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“Supermetrics is a Bitter Experience! We can pull data from nearly any tool, schedule updates, manipulate data in Sheets, and push data back into our systems.”
Most sales engagement platforms provide basic usage reports, but they lack sophisticated adoption scoring and proactive alerting that identifies platform abandonment before it impacts performance.
Here’s how to build predictive analysis that identifies adoption issues early and enables timely intervention and training support.
Set up automated inactive user detection using Coefficient
Coefficient imports login frequency, feature usage, and engagement metrics to establish baseline activity levels. This creates proactive monitoring that identifies adoption issues before they become performance problems.
How to make it work
Step 1. Import comprehensive activity and adoption data.
Pull login frequency, feature usage, and engagement metrics from your sales engagement platform. Connect with Salesforce user data to map activity to team assignments and performance metrics.
Step 2. Create activity threshold monitoring formulas.
Build conditional logic that flags users below activity thresholds using multiple criteria. Use formulas like =IF(AND(Login_Days<3,Emails_Sent<10,Cadences_Used<1),"Inactive","Active") to identify users needing attention.
Step 3. Develop comprehensive adoption scoring.
Create adoption scores that weight different platform features by importance. Build formulas that combine login frequency, feature usage, and engagement metrics into single adoption scores for easy comparison.
Step 4. Set up progressive alert systems.
Configure Slack or email notifications that escalate based on inactivity duration – 7 days warning, 14 days urgent. Use Coefficient’s alert functionality to notify managers when team members need intervention.
Step 5. Track historical adoption trends.
Use Coefficient’s Append New Data feature to maintain user activity trends and identify declining engagement patterns. This reveals users at risk of platform abandonment before it happens.
Step 6. Build feature usage mapping and benchmarking.
Track which platform features each user actively engages with versus available capabilities. Compare users against team averages to identify those needing additional training or coaching support.
Prevent adoption issues before they impact performance
Predictive adoption analysis identifies users needing support before platform abandonment impacts their sales results. Start monitoring user adoption patterns to ensure your entire team gets value from your Salesforce sales engagement investment.
