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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 can’t natively access Google Ads ad group data or create the complex cross-object calculations needed to analyze ad group performance by deal stage progression.
Here’s how to build comprehensive ad group performance reports that show which ad groups produce deals that move fastest through your pipeline and close at the highest rates.
Build ad group performance reports using Coefficient
HubSpotCoefficienthas no native ad group data storage and can’t join Google Ads metrics with deal stages.provides the solution by connecting both data sources for comprehensive ad group performance reporting across your entire sales funnel.
You’ll get cost per stage calculations, stage conversion rates by ad group, and predictive metrics that help optimize both ad spend and sales processes.
How to make it work
Step 1. Import Google Ads ad group data.
Connect Google Ads via Coefficient and import the Ad Groups report with Ad Group Name, Campaign, Impressions, Clicks, Cost, and Conversions. Apply date filters matching your deal analysis period and schedule hourly refresh for real-time performance data.
Step 2. Import HubSpot deal data.
HubSpotImport Deals fromwith Deal Name, Amount, Current Stage, Stage History, Create Date, and Close Date. Include your custom property for “Original Ad Group” that’s captured via UTM parameters. Pull all deals from paid search sources.
Step 3. Create performance calculations.
Build formulas for Cost per Stage = SUMIF(Ad_Group, “Ad Group Name”, Cost) / COUNTIF(Deal_Stage, “Stage Name”). Calculate Stage Conversion Rate = Deals in Next Stage / Deals in Current Stage. Create Ad Group Revenue by Stage = SUMIFS(Deal_Amount, Ad_Group, “Name”, Stage, “Stage Name”).
Step 4. Build multi-dimensional reports.
Create an Ad Group Performance Matrix with rows for ad groups, columns for deal stages, and values showing count of deals, total revenue, and average deal size. Use conditional formatting to highlight high-performing combinations. Build funnel charts showing ad group performance through stages and calculate drop-off rates between stages by ad group.
Step 5. Add advanced analytics.
Create cohort analysis tracking deal progression by month of creation to compare ad group performance over time. Build predictive metrics calculating expected revenue by ad group based on current pipeline and project close rates using historical ad group performance.
Step 6. Set up automation and alerts.
Schedule daily report refresh at 6 AM and set up Slack alerts for ad groups with deals stuck in stages. Create email reports for your sales team showing their deals by ad group origin and configure alerts for ad groups with declining stage conversion rates.
Optimize ad spend and sales process together
Start buildingThis approach provides granular visibility into which ad groups produce deals that close fastest and identifies ad groups requiring sales process optimization.your ad group performance reports today.
