You've connected your sales data to Enterpret - now it's time to understand why you're winning and losing deals. This guide will show you how to build comprehensive win/loss analysis dashboards that reveal competitive dynamics, feature gaps, and opportunity patterns.
Before You Start: Understanding Your Data Structure
Every company tracks sales data differently. Before building your dashboard, find out where these key data points exist in your metadata:
Deal Information:
Win/loss status (e.g., Stage, Outcome, Status fields)
Deal values (e.g., ARR, Contract Value fields)
Deal types (e.g., New Business, Expansion)
Account Information:
Account identifiers
Segment/industry data
Account size indicators
Sales Conversation Data:
Source platform (e.g., Gong, Chorus)
Call/meeting timestamps
Participant information
Pro Tip: Review your metadata fields in the Integrations page to identify these key fields for your account.
Step-by-Step Guide
Setup Basic Volume Tracking
Create a Quantify to track closed-lost conversations:
Plot: Feedback Records
Filters:
Opportunity Stage = "Closed Lost" (or your equivalent field)
Source = CRM/Your sales conversation platform
Duration: Last 3 months
View: Trend chart
This lets you see if your lost deal volume is increasing or decreasing over time.
Always filter using your CRM fields (like Salesforce Opportunity Stage) to determine won/lost status, rather than relying on mentions in sales conversations.( Gong, Chrous)
This ensures you're analyzing deals that are officially closed, not just ones where winning or losing was discussed.
Compare Win vs Loss Patterns
Basic Win/Loss Comparison
Create a Quantify to compare feedback patterns between won and lost deals:
Plot: Reasons
Filters:
Source = Your sales conversation platform
AND Deal Status = "Closed Won" OR "Closed Lost"
Duration: Last 3 months
View: Bar chart
Then click "Compare" and choose "By Another Filter":
Filter A: Deal Status = "Closed Won" (using your CRM field name)
Filter B: Deal Status = "Closed Lost" (using your CRM field name)
This will show two bars for each Reason - one showing frequency in won deals, one showing frequency in lost deals.
What this helps us understand:
Which topics come up more frequently in won vs lost deals
Key differentiators that help close deals
Common objections in lost opportunities
Pro Tip: Use the "Compare" feature to create a clear visual distinction between won and lost deal patterns.
Analyze Competitive Dynamics
Competitor Mention Analysis
Create a Quantify to track competitor mentions in lost deals:
Plot: Keywords (filter to Competitor category)
Filters:
Deal Status = "Closed Lost"
Source = Your sales conversation platform
Duration: Last 3 months
View: Bar chart
Feature Comparison by Competitor
Create a Quantify to understand feature discussions when competitors are mentioned:
Plot: Reasons
Filters:
Deal Status = "Closed Lost"
AND Keyword is any of [Your competitor keywords]
Duration: Last 3 months
View: Bar chart
What this helps us understand:
Which competitors you're losing to most frequently
Feature gaps compared to specific competitors
Common competitive differentiation points
Track Deal Stage Patterns
Stage-Based Analysis
Create a Quantify to understand feedback patterns at different deal stages:
Plot: Deal Stage (your equivalent field)
Filters:
Deal Status = "Closed Lost"
Duration: Last 3 months
View: Bar chart
What this helps us understand:
When in the sales cycle deals typically fall through
Different objection patterns at each stage
Opportunities for earlier qualification
Pro Tip: Look for anomalies in stage patterns - unusual spikes in losses at certain stages might indicate process issues.
Monitor Feature Gaps
Feature Request Tracking
Create a Quantify to identify missing features impacting deals:
Plot: Reasons (filter to Improvement category)
Filters:
Deal Status = "Closed Lost"
Duration: Last 3 months
View: Bar chart
Compare: Against previous period
What this helps us understand:
Most requested missing features
Trending feature gaps
Priority areas for product development
Detect Emerging Patterns
Anomaly Detection
Set up trend monitoring with anomalies enabled:
Plot: Reasons
Filters:
Deal Status = "Closed Lost"
Duration: Last 3 months
View: Trend chart with anomalies
Enable anomaly detection
What this helps us understand:
Sudden changes in loss reasons
Emerging competitive threats
New feature gap patterns
Pro Tip: Set up regular dashboard subscriptions to stay on top of changing patterns in your win/loss analysis.
Common Questions
Q: How do I handle deals with multiple loss reasons?
A: Enterpret automatically tracks all mentioned reasons. Focus on patterns and trends rather than exact counts.
Q: What's the right time period to analyze?
A: Start with 3 months and adjust based on your sales cycle length and deal volume.
Q: How should I share these insights with stakeholders?
A: Use the dashboard sharing feature and set up regular email/Slack updates for key insights.
Need Help with setting this up?
Contact us for assistance with setup