Understanding Segment Activity

The Segment Activity widget provides insights into how different user segments engage with your feedback system. By analyzing feedback submission patterns, voting behavior, and user participation across segments, you can identify which customer groups are most engaged and which need attention.

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What Are Segments?

Segments are groups of users organized by characteristics such as:

• Company/Account
• User role or department
• Geographic location
• Product tier or plan
• Custom attributes

Segments help you understand feedback patterns at a group level rather than just individual users.

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The Segment Activity Widget

Widget Components

1. Segment Comparison (Top Section)

Highlights the two most important segments:

Most Engaged Badge (Green)

• The segment with the highest engagement score
• Shows segment name and percentage of total feedback
• Example: "Enterprise Customers (42%)"

Needs Attention Badge (Orange)

• The segment with the lowest engagement score
• Shows segment name only
• Example: "Free Tier Users"

2. Segment Cards List

Displays all segments with detailed metrics:

• Segment Name: Name of the user group
• Engagement Score: Calculated activity metric
• Item Count: Number of feedback items from this segment
• User Count: Number of users in the segment (shown in tooltip)
• Vote Count: Total votes cast by segment users (shown in tooltip)
• Top Issues: Most common category for this segment's feedback
• Progress Bar: Visual representation of percentage of total feedback

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Engagement Score Calculation

The Formula

Engagement Score = ((Item Count + Vote Count) / User Count) × 10

Breakdown:

1. Total Actions = Item Count + Vote Count

   • Item Count: Number of feedback items submitted by segment users
   • Vote Count: Number of votes cast by segment users

2. Actions Per User = Total Actions / User Count

   • Normalizes activity by segment size
   • Prevents large segments from dominating

3. Scaled Score = Actions Per User × 10

   • Multiplied by 10 for easier reading
   • Rounded to 1 decimal place

Example Calculation

Segment: Enterprise Customers

• Users in segment: 25
• Feedback items submitted: 45
• Votes cast: 80

Total Actions = 45 + 80 = 125
Actions Per User = 125 / 25 = 5.0
Engagement Score = 5.0 × 10 = 50.0

Interpretation: Each enterprise user averages 5 actions (submissions + votes), resulting in an engagement score of 50.0.

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Backend Data Collection

How Segment Data is Gathered

The system performs four parallel database queries:

Query 1: Feedback Items Count per Segment

SELECT COUNT(feedback_items.id) as count,
       segmentOptions.value as name
FROM idm_feedback_items
JOIN users ON feedback_items.user_id = users.id
JOIN segment_options ON users.id = segment_options.user_id
WHERE feedback_items.product_id = ?
  AND feedback_items.subscription_id = ?
  AND feedback_items.status = 'active'
GROUP BY segmentOptions.value

Query 2: Distinct Users Count per Segment

SELECT COUNT(users.id) as count,
       segmentOptions.value as name
FROM users
JOIN segment_options ON users.id = segment_options.user_id
WHERE segment_options.subscriptionId = ?
  AND segment_options.initiativeId = ?
  AND segment_options.status = 'active'
  AND users.status = 'active'
GROUP BY segmentOptions.value

Query 3: Votes Count per Segment

SELECT COUNT(votes.id) as count,
       segmentOptions.value as name
FROM idm_votes
JOIN idm_feedback_items ON votes.feedback_item_id = feedback_items.id
JOIN users ON votes.user_id = users.id
JOIN segment_options ON users.id = segment_options.user_id
WHERE votes.subscription_id = ?
  AND feedback_items.product_id = ?
  AND feedback_items.status = 'active'
GROUP BY segmentOptions.value

Query 4: Top Category per Segment

SELECT COUNT(feedback_items.id) as count,
       segmentOptions.value as segmentName,
       category.name as categoryName
FROM idm_feedback_items
JOIN users ON feedback_items.user_id = users.id
JOIN segment_options ON users.id = segment_options.user_id
JOIN categories ON feedback_items.category_id = categories.id
WHERE feedback_items.product_id = ?
  AND feedback_items.subscription_id = ?
  AND feedback_items.status = 'active'
GROUP BY segmentOptions.value, category.name
ORDER BY count DESC

Data Merging Process

1. Initialize with user counts (base denominator)
2. Add item counts for each segment
3. Add vote counts for each segment
4. Assign top category (most frequent) for each segment
5. Calculate engagement scores
6. Calculate percentages of total feedback
7. Sort by engagement score (descending)
8. Mark highest as "Most Engaged"
9. Mark lowest as "Needs Attention"

