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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.”
Declining usage is the strongest predictor of churn, but NetSuite can’t track usage trends or trigger automated responses when engagement drops. You’re left manually checking reports and hoping you catch at-risk customers in time.
Here’s how to set up automated marketing workflows that activate when customer usage patterns show concerning drops.
Track usage trends and trigger campaigns using Coefficient
Coefficient excels at historical data analysis and trend identification that NetSuite’s standard reporting simply can’t achieve. You can analyze multiple time periods and identify declining usage patterns automatically.
How to make it work
Step 1. Import usage data with custom SuiteQL queries.
Use Coefficient’s SuiteQL Query feature to create custom queries pulling usage-related data from Transaction records, login logs, or custom usage tracking fields. Include complex joins and aggregations to get comprehensive usage metrics in one query.
Step 2. Set up historical trend analysis.
Import multiple time periods of usage data using Coefficient’s date filtering capabilities. Create separate imports for different date ranges to establish baseline metrics and compare current usage against historical patterns.
Step 3. Configure automated threshold monitoring.
Set up daily automated scheduling to refresh usage data. Use spreadsheet formulas to calculate percentage drops, moving averages, and trigger thresholds. For example: =IF((B2-C2)/C2<-0.3,"TRIGGER","OK") to flag 30% usage drops.
Step 4. Access custom usage fields.
Import NetSuite custom fields storing usage metrics through Coefficient’s comprehensive custom field support. This enables analysis of product-specific usage patterns that standard reports miss.
Step 5. Compare multiple time periods automatically.
Leverage Coefficient’s ability to import the same NetSuite data with different date filters into separate sheets. Create week-over-week or month-over-month usage comparisons using formulas like =VLOOKUP to match customers across time periods.
Step 6. Integrate with marketing automation.
Use the 100,000 row limit per SuiteQL query to accommodate extensive usage data analysis. Organize complex usage datasets with drag-and-drop column reordering, then connect to marketing automation platforms for immediate campaign triggers.
Catch declining engagement before customers churn
This approach gives you sophisticated usage monitoring that NetSuite can’t provide natively. You’ll identify at-risk customers weeks before they decide to leave. Start monitoring usage trends today.
