Feature Prioritization Using Reddit Feedback

Your backlog is full of feature ideas. You cannot build them all. How do you decide what to build first?

Reddit feedback helps you prioritize based on what users actually need, not what they claim to want.

Why Traditional Prioritization Fails

Common approaches:

• Loudest customer wins: Squeaky wheel gets attention
• HiPPO: Highest Paid Person's Opinion decides
• Gut feeling: Whatever seems right
• Sales requests: Whatever closes deals

These approaches optimize for noise, not signal.

The Reddit Prioritization Advantage

Reddit reveals:

• Frequency: How often is this requested?
• Intensity: How badly do people want it?
• Context: Why do they want it?
• Alternatives: What do they do without it?

The Feature Prioritization Framework

Step 1: Collect Feature Mentions

Search for feature requests in relevant subreddits:

Direct requests:

• "I wish [product] had"
• "[Product] needs to add"
• "Feature request for [product]"
• "Would be great if [product]"

Indirect signals:

• "Had to switch because [product] lacks"
• "Using [competitor] for this because"
• "Workaround for [missing feature]"

Step 2: Categorize by Type

Core features: Essential functionality gaps

Enhancement: Improvements to existing features

Integration: Connections to other tools

UX: Interface and experience improvements

Edge cases: Niche needs from small segments

Step 3: Score Each Feature

Rate each feature on four dimensions:

Frequency (1-5)

• How many times is this mentioned?
• 1 = Rare
• 5 = Very common

Intensity (1-5)

• How emotionally do people express the need?
• 1 = "Would be nice"
• 5 = "Deal-breaker without this"

Breadth (1-5)

• What percentage of users need this?
• 1 = Very niche
• 5 = Universal need

Urgency (1-5)

• How pressing is the need?
• 1 = Someday
• 5 = Blocking them now

Total = Frequency + Intensity + Breadth + Urgency

Reading Between the Lines

What They Ask For vs What They Need

Request: "Add dark mode"

Real need: Working at night causes eye strain

Insight: Maybe auto-brightness settings solve it too

Request: "Integration with Slack"

Real need: Team members miss updates

Insight: Better in-app notifications might suffice

Questions to Ask

For each feature request:

• What problem triggers this request?
• Is there a simpler solution to that problem?
• Would they still want this if the problem was solved differently?

Prioritization Red Flags

1. Feature Parity Requests

"[Competitor] has this, why do you not?"

Reality: Users often ask for features they will never use just because competitors have them.

How to handle: Check if people actually use that feature in competitor discussions.

2. Power User Requests

Complex features requested by heavy users.

Reality: Power users are vocal but small in number. Building for them can hurt the majority.

How to handle: Check if the request also appears from regular users.

3. Hypothetical Features

"I would definitely use X if you built it."

Reality: People are bad at predicting their own behavior.

How to handle: Look for evidence of actual behavior changes, not just stated preferences.

Finding Signal in Noise

High Signal Indicators

• Multiple people independently requesting the same thing
• Requests include specific use cases
• People describe workarounds they currently use
• Frustration is tied to real workflow impact
• Request appears across multiple subreddits

Low Signal Indicators

• Single mention with no upvotes
• Vague requests without context
• No explanation of the problem it solves
• Only appears in one niche community
• Contradicts other frequent requests

The Prioritization Matrix

Plot features on two axes:

X-axis: User Value (from Reddit research)

• Low: Few requests, mild intensity
• High: Many requests, strong intensity

Y-axis: Development Effort

• Low: Quick to build
• High: Significant investment

Quadrants

Quick Wins (High Value, Low Effort)

Build these first.

Strategic (High Value, High Effort)

Plan for these next.

Fill-Ins (Low Value, Low Effort)

Build when convenient.

Avoid (Low Value, High Effort)

Skip or delay indefinitely.

Case Study: Prioritizing a Feature Backlog

Starting Backlog

• Dark mode
• Slack integration
• Mobile app
• Custom fields
• Team permissions
• API access
• Bulk import
• Report export

Reddit Research Findings

Prioritized Roadmap

• Mobile app (17) - High value, needed urgently
• Bulk import (17) - Blocking new user adoption
• Team permissions (15) - Deal-breaker for teams
• Slack integration (13) - Medium priority
• Dark mode (12) - Easy win
• Report export (12) - Standard feature
• Custom fields (11) - Power user need
• API access (8) - Very niche

Avoiding Prioritization Traps

Trap 1: Recency Bias

The last thing you read feels most important.

Solution: Aggregate data over time, not just recent posts.

Trap 2: Confirmation Bias

You find what you want to find.

Solution: Actively search for evidence against your preferred features.

Trap 3: Vocal Minority

Loud users are not representative.

Solution: Check upvotes and comments for validation beyond the original poster.

Trap 4: Ignoring Non-Users

Current users might not represent future customers.

Solution: Research subreddits where non-users discuss alternatives.

Maintaining Prioritization

Monthly Review

• Scan for new feature requests
• Update scores based on new data
• Check if shipped features reduced related complaints

Quarterly Strategy

• Re-evaluate major priorities
• Look for emerging patterns
• Adjust based on market changes

Post-Launch

• Monitor Reddit for reactions to new features
• Track if the feature reduced related complaints
• Note any new requests triggered by the release

Conclusion

Feature prioritization should be evidence-based, not opinion-based. Reddit provides a free source of user feedback that reveals frequency, intensity, and context for every feature request.

Use this data to build what users actually need, not what you think they need.

Want to prioritize your roadmap with real feedback? Try Peekdit free — save feature request threads and analyze patterns with AI.