Category: HubSpot

Creating rolling forecast reports from HubSpot pipeline data in Google Sheets

Rolling forecasts provide better visibility than static monthly views, but HubSpot lacks native rolling forecast capabilities. You need dynamic time windows that adjust automatically and historical data to build predictive models.

Here’s how to build sophisticated rolling forecasts that update daily with your latest pipeline changes.

Build dynamic rolling forecasts using Coefficient

Coefficient enables sophisticated rolling forecasts by combining live HubSpot pipeline data with Google Sheets’ calculation power, creating forecasts that adjust automatically as time progresses.

How to make it work

Step 1. Set up live pipeline data import.

Connect HubSpot to Google Sheets via Coefficient and import deals with all active pipeline stages, expected close dates, deal amounts, probabilities, and historical win rates by stage. This creates your foundation for rolling calculations.

Step 2. Create dynamic rolling time windows.

Use Google Sheets formulas to automatically categorize deals into rolling periods: Next 30 days with, 31-60 days with, and 61-90 days for longer-term visibility.

Step 3. Implement historical snapshots for trend analysis.

Configure Coefficient Snapshots to capture pipeline state daily for trend analysis, weekly for forecast accuracy measurement, and monthly for historical comparisons. This builds the historical dataset needed for predictive modeling.

Step 4. Calculate rolling averages from historical data.

Analyze snapshot data to determine 13-week rolling average of new pipeline created, 4-week rolling close rates by stage, and 12-week rolling average deal velocity. These metrics inform your predictive calculations.

Step 5. Build predictive rolling models.

Combine current pipeline with historical trends using formulas like:to predict future performance based on rolling patterns.

Step 6. Automate updates and visualizations.

Schedule imports to refresh daily for real-time rolling views, before weekly forecast meetings, and with alerts for significant pipeline changes. Create charts showing pipeline coverage over rolling 90-day periods and forecast accuracy trending over time.

Get dynamic forecasting that adapts automatically

Rolling forecasts provide insights impossible with HubSpot’s static reporting, adjusting daily as your pipeline evolves and incorporating historical patterns for better predictions. Your forecasts become more accurate and actionable. Start building your rolling forecasts today.

Creating weighted pipeline forecasts from HubSpot data in spreadsheets

Weighted pipeline forecasts provide more accurate revenue predictions than raw pipeline values, but HubSpot’s native tools offer limited weighting options. You need sophisticated multi-factor models that account for deal age, engagement, and historical patterns.

Here’s how to build advanced weighted forecasting that goes far beyond simple stage probabilities.

Build sophisticated weighted forecasting using Coefficient

Coefficient enables sophisticated weighted pipeline forecasting by combining live HubSpot pipeline data with advanced spreadsheet calculations , creating forecasting precision impossible in HubSpot alone.

How to make it work

Step 1. Import complete pipeline data for multi-factor weighting.

Use Coefficient to pull all active deals with current stage and probability, deal amount and expected close date, deal age and velocity metrics, plus custom fields like competitor presence or budget confirmation status.

Step 2. Create multi-factor weighting models.

Go beyond simple stage probability with complex formulas:. This accounts for multiple variables that impact close likelihood.

Step 3. Build dynamic probability matrices.

Create stage-based probabilities: Appointment Scheduled (10%), Qualified to Buy (20%), Presentation Scheduled (35%), Decision Maker Bought-In (50%), Contract Sent (75%), Closed Won (100%). Apply these as base probabilities for further weighting.

Step 4. Implement dynamic weighting adjustments.

Add deal age factors that reduce probability by 5% for each week past average stage duration, engagement weighting that increases probability based on recent activity levels, seasonal adjustments using historical close rate variations, and size-based weights for enterprise vs. SMB deals.

Step 5. Create segment-specific calculations.

Build separate weighted forecasts for new business vs. renewals (different close rates), product lines (varying sales cycles), geographic regions (market differences), and lead sources (quality variations).

Step 6. Enable historical calibration and scenario planning.

