How to Use Sentiment Analysis to Prioritise Your Product Roadmap (Without Guesswork)
Discover how sentiment analysis can transform your product roadmap prioritisation from guesswork into data-driven decision making, helping you focus on what truly matters to your users.
If you're a founder or PM at a small SaaS, you're drowning in feedback. Feature requests in your inbox, bug reports in support tickets, opinions in Slack and Discord.
You know you should be data-driven, but roadmap decisions still feel like educated guesswork.
Sentiment analysis gives you a way to bring the emotional reality of your users into those decisions—without reading every comment by hand.
Why Traditional Prioritisation Misses the Emotional Context
Most teams look at:
- Number of requests
- ARR or plan level of requesting customers
- Strategic fit with company vision
But this misses a critical dimension: how strongly people feel about an issue.
Two examples:
- 50 users are mildly annoyed by a missing filter
- 7 users are furious that invoices fail silently and cause client embarrassment
Looking only at "number of requests," the filter wins. But considering emotional intensity, the billing issue is far more urgent.
What Traditional Prioritisation Misses
- Intensity of frustration
- Emotional impact on users
- Hidden risk from a few high-value, very unhappy customers
Sentiment analysis captures that emotional context and brings it into your roadmap discussions.
What Sentiment Analysis Actually Does
Sentiment analysis turns unstructured text (feedback, tickets, reviews) into a score about how someone feels.
A good sentiment system can:
- Detect tone: positive, negative, or neutral
- Measure intensity: slightly annoyed vs absolutely furious
- Pick up specific emotions like frustration, confusion, delight
Examples:
- "The new dashboard is great, but it's a bit slow sometimes" → mildly positive with a negative note
- "This bug has cost us real money. We're considering alternatives if this isn't fixed soon." → strongly negative, high urgency
It gives you a consistent, scalable signal to combine with other data (like ARR and feature usage) for better decisions.
The 3 Dimensions of Feedback That Matter
Think about feedback across three dimensions:
- Sentiment – How users feel
- Impact – Who is affected and how critical it is
- Frequency – How often it comes up
Most teams look at frequency and sometimes impact. Very few systematically include sentiment.
When you combine all three, you get a much clearer picture of what truly matters.
A Simple Scoring Model Using Sentiment
Use this simple model:
- Sentiment score: -5 (very negative) to +5 (very positive)
- Impact score: 1–5 based on segment/plan/usage
- Frequency score: 1–5 based on how often it appears
| Issue | Sentiment | Impact | Frequency | Priority Score | Action |
|---|---|---|---|---|---|
| Invoice Bug | -5 | 5 | 2 | 10 | Fix Now |
| Analytics Filter | -2 | 3 | 5 | 6 | Plan Later |
| Dark Mode | 0 | 2 | 4 | 4 | Backlog |
Even though the analytics filter and dark mode have more mentions, the invoice bug is clearly more urgent because of extreme negative sentiment and high impact.
How Sentiment Changes Roadmap Conversations
Scenario 1: Low-frequency, extremely negative issue
Few tickets mention a billing bug, but all are very negative from high-value customers.
Traditional view: "Only a few customers affected."
Sentiment-aware view: "Serious churn risk; fix now."
Scenario 2: Medium-negative issue trending upward
Onboarding feedback is moderately negative, with volume and negativity increasing.
Traditional view: "Onboarding could be better."
Sentiment-aware view: "If we don't address this, conversion and retention will suffer."
Scenario 3: Popular but low-intensity requests
Many users ask for a nice-to-have feature with only slightly negative or neutral sentiment.
Traditional view: "Everyone is asking for this."
Sentiment-aware view: "Important, but can wait behind more painful issues."
Using Sentiment Trends to Spot Emerging Problems
Track sentiment over time for:
- Specific features
- Onboarding experience
- Pricing and billing
Early Warning Example
Sentiment for onboarding drops from mildly positive to clearly negative over four weeks, while feedback volume rises. This is an early warning—you can fix friction before it shows up as churn.
Practical Workflow: From Feedback to Prioritised Roadmap
Centralise Feedback
Gather feedback from support, in-app widgets, surveys, sales notes, and communities into one place.
Apply Sentiment Analysis
Use automated sentiment scoring where possible to assess how users feel about each issue.
Combine the Three Dimensions
Create priority scores by combining sentiment + impact + frequency into a single metric.
Review Top Issues
Use top-scoring issues in roadmap meetings instead of relying on anecdotes or gut feel.
Make Informed Decisions
Decide what to build now, later, or never—using scores as input, not as the only decision-maker.
Where AI Helps (And Where Humans Still Matter)
AI is Great For
- Consistent scoring at scale
- Surfacing patterns and outliers
- Detecting sentiment trends over time
Humans Are Needed For
- Strategic trade-offs
- Interpreting subtle context
- Protecting long-term product vision
The best setup is AI plus human judgment: AI does the heavy lifting, your team makes strategic decisions.
Getting Started With Sentiment-Driven Prioritisation
You don't need to overhaul everything on day one.
If you don't have tools yet:
- Take a sample of recent feedback and manually tag sentiment
- Note which accounts are high-value
- Group into themes and score impact and frequency
- Use this as input to your next roadmap meeting
If you're using a tool like FeedbackNexus:
- Turn on automatic sentiment analysis for all feedback
- Use built-in priority scoring that combines sentiment, impact, and frequency
- Track sentiment trends for key features, onboarding, and pricing
- Review top-priority issues before each planning session
Next Steps
Want to see sentiment analysis in action? Start a 5-day free trial of FeedbackNexus.
You'll get automatic sentiment and priority scoring from day one, so you can stop guessing what to build next and start using your users' emotions as a clear, data-backed signal for your roadmap.