Account Analytics & Reporting

The Accounts feature in Feedback Manager provides powerful analytics capabilities that help you understand your B2B customers at a deeper level. This guide covers how to analyze account data, generate insights, and make data-driven decisions about your product and customer relationships.

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Understanding Account Metrics

Business Metrics

Track the financial and business health of your accounts:

Annual Recurring Revenue (ARR)

• Total yearly revenue from the account
• Key indicator of account value
• Use to prioritize high-value customers

Example Use Cases:

• Identify top revenue-generating accounts
• Correlate feedback volume with account value
• Prioritize feature requests from high-ARR accounts

Monthly Recurring Revenue (MRR)

• Monthly revenue from the account
• Useful for tracking growth trends
• Calculate from ARR: MRR = ARR / 12

Example Use Cases:

• Monitor month-over-month revenue changes
• Identify accounts with changing subscription levels
• Track expansion or contraction revenue

Plan Tier

• Subscription level (e.g., Starter, Professional, Enterprise)
• Indicates feature access and commitment level
• Helps segment accounts by value

Example Use Cases:

• Analyze feedback patterns by plan tier
• Identify upgrade opportunities
• Understand which features matter to each tier

Engagement Metrics

Measure how actively accounts participate in feedback:

User Count

• Total number of users associated with the account
• Indicates account size and potential reach
• Track growth over time

Insights:

• Growing user count = account expansion
• Declining user count = potential churn risk
• High user count = broad organizational buy-in

Active Users

• Users who have logged in or submitted feedback recently
• More meaningful than total user count
• Calculate activation rate: Active Users / Total Users

Insights:

• Low activation rate = onboarding issues
• High activation rate = strong engagement
• Track changes over time to spot trends

Feedback Volume

• Number of ideas, issues, or feedback items submitted
• Indicates engagement level
• Compare across accounts to identify power users

Insights:

• High volume = engaged, invested customer
• Sudden drop = potential dissatisfaction
• Zero feedback = may need outreach

Voting Activity

• Votes given and received by account users
• Shows community participation
• Indicates influence and engagement

Insights:

• High votes received = influential feedback
• High votes given = active community member
• Imbalance may indicate one-way communication

Customer Lifecycle Metrics

Track the customer journey:

Customer Since

• Date the account became a customer
• Calculate customer lifetime value (CLV)
• Identify long-term vs. new customers

Insights:

• Long-term customers = stable revenue
• New customers = onboarding focus
• Cohort analysis by signup date

Renewal Date

• Next contract renewal date
• Critical for churn prevention
• Enables proactive customer success

Insights:

• Upcoming renewals = outreach opportunity
• Past renewals = potential churn
• 90-day window = critical engagement period

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Analyzing Account Data

Segmentation Strategies

By Revenue

High-Value Accounts (Top 20%)

• ARR > $100,000
• Focus: White-glove service, priority support
• Strategy: Ensure their feedback is prioritized

Mid-Market Accounts (Middle 60%)

• ARR 10,000 - 100,000
• Focus: Scalable engagement, self-service
• Strategy: Group feedback for common themes

Small Accounts (Bottom 20%)

• ARR < $10,000
• Focus: Efficiency, automation
• Strategy: Look for upgrade opportunities

By Plan Tier

Enterprise Tier

• Highest commitment level
• Advanced features and customization
• Feedback often drives roadmap

Professional Tier

• Mid-level commitment
• Balance of features and price
• Feedback indicates upgrade potential

Starter Tier

• Entry-level customers
• Testing product fit
• Feedback shows expansion needs

By Engagement Level

Highly Engaged

• Multiple active users
• Regular feedback submission
• High voting activity

Moderately Engaged

• Some active users
• Occasional feedback
• Sporadic voting

Low/No Engagement

• Few or no active users
• Minimal feedback
• No voting activity

[!IMPORTANT]
Low engagement doesn't always mean dissatisfaction. Some customers are happy but quiet. However, it's worth investigating to ensure they're getting value.

By Industry

Technology

• Fast-moving, feature-focused
• High engagement typical
• Quick adoption of new features

Healthcare

• Compliance-focused
• Security and privacy priorities
• Slower adoption, thorough feedback

Manufacturing

• Process-oriented
• Integration needs
• Practical, implementation-focused feedback

Financial Services

• Risk-averse
• Regulatory requirements
• Detailed, specific feedback

Comparative Analysis

Account Size vs. Engagement

Question: Do larger accounts engage more?

Analysis:

1. Plot user count vs. feedback volume
2. Calculate engagement rate per user
3. Identify outliers

Insights:

• Large accounts with low engagement = opportunity
• Small accounts with high engagement = expansion potential
• Benchmark engagement by account size

Revenue vs. Feedback Quality

Question: Do high-paying customers provide more valuable feedback?

Analysis:

1. Tag feedback by account ARR
2. Track implementation rate by revenue tier
3. Measure feedback impact

Insights:

• High-ARR feedback alignment with roadmap
• Low-ARR feedback for future opportunities
• Balance stakeholder needs

Plan Tier vs. Feature Requests

Question: What features does each tier request?