Use Coefficient Snapshots to track actual close rates vs. weighted predictions, adjust weights based on historical accuracy, and identify which factors best predict closure. Calculate Conservative (Weight * 0.8), Expected (standard weighting), and Optimistic (Weight * 1.2) scenarios.

Get forecasting precision that continuously improves

Sophisticated weighted forecasting provides accuracy impossible with HubSpot’s basic tools, with weights that continuously calibrate based on your unique sales patterns and real-time pipeline changes. Your forecasts become more precise over time. Start building your weighted forecasts today.

Dashboard configuration for comparing marketing campaign performance across DDH, CMSSP, O142 units

HubSpot’s native dashboards struggle with complex cross-business unit comparisons, especially when each unit (DDH, CMSSP, O142) may have different KPIs, campaign types, and performance benchmarks. Creating normalized comparisons requires extensive manual work and lacks real-time updates.

Here’s how to build sophisticated cross-unit comparison dashboards with standardized metrics and automated insights.

Build cross-unit comparison dashboards using Coefficient

The key is creating standardized performance frameworks with dynamic filtering and comparative analysis. Coefficient enables sophisticated cross-unit comparison dashboards through flexible data modeling that HubSpot cannot handle natively.

How to make it work

Step 1. Define standardized performance framework.

Establish common KPIs across all units: Campaign reach (impressions/contacts touched), Engagement rate (clicks, downloads, registrations), Conversion metrics (MQLs, SQLs, Opportunities), Revenue impact (pipeline generated, closed-won), and Efficiency ratios (CPL, CAC, ROI). Import data from HubSpot using consistent field mapping.

Step 2. Create business unit data architecture.

Set up separate filtered imports for DDH, CMSSP, and O142 units. Use consistent field mapping across all imports to ensure comparability. Add calculated “Performance Index” for normalized comparison using this formula: Performance Index = (Actual KPI / Target KPI) × Weight Factor.

Step 3. Build comparative analysis features.

Create side-by-side comparisons showing DDH vs CMSSP vs O142 performance. Build indexed performance views showing % above/below average. Create trend analysis tracking unit performance over time. Calculate market share showing relative contribution to total marketing impact.

Step 4. Implement dynamic filtering and segmentation.

Add filters by campaign type, date range, or specific KPIs for flexible analysis. Create segments by campaign size, budget, or target audience. Build custom comparison groups for specialized analysis needs with data from HubSpot .

Step 5. Design visual dashboard layout.

Structure with Executive Summary showing all units at the top, followed by three columns for DDH, CMSSP, and O142 performance metrics, and comparative analysis charts at the bottom. Use consistent color coding and formatting across all units for easy comparison.

Step 6. Configure automation and insights.

Set up 4x daily refreshes for current performance data. Create automated weekly performance rankings by unit. Build anomaly detection for unusual performance patterns. Generate automated commentary on significant changes and predictive modeling for quarterly forecasts.

Master cross-unit performance analysis

Comparing marketing campaign performance across business units reveals optimization opportunities and best practices that individual unit reports miss. This standardized approach enables fair comparisons while maintaining unit-specific insights. Start building your cross-unit dashboard today.

Dashboard setup for tracking content performance to form fill attribution in HubSpot campaigns

HubSpot’s native content attribution reporting provides basic metrics but struggles with granular form fill attribution. The platform has difficulty connecting individual content assets to specific form submissions, especially when tracking multi-touch content journeys within campaigns.

Here’s how to build sophisticated content-to-form attribution tracking that reveals which content pieces actually drive conversions.

Build comprehensive content attribution dashboards using Coefficient

The key is connecting content performance data with form submission data and campaign associations. Coefficient enables multi-object data integration that HubSpot can’t handle natively, creating clear attribution paths from content consumption to form fills.

How to make it work

Step 1. Set up multi-object data integration.

Import form submission data including Contact ID, Form name, Submission timestamp, and Page URL. Pull content performance metrics like page views, unique visitors, average time on page, and content ID. Import campaign associations to link form fills back to specific campaigns.

Step 2. Create custom attribution logic.

