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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.”
Native Salesforce reporting struggles with complex adoption rate calculations across user roles due to cross-object reporting limitations and percentage calculation constraints. You can see who uses what, but calculating meaningful adoption rates requires analytics that Salesforce simply can’t deliver.
Here’s how to build comprehensive feature adoption tracking that shows exactly how different roles engage with Salesforce features over time.
Build multi-layered adoption analytics using Coefficient
CoefficientSalesforceexcels at the complex data integration and calculations needed for feature adoption tracking. By pulling data from multipleobjects simultaneously, you can create adoption insights that are impossible with native reporting.
How to make it work
Step 1. Import user and feature usage data.
Create separate Coefficient imports for User data (including UserRole), Report usage, Dashboard views, and Custom object interactions. This gives you all the raw data needed to calculate adoption rates across different user segments.
Step 2. Calculate adoption rates with advanced formulas.
Use VLOOKUP and pivot tables to match users with their feature usage across roles. Apply formulas like =(COUNTIF(Users_by_Role, “Sales Rep”) / COUNTIF(Feature_Users, “Sales Rep”)) * 100 to calculate percentage adoption rates that Salesforce reports cannot handle natively.
Step 3. Set up automated calculations for new data.
Use Formula Auto Fill Down to automatically calculate adoption percentages when new data arrives. This ensures your adoption rates stay current without manual recalculation every time you refresh your data.
Step 4. Create dynamic filtering for stakeholder views.
Set up dynamic filters that allow stakeholders to filter by specific roles, time periods, or feature sets without rebuilding reports. This provides role-specific adoption insights that adapt to different viewing needs.
Step 5. Build trending analysis over time.
Track adoption rate changes month-over-month to identify improving or declining feature usage by role. Create weighted adoption scores based on usage frequency to distinguish between occasional and regular feature users.
Get the adoption insights you need
start buildingRole-specific feature adoption rates reveal which teams embrace new functionality and which need additional support. Stop struggling with Salesforce’s reporting limitations andcomprehensive adoption analytics today.
