The Research Hub is the analyze layer of Deeto’s research stack. It turns VoC data collected through AI Interviews into structured intelligence — win/loss studies, sentiment tracking, competitive analysis, and product feedback research. If you haven’t set up AI Interviews yet, start with AI Interviews — Overview.
1. Setting up your first research project
Your first research project sets the foundation for your customer intelligence program. Choose a project where you already have good data and real stakeholder interest. Pre-launch checklist- Confirm Research Hub is activated and accessible
- Verify you have 50+ VoC assets connected — interviews, surveys, reviews, feedback
- Identify your first research question (see recommended projects below)
- Confirm at least one stakeholder who will act on the results
- Set a timeline for your first findings review (3 weeks recommended)
Win/Loss Analysis
Start here if you have deal outcome data. Sales and product marketing teams see value immediately. Research question: “Why are we winning and losing deals, and what patterns emerge across segments?”
Product Feedback Research
Start here if you have strong product usage data. Product teams can act on this right away. Research question: “What are our customers’ top pain points and feature requests, and how do they vary by segment?”
Customer Health Tracking
Start here if you have broad feedback from across your customer base. CS leadership can spot trends and risk signals. Research question: “What’s the overall sentiment trend, and which accounts show risk signals?”
2. Designing effective research projects
A well-scoped project produces findings people act on. A poorly scoped one produces interesting data that sits in a report. Project scoping framework
Data quality checklist
- Are your data sources connected and flowing?
- Do you have enough data points? (50+ for most projects)
- Is the data recent enough to be relevant? (6 months or less for most research)
- Are there known gaps? Consider launching an AI Interview campaign to fill them
3. Using AI Interviews within research
Research Hub and AI Interviews work together. Use AI Interviews when your existing data identifies a pattern but you need to understand the “why” behind it. When to add AI Interviews to a project- Your research identifies a pattern but needs deeper qualitative context
- You have a hypothesis that needs validation from a larger sample
- A specific segment is underrepresented in your current VoC data
- You want to test a new research question before committing to a full project
4. Presenting findings to stakeholders
Research only creates value when people act on it. Tailor your delivery to each audience.This table covers presenting structured research project findings — synthesized across multiple data sources over time. For sharing individual campaign results right after they close, see AI Interviews: Best Practices.
Presentation best practices
- Lead with the finding, not the methodology — “Customers say X” not “We analyzed 500 responses”
- Include 2–3 direct customer quotes to bring findings to life
- End every presentation with specific recommended actions
- Follow up in 2 weeks to check whether findings led to decisions
5. Building a research cadence
Move from one-off projects to a recurring research program that drives continuous intelligence.This cadence covers ongoing research projects inside the Research Hub — how often you run and review each project type. For scheduling individual AI Interview campaigns, see AI Interviews: Best Practices.
Program maturity checklist
- At least 2 research projects running simultaneously
- Findings presented to stakeholders within 1 week of project milestones
- At least 1 strategic decision per quarter informed by research data
- Research requests coming inbound from stakeholders, not just initiated by your CSM
- Research Hub metrics reviewed in executive check-ins
6. Measuring success
7. Troubleshooting
Findings seem surface-level
Findings seem surface-level
Check data volume and diversity. Most projects need 100+ data points across multiple source types. Consider launching an AI Interview campaign to add qualitative depth to aggregate patterns.
Stakeholders aren't engaging with results
Stakeholders aren't engaging with results
You may be delivering in the wrong format. Ask each stakeholder what format they prefer. Lead with the “so what” — what it means for the business — before diving into data.
Not sure what to research next
Not sure what to research next
Ask your stakeholders: “What’s the biggest customer-related question you can’t answer today?” Their answer is your next project.
Too many projects, not enough depth
Too many projects, not enough depth
Consolidate. Better to run 2 rich projects than 5 thin ones. Prioritize by stakeholder demand and business impact.
Data from different sources is conflicting
Data from different sources is conflicting
This is actually a finding. Conflicting signals often mean different segments have different experiences. Slice by segment and you’ll find the real story.
Support
Contact your Deeto Customer Success Manager or email support@deeto.ai.AI Interviews: Best Practices
Running campaigns, maximizing response rates, and sharing campaign-level results.
AI Insights
Query all your collected data in natural language at any time.