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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 sales engagement reporting provides aggregate cadence performance, but it doesn’t show you the step-by-step analysis needed to optimize individual sequences for better response rates.
Here’s how to build detailed sequence step tracking that reveals exactly where prospects engage and where they drop off.
Import granular sequence data for step-by-step analysis using Coefficient
Coefficient imports detailed sequence data including step number, action type, engagement rates, response rates, and time delays. This gives you the granular data needed for sequence optimization that most platforms don’t provide natively.
How to make it work
Step 1. Import step-level engagement data.
Pull detailed sequence data including step number, action type, engagement rates, response rates, and time delays from your sales engagement platform. Connect with Salesforce to correlate step performance with opportunity creation.
Step 2. Calculate engagement rates for each step.
Create automated formulas that calculate open rates, click rates, and response rates for each step within every cadence. Use formulas like =COUNTIFS(Step_Number,1,Action,”Opened”)/COUNTIFS(Step_Number,1) to measure step-specific performance.
Step 3. Build drop-off analysis between steps.
Calculate progression rates between steps to identify where prospects typically disengage. Create formulas that show the percentage of prospects who move from step 1 to step 2, step 2 to step 3, and so on.
Step 4. Track performance changes over time.
Use Coefficient’s Append New Data feature to maintain historical step performance data. This reveals when engagement fatigue sets in and helps identify optimal sequence length.
Step 5. Create comparative analysis across cadences.
Build side-by-side step performance comparisons across different cadences and industries. Use conditional formatting to highlight high-performing steps and engagement rate anomalies.
Step 6. Correlate step timing with engagement rates.
Analyze how step timing affects engagement rates to optimize sequence pacing. Connect timing data with Salesforce prospect data to understand timing preferences by industry or role.
Optimize sequences with data-driven insights
Detailed sequence step analysis reveals exactly which steps drive engagement and which cause prospect drop-off, enabling data-driven cadence refinement. Start analyzing your sequence performance to significantly improve response rates and pipeline generation.
