sprint
| KPI | Target | Measurement | Cadence |
|---|---|---|---|
| Source Coverage | 5-10 interviews + 5-8 public sources | Discovery documentation | Per cluster |
| SERP Validation Rate | ≥ 80% pass content-type fit | SERP review checklist | Weekly |
| Brief Throughput | 6-8 briefs/week per team | Brief tracker | Weekly |
| Time-to-First-Signal | Impressions within 2-4 weeks | GSC page group analysis | Weekly |
| CTR Improvement | +10-20% vs SERP baseline | GSC CTR comparison | Monthly |
| Cluster Coverage | 1 pillar + 3-5 supporting pages | Cluster map tracker | Monthly |
Targeting high-volume keywords without clear intent or realistic authority
Using generic personas instead of verbatim customer vocabulary
Relying solely on keyword tools without analyzing ranking pages
Publishing without connecting to pillar pages and related content
Letting AI write claims or statistics without human verification
Creating automated pages without unique value or quality controls
Clear triggers, models, and ROI for bringing in external guidance—augmented responsibly with AI
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Read more →We'll help you discover, validate, and prioritize topics that fit your product and audience—even before product-market fit.