Analysis:

1. Categorize feedback by feature area
2. Cross-reference with plan tier
3. Identify tier-specific needs

Insights:

• Starter tier = ease of use, basics
• Professional tier = automation, efficiency
• Enterprise tier = customization, integration

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Reporting Strategies

Executive Dashboard

Key Metrics to Display:

• Total Accounts
• Total ARR/MRR
• Average Account Size (users)
• Overall Engagement Rate
• Top 10 Accounts by Revenue
• Accounts at Risk (renewal < 30 days)

Frequency: Weekly or Monthly

Audience: Leadership, executives

Customer Success Dashboard

Key Metrics to Display:

• Accounts by Engagement Level
• Upcoming Renewals (30/60/90 days)
• Accounts with Declining Engagement
• New Accounts (last 30 days)
• Feedback Response Rate
• User Activation Rate by Account

Frequency: Daily or Weekly

Audience: Customer Success Managers

Product Dashboard

Key Metrics to Display:

• Feedback Volume by Account
• Top Feature Requests by Revenue Impact
• Account Distribution by Plan Tier
• Industry-Specific Feedback Trends
• Feedback Implementation Rate
• User Satisfaction by Account

Frequency: Weekly or Bi-weekly

Audience: Product Managers, Product Team

Sales Dashboard

Key Metrics to Display:

• Account Growth Rate
• Expansion Opportunities (users added)
• Accounts Requesting Advanced Features
• Engagement as Renewal Predictor
• Accounts with High Influence
• Referral Potential Accounts

Frequency: Weekly

Audience: Sales Team, Account Executives

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Identifying Insights

Health Score Calculation

Create a composite health score for each account:

Formula:

Health Score = (Engagement Score × 0.4) + (Revenue Score × 0.3) + (Lifecycle Score × 0.3)

Engagement Score (0-100):

• Active users / Total users (40%)
• Feedback volume (30%)
• Voting activity (30%)

Revenue Score (0-100):

• ARR percentile (50%)
• Plan tier (30%)
• Revenue trend (20%)

Lifecycle Score (0-100):

• Days until renewal (40%)
• Customer tenure (30%)
• Support ticket volume (30%)

Interpretation:

• 80-100: Healthy, thriving account
• 60-79: Stable, monitor for changes
• 40-59: At risk, needs attention
• 0-39: Critical, immediate action required

Churn Risk Indicators

Red Flags:

• ⚠️ Declining active user count
• ⚠️ No feedback in last 60 days
• ⚠️ Decreased voting activity
• ⚠️ Renewal date < 30 days
• ⚠️ Increase in negative feedback
• ⚠️ Support ticket volume spike

Action Items:

1. Schedule check-in call
2. Review recent feedback
3. Offer training or resources
4. Escalate to customer success
5. Consider special offers or incentives

Expansion Opportunities

Green Flags:

• ✅ Growing user count
• ✅ High engagement rate
• ✅ Requests for advanced features
• ✅ Multiple departments using product
• ✅ Positive feedback trends
• ✅ Referrals or testimonials

Action Items:

1. Present upgrade options
2. Showcase advanced features
3. Offer pilot programs
4. Schedule executive briefing
5. Provide ROI analysis

Product Insights

Patterns to Look For:

Feature Adoption by Tier:

• Which features do Enterprise customers use most?
• What features drive upgrades from Starter to Professional?
• Are there underutilized features in certain tiers?

Industry-Specific Needs:

• Do healthcare customers request different features than tech?
• Are there compliance needs specific to certain industries?
• Can you create industry-specific packages?

Account Size Patterns:

• Do larger accounts need different workflows?
• Are there scalability issues for big accounts?
• Can you identify optimal account size?

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Advanced Analytics

Cohort Analysis

Group accounts by:

• Signup month/quarter
• Initial plan tier
• Industry
• Company size

Track over time:

• Retention rate
• Expansion rate
• Engagement trends
• Feature adoption

Example:

"Accounts that signed up in Q1 2024 have a 25% higher engagement rate than Q4 2023 cohort, suggesting improved onboarding."

Correlation Analysis

Investigate relationships:

• ARR vs. Feedback Volume
• User Count vs. Engagement Rate
• Plan Tier vs. Churn Rate
• Industry vs. Feature Requests

Example Finding:

"Accounts with >10 active users have 3x lower churn rate, suggesting that broad organizational adoption is a retention driver."

Predictive Analytics

Build models to predict:

• Churn probability
• Expansion likelihood
• Optimal renewal timing
• Feature request impact

Data Inputs:

• Historical engagement data
• Revenue trends
• Feedback patterns
• Support interactions

[!TIP]
Start simple with basic correlations before building complex predictive models. Often, simple insights drive the most action.

