Why Build Another CRM?
Customer Relationship Management (CRM) software remains one of the most competitive markets in B2B SaaS. With giants like Salesforce, HubSpot, and Pipedrive dominating the landscape, you might wonder: is there room for another player?
The answer lies in proper product discovery. By deeply understanding specific market segments, identifying underserved user personas, and validating assumptions before building, teams can find genuine opportunities even in crowded markets.
In this use case, we'll walk through how a product team might use CastSpells to research, validate, and plan a new CRM product from the ground up. We'll demonstrate the complete product discovery workflow, from understanding the market landscape to creating user personas and validating key hypotheses.
What You'll Learn
- How to analyze a competitive market using AI-powered research
- Techniques for identifying underserved segments within established markets
- Building detailed user personas based on real market data
- Validating product-market fit hypotheses before writing code
Market Analysis: The Foundation of Product Discovery
Before diving into features or user interviews, smart product teams start with comprehensive market research. Understanding market size, growth trends, competitive dynamics, and customer segments provides the foundation for all subsequent product decisions.
CastSpells uses AI to accelerate this research, pulling from thousands of sources to build a comprehensive market picture. Let's examine what we discovered about the CRM market.
Generate Market Research with AI
The market analysis above was generated using CastSpells' AI-powered research capabilities. Here's how you can create similar research for your product:
- Create a new Market entity - Navigate to the Markets section and click "New Market"
- Describe your target market - Enter a brief description like "CRM software for mid-market B2B sales teams"
- Let AI generate research - Click "Generate with AI" to have CastSpells pull market data, size estimates, growth projections, and competitive landscape
- Refine and customize - Edit the generated content, add your own insights, and adjust projections based on your research
CastSpells automatically identifies market segments, tracks technology trends, and maps out the competitive landscape—work that would typically take weeks of manual research.
Learn more: Market Research Documentation
From Market Data to User Personas
Market analysis tells us where the opportunity exists. User personas tell us who we're building for and why they'll choose our solution.
Through our research, we identified several underserved user segments within the CRM market. One particularly promising opportunity emerged: mid-market sales managers who find enterprise CRMs too complex and SMB tools too limited.
Let's examine the persona we developed to represent this target user.
Build Data-Driven Personas
The persona above combines demographic data, psychographic insights, and Jobs to Be Done—all structured to inform product decisions. Here's how to create personas in CastSpells:
- Create from market data - Link your persona to a Market entity to inherit segment insights
- Use AI to generate initial profile - Describe your target user and let AI draft demographics, psychographics, and JTBD
- Add Jobs to Be Done - Structure user needs using the JTBD framework: "When [situation], I want [motivation], so I can [outcome]"
- Connect to validation - Link personas to interview evidence and validation data to keep them grounded in reality
Personas in CastSpells aren't static documents—they evolve as you gather more evidence and can be linked to hypotheses, experiments, and roadmap items.
Learn more: Persona Documentation
From Assumptions to Evidence
Before investing in product development, smart teams identify and test their riskiest assumptions. CastSpells helps you structure hypotheses and track insights as you validate them through research.
Our Key Hypotheses
Based on our market analysis and persona research, we identified four critical hypotheses to validate:
| Hypothesis | Risk Level | Status |
|---|---|---|
| H1: Mid-market sales managers are underserved by current CRM options | High | Validated |
| H2: CRM adoption failure is primarily a UX problem, not a feature problem | High | Validated |
| H3: AI-powered automation can meaningfully reduce admin burden | Medium | Partially Validated |
| H4: Managers would pay a premium for higher adoption rates | Medium | Validated |
Key Insights Discovered
Through user interviews and competitive analysis, CastSpells helped us extract and cluster these insights:
Insight Cluster: "The Mid-Market Gap"
"We outgrew HubSpot but Salesforce feels like overkill. We're stuck in this weird middle ground." — Sarah M., SaaS Sales Manager
- 87% of interviewees expressed frustration with current CRM options
- The "stuck in the middle" theme appeared in 19 of 24 interviews
- Key driver: Enterprise tools require dedicated admins; SMB tools lack workflow sophistication
Insight Cluster: "Adoption Over Features"
"Rep adoption is my #1 KPI for any tool we buy. I don't care how many features it has if people won't use it." — Marcus T., B2B Services Sales Director
- "Ease of use" ranked #1 requirement in 21/24 responses
- "Advanced features" appeared in only 6/24 top-3 lists
- Managers spend 15-20% of their time on CRM compliance, not coaching
Insight Cluster: "Show Me, Don't Tell Me"
"Every CRM promises to 'save time.' Show me the data. Show me it actually works." — Jennifer K., Tech Sales Manager
- High AI interest (8.2/10 average) but significant skepticism
- Past experiences with overpromised features create trust deficit
- Demand for provable ROI and adoption metrics built into the product
Insight Cluster: "Willingness to Pay"
- 71% would pay 20-30% premium for proven higher adoption rates
- Key condition: adoption metrics must be visible in the product itself
- Switching costs are acceptable if value proposition is clear
Track Hypotheses and Extract Insights
CastSpells provides structured tools for assumption mapping and insight extraction:
Hypothesis Tracking:
- Create hypotheses - Define your riskiest assumptions with clear success criteria
- Categorize by dimension - Tag hypotheses as Desirability, Viability, or Feasibility
- Link to experiments - Connect each hypothesis to the interviews or tests that will validate it
- Track status - Mark as Validated, Invalidated, or Partially Validated as evidence comes in
Insight Extraction:
- Import interview notes - Paste transcripts or notes from user interviews
- AI-powered clustering - CastSpells identifies recurring themes and patterns across interviews
- Link insights to hypotheses - Connect discoveries to the assumptions they support or refute
- Build evidence chains - Create traceable connections from raw data to product decisions
The insight clustering feature saves hours of manual affinity mapping while ensuring you capture patterns you might otherwise miss.