Use the hubspot_search formula to find all content interactions before form submission. Create time-decay attribution models using submission timestamps to weight recent interactions more heavily. Build first-touch and last-touch attribution views with VLOOKUP formulas.

Step 3. Build content performance scoring.

Calculate content engagement scores using this formula: (Page views × Time on page) / Bounce rate. Track form fill conversion rates by content piece. Identify high-performing content combinations that lead to conversions within your HubSpot campaigns.

Step 4. Configure automated attribution reporting.

Schedule daily imports of new form submissions and content metrics. Use Append New Data feature to build historical attribution database. Set up alerts for content pieces driving above-average form fills or conversion rates.

Step 5. Create campaign-level roll-up analysis.

Aggregate content performance by campaign using SUMIF formulas. Create content attribution heat maps showing which assets drive most conversions. Track content ROI using this calculation: Form fills generated × Average deal value / Content creation cost.

Step 6. Build a multi-sheet dashboard structure.

Organize with Sheet 1 for raw form submission data with content interaction history, Sheet 2 for content performance metrics with engagement scoring, Sheet 3 for attribution calculation layer with custom models, Sheet 4 for campaign summary dashboard with top-performing content, and Sheet 5 for historical trends using snapshot data.

Unlock true content attribution insights

Understanding which content pieces actually drive form fills transforms your content strategy and campaign optimization. This attribution system reveals the content journey that HubSpot can’t track natively. Start building your content attribution dashboard today.

Export activities assigned to multiple users across different teams without admin access

While HubSpot’s permission structure controls which activities you can access, the native export tools make it cumbersome to pull activity data from multiple users across different teams, even when you have the necessary permissions.

Here’s how to streamline multi-user activity exports once you have appropriate access to the data.

Streamline multi-user activity exports using Coefficient

Coefficient optimizes the multi-user activity export process through advanced filtering capabilities. While you still need proper HubSpot permissions to view activities assigned to other users, Coefficient makes the actual export process much more efficient.

How to make it work

Step 1. Verify your HubSpot permissions.

Ensure you have read access to activities assigned to the target users. You’ll need visibility to activities across teams, which may require elevated permissions for cross-team data access in HubSpot’s settings.

Step 2. Set up multi-user filtering.

Create an Activities import and use the “Assigned To” field with the IN operator: “Assigned To IN user1,user2,user3”. Replace the user values with actual HubSpot user IDs or email addresses to target specific team members.

Step 3. Configure dynamic user lists.

Reference a spreadsheet cell range for your user list: “Assigned To IN A1:A10” where cells A1 through A10 contain the user IDs. This makes it easy to update your target users without rebuilding the entire import.

Step 4. Add team-based filtering.

Combine user filters with other criteria like date ranges or activity types. For example: “Assigned To IN user1,user2,user3” AND “Activity Date >= 2024-01-01” AND “Activity Type = calls” for focused team activity analysis.

Step 5. Schedule automated multi-user exports.

Set up regular refreshes to maintain current multi-user activity data without manual intervention. This eliminates the need to repeatedly run filtered exports for different team combinations.

Optimize your cross-team activity reporting

Once you have the necessary HubSpot permissions, this approach streamlines multi-user activity exports and automates regular cross-team reporting workflows. Start building your multi-user activity reports today.

Export activities with all related records (contacts, deals, tickets) in single dataset

HubSpot’s native exports struggle with complex multi-object relationships, typically requiring separate exports for activities, contacts, deals, and tickets that you then have to manually join together.

Here’s how to create a unified dataset that includes all related CRM records in a single export.

Create unified activity datasets using Coefficient

Coefficient’s advanced association handling makes this a streamlined single-step process. Instead of managing multiple exports and complex lookups, you get comprehensive activity data with full relationship context in one import from HubSpot .

How to make it work

Step 1. Set up Activities import with comprehensive field selection.

Create an Activities import in HubSpot and select your desired activity fields including both standard properties (date, type, subject) and any custom activity fields you’ve configured.

Step 2. Add associated contact fields using bracket notation.

