Build company-level pipeline revenue reports with forecast variance in HubSpot

HubSpot’s native reporting tools can’t create company-level pipeline revenue reports that include forecast variance calculations. The platform lacks the ability to combine historical forecast data with actual revenue outcomes at this granular level.

Here’s how to build comprehensive variance reporting that tracks company-level pipeline performance over time and provides insights into forecasting accuracy that HubSpot’s standard reports simply can’t deliver.

Create comprehensive variance reports using Coefficient

Coefficient solves this by enabling comprehensive variance reporting through live data imports and historical snapshots. You can combine HubSpot deal data with sophisticated calculations to track forecast performance by company across all pipelines.

How to make it work

Step 1. Import deal data from all pipelines with company associations.

Set up imports that pull deal data with company associations and revenue amounts from all your pipelines. Include fields like deal amount, close date, pipeline name, deal stage, and associated company. Configure filters to focus on your reporting timeframe.

Step 2. Build forecast calculations using stage probabilities.

Create formulas that calculate forecasted revenue using deal stage probabilities and close date projections. For example: =Deal_Amount * VLOOKUP(Deal_Stage, Stage_Probability_Table, 2, FALSE). Apply these calculations across all deals to generate company-level forecasts.

Step 3. Capture monthly forecast baselines with Snapshots.

Use the Snapshots feature to capture monthly forecast baselines by company and pipeline. Set up automated snapshots on the last day of each month to preserve point-in-time forecasts. This creates the historical data you need for variance analysis.

Step 4. Import actual closed-won revenue data.

Create a separate import for closed-won deals with the same company/pipeline dimensions. Filter for deals with “Closed Won” status and include actual close dates and revenue amounts. This provides the actual results to compare against your forecasts.

Step 5. Build variance formulas and summary dashboards.

Create formulas that compare forecasted vs actual revenue with percentage accuracy calculations. Build summary dashboards using pivot tables or SUMIFS formulas to show forecast performance by company across all pipelines. Include metrics like absolute variance, percentage accuracy, and trend analysis.

Step 6. Set up automated monthly updates.

Configure scheduled refreshes to automatically update your variance reports monthly. Add Slack and Email Alerts to notify stakeholders when reports are updated or when significant variance patterns emerge.

Get the pipeline variance insights you need

This creates a comprehensive forecast variance reporting system that tracks company-level pipeline performance over time with insights that HubSpot standard reports simply cannot provide. Start building your variance reporting system today.