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Interpreting Segment Metrics

Engagement Score Ranges

Score	Interpretation	Action
50+	Highly Engaged	Maintain momentum, showcase their feedback
30-49	Well Engaged	Good participation, encourage continued activity
15-29	Moderately Engaged	Room for improvement, targeted outreach
5-14	Low Engagement	Needs attention, investigate barriers
<5	Very Low Engagement	Critical, immediate action required

Item Count

What it shows: Volume of feedback from the segment

High Count:

• Segment is actively using the feedback system
• May indicate pain points or high investment in product
• Opportunity to prioritize their needs

Low Count:

• Segment may be satisfied (no complaints)
• May not know about feedback system
• Could indicate disengagement

User Count

What it shows: Size of the segment

Importance:

• Normalizes engagement score
• Helps identify if low activity is due to small segment size
• Informs resource allocation decisions

Example:

• Segment A: 5 users, 10 items = 2 items per user
• Segment B: 50 users, 30 items = 0.6 items per user
• Segment A is more engaged despite lower total volume

Vote Count

What it shows: Community participation beyond submission

High Vote Count:

• Segment is engaged with others' feedback
• Indicates collaborative mindset
• Shows investment in product direction

Low Vote Count:

• Segment submits but doesn't engage with community
• May prefer direct communication
• Could indicate UI/UX issues with voting

Top Issues (Category)

What it shows: Most common feedback category for the segment

Use Cases:

• Identify segment-specific pain points
• Tailor product improvements to segment needs
• Understand different priorities across customer groups

Examples:

• Enterprise: "Integrations" (need business tool connectivity)
• Free Tier: "Pricing" (interested in upgrading)
• Mobile Users: "Performance" (app speed concerns)

Percentage Bar

What it shows: Segment's share of total feedback volume

Visual Indicators:

• Green (High): Most engaged segment
• Orange (Low): Least engaged segment
• Gray (Normal): Mid-range engagement

Interpretation:

• High percentage: Segment is vocal, may dominate roadmap
• Low percentage: Segment is quiet, may need targeted outreach

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Using Segment Activity Data

Prioritizing Product Development

Scenario: Multiple feature requests from different segments

Approach:

1. Check engagement scores - Highly engaged segments may be power users
2. Review top issues - Understand segment-specific needs
3. Consider user count - Balance individual engagement with segment size
4. Analyze vote patterns - See which features have broad support

Decision Framework:

Priority Score = (Engagement Score × 0.4) + 
                 (User Count × 0.3) + 
                 (Item Count × 0.2) + 
                 (Strategic Value × 0.1)

Customer Success Outreach

Most Engaged Segments:

• Action: Recognize and reward participation
• Communication: "Thank you for your active feedback!"
• Opportunity: Request testimonials, case studies
• Strategy: Maintain momentum with regular updates

Needs Attention Segments:

• Action: Investigate barriers to engagement
• Communication: "We'd love to hear from you!"
• Opportunity: Conduct surveys, schedule calls
• Strategy: Make feedback easier, provide incentives

Product Marketing Insights

Use segment data to:

• Identify champions: High-engagement segments for advocacy
• Understand pain points: Top issues by segment
• Tailor messaging: Address segment-specific concerns
• Measure satisfaction: Engagement as proxy for product fit

Resource Allocation

Questions to answer:

• Which segments need more support resources?
• Where should we focus product improvements?
• Which segments are at risk of churn?
• Where are our growth opportunities?

Example Analysis:

Segment: Free Tier Users
- Engagement Score: 8.5 (Low)
- Top Issue: "Pricing"
- Action: Create upgrade path content, offer trials

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Common Patterns and What They Mean

Pattern 1: High Engagement, Low User Count

Example:

• Segment: Beta Testers
• Users: 10
• Engagement Score: 75.0

Interpretation:

• Small but highly engaged group
• Likely power users or early adopters
• Valuable for product feedback

Action:

• Maintain close relationship
• Prioritize their feedback for product direction
• Consider expanding this segment

Pattern 2: Low Engagement, High User Count

Example:

• Segment: Free Tier
• Users: 500
• Engagement Score: 3.2

Interpretation:

• Large segment with minimal participation
• May not see value in feedback system
• Potential churn risk or satisfaction

Action:

• Investigate barriers (awareness, access, motivation)
• Targeted campaigns to increase engagement
• Consider if segment is right fit for product

Pattern 3: Balanced Engagement Across Segments

Example:

• All segments: 20-30 engagement score range

Interpretation:

