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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.”
HubSpot’s native reporting cannot effectively show monthly new customers at the company level without lifecycle stage history. The platform lacks the ability to group deal data by company and determine first customer conversion dates within specific time periods.
Here’s how to build accurate monthly new customer analysis using advanced data processing that delivers the insights native HubSpot reporting simply cannot provide.
Build comprehensive monthly customer reports using deal data analysis
Coefficient provides the advanced reporting capabilities needed for accurate monthly new customer analysis. You can reconstruct monthly trends from existing deal data that HubSpot reporting cannot access properly while supporting flexible time periods and cross-object analysis.
How to make it work
Step 1. Import comprehensive company and deal data.
Use Coefficient to pull HubSpot companies with all associated deals, including deal close dates and amounts. Filter imports to relevant date ranges and deal types to focus on conversion-related data.
Step 2. Calculate customer conversion dates.
Create formulas to identify each company’s first “Closed Won” deal date using functions like =MIN(IF(company_column=company_name,IF(stage_column=”Closed Won”,date_column))). This establishes when companies became customers.
Step 3. Create monthly segmentation.
Use spreadsheet date functions to group customer conversions by month/year. Apply formulas like =TEXT(conversion_date,”YYYY-MM”) to create monthly cohorts that HubSpot cannot generate natively.
Step 4. Build advanced metrics and visualizations.
Calculate month-over-month growth rates, seasonal trends, and customer acquisition velocity. Create pivot tables showing monthly new customer counts, revenue from new customers by month, conversion source analysis, and year-over-year comparisons.
Step 5. Set up automated dashboard updates.
Schedule regular data refreshes to maintain current reporting without manual intervention. Use COUNTIFS and SUMIFS functions for monthly aggregation that updates automatically with fresh data.
Step 6. Create monitoring alerts.
Set up alerts for significant month-over-month changes in new customer acquisition to stay on top of trends and potential issues.
Get the monthly customer insights you need
This approach delivers the monthly customer reporting that was previously available through deprecated lifecycle properties but with greater accuracy and flexibility than native alternatives. Start building your comprehensive monthly customer reports today.