Include contact information by selecting fields like “First Name (Associated Contact),” “Email (Associated Contact),” and “Lifecycle Stage (Associated Contact)” to pull relevant contact data for each activity.

Step 3. Include deal associations.

Add deal-related fields such as “Deal Name (Associated Deal),” “Deal Stage (Associated Deal),” and “Deal Amount (Associated Deal)” to capture the deal context for each activity.

Step 4. Add ticket associations.

Include ticket information with fields like “Ticket Subject (Associated Ticket),” “Ticket Status (Associated Ticket),” and “Ticket Priority (Associated Ticket)” for complete support context.

Step 5. Choose your association display format.

Select how you want multiple associations displayed. “Row Expanded” creates separate rows for each association, “Comma Separated” lists multiple values in single cells, and “Primary Association” shows the main related record.

Step 6. Apply filters and schedule updates.

Add any necessary filters for date ranges, activity types, or association criteria. Set up automated refreshes to keep your unified dataset current with new activities and updated relationship data.

Get complete activity context in one report

This unified approach eliminates complex data matching and provides immediate access to comprehensive activity insights with full CRM relationship context in a single, analyzable dataset. Build your unified activity report today.

Export activities with custom fields and associated company data in one report

HubSpot’s native reporting forces you to export activities, custom fields, and company data separately, then manually join them together. This creates data fragmentation and wastes time on repetitive data matching tasks.

Here’s how to pull all this information into a single, unified report that saves hours of manual work.

Create unified activity reports using Coefficient

Coefficient’s advanced association handling lets you combine activity data, custom fields, and associated company information in one import. Instead of managing multiple exports, you get a complete dataset where each activity row includes all relevant context.

How to make it work

Step 1. Set up your Activities import with custom field selection.

Connect to HubSpot through Coefficient and create an Activities import. During field selection, choose both standard activity fields (date, type, subject) and any custom activity properties you’ve configured in your CRM.

Step 2. Add associated company fields using bracket notation.

Include company information by selecting fields like “Company Name (Associated Company)” or “Industry (Associated Company)”. This pulls the relevant company data for each activity without requiring separate exports or complex lookups.

Step 3. Choose your association display format.

Select how you want associated data displayed. “Primary Association” shows the main company, “Comma Separated” lists multiple companies in one cell, and “Row Expanded” creates separate rows for each company association.

Step 4. Configure filters and scheduling.

Apply any necessary filters for date ranges, activity types, or company criteria. Set up automated refreshes to keep your unified report current with new activities and updated company information.

Get complete activity context in one place

This unified approach eliminates the tedious process of matching data across multiple exports and gives you immediate access to comprehensive activity insights with full company context. Build your unified activity report today.

Export activity notes and call recordings metadata together with activity details

HubSpot captures detailed activity information including notes and call recording metadata, but accessing this comprehensive data alongside standard activity details requires more than typical export tools provide.

Here’s how to export complete activity datasets that include both structured data and detailed content like notes and recording information.

Export comprehensive activity content using Coefficient

Coefficient’s ability to access all available activity fields makes it well-suited for detailed CRM data extraction from HubSpot , including notes and call recording metadata that native exports often miss.

How to make it work

Step 1. Set up Activities import with comprehensive field selection.

Create an Activities import focusing on calls, meetings, and tasks that contain notes. During field selection, choose all note-related fields including formatted text content and any custom note properties you’ve configured in HubSpot .

Step 2. Include call recording metadata fields.

Select call recording fields such as “Recording URL,” “Recording Duration,” “Recording Status,” and “Recording File Size” to capture complete call metadata alongside your activity details.

Step 3. Add call disposition and outcome fields.

Include fields like “Call Disposition,” “Call Outcome,” “Call Summary,” and any custom call tracking properties to provide context for your call recordings and notes.

Step 4. Pull associated contact and company context.

Add associated record fields like “Contact Name (Associated Contact)” and “Company Name (Associated Company)” to provide complete context for your activity notes and recordings.

Step 5. Configure activity type filtering.

Apply filters to focus on activities that typically contain notes and recordings: “Activity Type IN calls,meetings,tasks” to exclude activities without detailed content.