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Exporting and Sharing Data

Export Options

Account List Export:

• All accounts with key metrics
• Filter by segment or criteria
• CSV format for analysis in Excel/Sheets

User List Export:

• All users by account
• Include engagement metrics
• Useful for CRM sync

Feedback Export:

• All feedback by account
• Include votes and status
• Analyze in external tools

Integration with Other Tools

CRM Integration:

• Sync account data to Salesforce, HubSpot
• Update health scores automatically
• Trigger workflows based on engagement

BI Tools:

• Connect to Tableau, Power BI, Looker
• Build custom dashboards
• Combine with other data sources

Data Warehouse:

• Export to Snowflake, BigQuery, Redshift
• Combine with product usage data
• Run complex analytics queries

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Actionable Insights Framework

1. Identify

What to look for:

• Trends in the data
• Outliers and anomalies
• Patterns across segments

Tools:

• Dashboards and reports
• Automated alerts
• Regular data reviews

2. Analyze

Dig deeper:

• Why is this happening?
• What's the root cause?
• Is this a one-time event or a trend?

Methods:

• Drill down into account details
• Compare to historical data
• Interview customers

3. Act

Take action:

• Customer outreach
• Product changes
• Process improvements

Examples:

• Reach out to at-risk accounts
• Prioritize high-impact features
• Improve onboarding for low-engagement cohorts

4. Measure

Track impact:

• Did engagement improve?
• Did churn decrease?
• Did revenue increase?

Iterate:

• Refine your approach
• Scale what works
• Discontinue what doesn't

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Best Practices

📊 Regular Reviews

Weekly:

• Check health scores
• Review at-risk accounts
• Monitor engagement trends

Monthly:

• Deep dive into segments
• Analyze cohort performance
• Review product feedback themes

Quarterly:

• Strategic planning
• Roadmap alignment
• Executive reporting

🎯 Focus on Action

Don't just report, act:

• Every insight should drive a decision
• Assign owners to action items
• Track follow-through

Prioritize:

• High-impact, low-effort wins first
• Balance quick wins with strategic initiatives
• Focus on accounts with highest potential

🔄 Continuous Improvement

Iterate on metrics:

• Refine health score formula
• Add new data sources
• Improve segmentation

Learn from outcomes:

• Track which actions work
• Document best practices
• Share learnings across teams

🤝 Cross-Functional Collaboration

Share insights with:

• Customer Success: Account health, churn risk
• Sales: Expansion opportunities, referrals
• Product: Feature requests, usage patterns
• Marketing: Case studies, testimonials

Regular sync meetings:

• Review key metrics together
• Align on priorities
• Coordinate outreach

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Common Analysis Scenarios

Scenario 1: Identifying Upsell Opportunities

Goal: Find accounts ready to upgrade

Analysis:

1. Filter accounts by current plan tier (Starter or Professional)
2. Look for high engagement (>70% active users)
3. Check for advanced feature requests
4. Review user growth trends

Action:

• Sales outreach with upgrade offer
• Product demo of advanced features
• ROI analysis presentation

Scenario 2: Preventing Churn

Goal: Identify and save at-risk accounts

Analysis:

1. Filter accounts with renewal < 60 days
2. Check engagement trends (declining?)
3. Review recent feedback (negative sentiment?)
4. Analyze support ticket history

Action:

• Customer success check-in call
• Address specific pain points
• Offer training or resources
• Executive escalation if needed

Scenario 3: Product Roadmap Prioritization

Goal: Decide which features to build next

Analysis:

1. Categorize all feature requests
2. Calculate total ARR requesting each feature
3. Count number of accounts requesting
4. Assess strategic importance

Action:

• Prioritize high-ARR, high-count requests
• Consider strategic features even if lower demand
• Communicate roadmap to requesting accounts

Scenario 4: Understanding Low Engagement

Goal: Improve activation and engagement

Analysis:

1. Identify accounts with <30% active users
2. Segment by plan tier, industry, size
3. Look for common patterns
4. Compare to high-engagement accounts

Action:

• Improve onboarding for identified segments
• Targeted email campaigns
• In-app prompts and tutorials
• Customer success outreach

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Metrics Glossary

Metric	Definition	Calculation	Use Case
ARR	Annual Recurring Revenue	Total yearly subscription value	Account value, prioritization
MRR	Monthly Recurring Revenue	ARR / 12	Monthly tracking, trends
User Count	Total users in account	Count of associated users	Account size
Active Users	Users active in last 30 days	Users with recent activity	Engagement level
Activation Rate	Percentage of active users	Active Users / Total Users × 100	Onboarding success
Engagement Score	Composite engagement metric	Weighted formula	Overall health
Health Score	Overall account health	Composite of multiple factors	Risk assessment
Churn Risk	Probability of cancellation	Predictive model	Retention focus
Expansion Potential	Likelihood of upgrade	Engagement + feature requests	Upsell targeting
Feedback Volume	Number of submissions	Count of feedback items	Engagement indicator
Votes Given	Votes cast by account users	Sum of all votes given	Community participation
Votes Received	Votes on account feedback	Sum of votes on their feedback	Influence measure

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Next Steps

• Getting Started with Accounts: Learn the basics of account management
• Managing Account Users: Detailed guide for user management
• CSV Import Guide: Bulk import accounts and users

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Need Help?

For questions about analytics and reporting, please contact your system administrator or data team. They can help you:

• Set up custom dashboards
• Configure automated reports
• Integrate with your BI tools
• Build predictive models