• Healthy, diverse feedback ecosystem
• No single segment dominating
• Broad product-market fit

Action:

• Maintain current approach
• Continue balanced roadmap development
• Monitor for changes

Pattern 4: One Dominant Segment

Example:

• Enterprise: 85% of feedback, Score: 92.0
• All others: <5% each, Scores: <10

Interpretation:

• Product heavily used by one segment
• Other segments may be underserved
• Risk of narrow product focus

Action:

• Ensure roadmap serves all segments
• Increase engagement from other segments
• Consider segment-specific features

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Segment Activity Trends

Tracking Changes Over Time

Monitor these metrics weekly:

• Engagement score changes
• Shifts in most/least engaged segments
• New segments appearing
• Segments disappearing (users leaving)

Red Flags:

• Sudden drop in engagement score
• Previously engaged segment goes quiet
• Growing gap between most and least engaged

Green Flags:

• Increasing engagement across all segments
• New segments becoming active
• Balanced distribution of feedback

Seasonal Patterns

Consider:

• End of quarter: Enterprise segments may be busier
• Product launches: Spike in specific segment activity
• Holidays: General decrease in engagement
• Renewal periods: Increased feedback before renewals

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Advanced Analysis

Engagement Score Benchmarks

By Segment Type:

Segment Type	Expected Score	Notes
Enterprise Customers	40-60	High investment, active feedback
SMB Customers	25-40	Moderate engagement
Free/Trial Users	10-20	Lower but growing
Internal Users	50-80	Highest engagement
Partner Organizations	30-50	Varies by partnership

Correlation Analysis

Engagement vs. Retention:

• High engagement often correlates with lower churn
• Track if engaged segments renew at higher rates

Engagement vs. Revenue:

• Do high-engagement segments have higher LTV?
• Is engagement a leading indicator of expansion?

Engagement vs. Satisfaction:

• Compare with NPS or CSAT scores
• High engagement doesn't always mean satisfaction

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Troubleshooting

No Segment Data Showing

Symptoms: "No segment activity yet" message

Possible Causes:

1. No segments configured for this product
2. No users assigned to segments
3. No feedback submitted yet
4. Data loading error

Solutions:

1. Verify segments exist in user management
2. Check that users have segment assignments
3. Ensure feedback items exist
4. Refresh the page
5. Check browser console for errors

Unexpected Engagement Scores

Symptoms: Scores seem too high or too low

Verification:

1. Check user count (low count inflates scores)
2. Verify vote and item counts in tooltip
3. Recalculate manually using formula
4. Check for data anomalies (bulk imports, etc.)

Missing Top Issues

Symptoms: "Top Issues" shows "General" or blank

Causes:

• Feedback items lack category assignments
• No categorized feedback from this segment

Solutions:

• Assign categories to feedback items
• Ensure category system is set up
• Review uncategorized items

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Best Practices

Regular Monitoring

✅ Check weekly - Review segment activity trends
✅ Compare periods - Track month-over-month changes
✅ Set alerts - Notify when engagement drops significantly
✅ Document patterns - Note seasonal or event-driven changes

Actionable Insights

✅ Prioritize outreach - Focus on "Needs Attention" segments
✅ Celebrate engagement - Recognize highly engaged segments
✅ Balance roadmap - Ensure all segments are represented
✅ Investigate changes - Understand why scores shift

Data Quality

✅ Maintain segments - Keep segment definitions current
✅ Update assignments - Ensure users are in correct segments
✅ Clean data - Remove inactive users from counts
✅ Validate categories - Ensure consistent categorization

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Formulas Quick Reference

Engagement Score

Engagement Score = ((Item Count + Vote Count) / User Count) × 10
Rounded to 1 decimal place

Percentage of Total

Percentage = (Segment Item Count / Total Items Across All Segments) × 100
Rounded to nearest integer

Most Engaged Determination

Sort all segments by Engagement Score (descending)
First segment = Most Engaged
Last segment = Needs Attention

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Glossary

Segment: A group of users with shared characteristics
Engagement Score: Calculated metric of segment activity level
Item Count: Number of feedback items submitted by segment
User Count: Number of active users in the segment
Vote Count: Total votes cast by segment users
Top Issues: Most common feedback category for the segment
Actions Per User: Average activity level per segment member

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Segment Activity data transforms raw feedback numbers into actionable customer intelligence. Use it to understand which customer groups are most invested in your product, identify at-risk segments, and ensure your roadmap serves all your users effectively.