Learn more: Hypothesis Tracking | Data & Insights
Structured Interview Templates
The validation evidence above came from structured user interviews. CastSpells provides interview templates that help you:
- Prepare consistent questions - Ensure you ask the right questions to validate specific hypotheses
- Capture insights in real-time - Record observations during the interview
- Extract patterns automatically - AI analyzes interview transcripts to surface recurring themes
Let's look at the interview template we used for our CRM discovery research.
Run and Analyze User Interviews
CastSpells transforms user interviews from scattered notes into structured, actionable insights. Here's the workflow:
- Create an Experiment - Choose "Interview" as the experiment type and select a template (Problem Discovery, Solution Validation, etc.)
- Customize your interview guide - Edit the template questions to focus on your specific hypotheses
- Record interview trials - After each interview, create a Trial to capture notes, quotes, and observations
- Extract insights with AI - CastSpells analyzes your interview notes to identify patterns, sentiment, and recurring themes
- Link insights to hypotheses - Connect findings to the hypotheses they support or refute
The AI-powered insight extraction saves hours of manual analysis while ensuring you don't miss important patterns across multiple interviews.
Learn more: Interviews & Trials
From Insights to Strategy
Our research revealed a clear product strategy direction:
Core Value Proposition
"The CRM your sales team will actually use."
Unlike enterprise CRMs that prioritize management reporting over rep experience, or SMB CRMs that sacrifice functionality for simplicity, we'll build a CRM that earns adoption through genuine value to individual sales reps while delivering the insights managers need.
Key Strategic Pillars
-
Rep-First Design
- Every feature must pass the "Would a rep choose to use this?" test
- Minimize required fields and manual data entry
- Surface insights at the moment they're useful, not in separate dashboards
-
Intelligent Automation
- Auto-log emails, calls, and meetings
- Smart suggestions for next best actions
- Automatic data enrichment from public sources
-
Adoption Metrics Built-In
- Show managers which reps are actually using the system
- Correlate CRM usage with sales outcomes
- Prove ROI to justify the purchase decision
-
Mid-Market Focus
- Pricing for 25-200 user teams
- Self-serve onboarding with optional white-glove support
- Feature set between HubSpot and Salesforce
Next Steps
With this strategy validated, the team would move into:
- Detailed user story mapping
- Technical architecture planning
- MVP scope definition
- Go-to-market strategy development
All of these activities can be continued within CastSpells, creating a single source of truth for product discovery.
The next step is to create a Product Requirements Document (PRD) that captures our validated strategy and translates it into actionable requirements.
Build Evidence-Backed PRDs
CastSpells PRDs are different from traditional documents—they're living artifacts connected to your research:
- Create from validated insights - Start your PRD after validating hypotheses, automatically linking to supporting evidence
- Reference personas and markets - Embed persona and market entities directly in PRD sections
- Structure requirements clearly - Use sections for Problem, Users, Requirements, Success Metrics
- Track changes over time - PRD versioning shows how requirements evolved as you learned more
- Generate with AI assistance - Describe your product and let AI draft initial PRD sections based on your research
The key advantage: every requirement in your PRD traces back to validated insights and user evidence, making stakeholder alignment easier and reducing "opinion-driven" product debates.
Learn more: PRD Documentation
Start Your Own Product Discovery Journey
This use case demonstrated how CastSpells enables product teams to:
- Research markets with AI-powered analysis that would take weeks to compile manually (Learn more)
- Build personas grounded in real market data and validated through research (Learn more)
- Run structured interviews with templates and AI-powered insight extraction (Learn more)
- Track hypotheses and insights with structured evidence collection and clustering (Learn more)
- Create evidence-backed PRDs that trace requirements back to validated research (Learn more)
Every entity you create in CastSpells is interconnected—markets link to personas, personas link to hypotheses, hypotheses link to experiments, and experiments generate insights that inform your roadmap. This creates a complete, traceable product discovery workflow.
Whether you're exploring a new product idea, entering an adjacent market, or trying to understand why your current product isn't gaining traction, CastSpells provides the tools and AI assistance to accelerate your product discovery process.
Ready to Get Started?
Try CastSpells free and see how AI-native product discovery can transform your approach to building products people actually want.
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