Step 6. Schedule regular comprehensive exports.

Set up automated refreshes to maintain current activity information including updated notes and new call recordings without manual export processes.

Access complete activity intelligence

This comprehensive approach captures both structured activity data and detailed content like notes and call metadata, providing the foundation for thorough activity analysis and complete CRM intelligence. Start exporting your complete activity data today.

Export form submissions to spreadsheet on weekly schedule

You can export form submissions from HubSpot to spreadsheets on a reliable weekly schedule using automated imports. This ensures consistent data delivery without manual triggering and keeps your team working with fresh information.

Here’s how to set up flexible weekly scheduling that delivers form submission data automatically to your preferred spreadsheet platform.

Set up reliable weekly form submission exports using Coefficient

Coefficient provides a straightforward solution for exporting HubSpot form submissions to spreadsheets on a reliable weekly schedule. You can choose any day and time for your weekly export, and the system handles automatic execution without manual triggering.

How to make it work

Step 1. Install Coefficient and connect to your HubSpot account.

Add Coefficient to Google Sheets from the Google Workspace Marketplace. Open the Coefficient sidebar and connect to your HubSpot account through the authentication process.

Step 2. Create import for form submission data via Contacts object.

Click “Import from” and select HubSpot, then choose “Contacts” as your object since form submissions create contact records. Select the fields you need like name, email, company, form name, and submission date.

Step 3. Configure weekly scheduling in import settings.

Click “Import Settings” and select “Schedule.” Choose “Weekly” and set your preferred day and time for the automated export. This could be Monday mornings for week planning or Friday afternoons for weekly reviews.

Step 4. Enable data preservation options.

Turn on “Append New Data” if you want to maintain historical form submissions alongside new ones. This creates a comprehensive record of all submissions over time without overwriting previous data.

Step 5. Save and let automation handle the rest.

Once configured, your weekly export runs automatically at the scheduled time. The spreadsheet updates with fresh form submission data, and all users with access see the updated information immediately.

Ensure consistent weekly data delivery

Weekly scheduled exports save hours of manual work while guaranteeing your team always has access to current form submission data. Set up your automated weekly exports today and eliminate the risk of missed or delayed data updates.

Export HubSpot company revenue metrics to external reporting dashboard

You can export HubSpot company revenue metrics to external reporting dashboards using advanced automation and formatting capabilities that create professional, independent dashboards with real-time updates.

This approach transforms HubSpot data into comprehensive external reporting dashboards that operate independently while maintaining data accuracy and professional presentation.

Build external revenue dashboards using Coefficient

Coefficient excels at exporting HubSpot company revenue metrics to create external reporting dashboards with advanced automation and formatting capabilities. You can pull deals, payments, and line items with company associations, calculate MRR, ARR, churn rates, and growth metrics, then build visual dashboards using spreadsheet charts and conditional formatting.

How to make it work

Step 1. Set up revenue data import and metric calculations.

Import deals, payments, and line items with company associations from HubSpot. Use spreadsheet formulas to calculate MRR, ARR, churn rates, and growth metrics automatically. Build visual dashboard components using spreadsheet charts and conditional formatting for professional presentation.

Step 2. Configure advanced export features and automation.

Set up scheduled exports to push calculated metrics back to HubSpot custom properties for CRM visibility. Configure multi-format support to export to Google Sheets, Excel, or CSV for various dashboard tools. Implement conditional exports that trigger only when specific conditions are met, like monthly revenue targets.

Step 3. Build comprehensive dashboard components.

Create revenue tracking with real-time metrics and trend analysis. Build company comparison dashboards with side-by-side performance metrics across different companies. Include pipeline analysis with forecasted revenue and deal progression tracking, plus payment performance showing conversion rates and collection analytics.

Deploy independent revenue dashboards

This creates a comprehensive system for transforming HubSpot data into professional external reporting dashboards that operate independently while maintaining data accuracy. You eliminate expensive dashboard tools while providing executive-ready reporting with real-time updates. Start building your external revenue dashboard today.