Category: HubSpot

Duplicate deals appear in HubSpot’s custom reports when deals have multiple associated contacts or companies, causing the report builder to create separate rows for each association while showing the same deal multiple times.

Here’s how to eliminate duplicate deal entries through proper association handling and ensure your marketing source reports show accurate, non-duplicated deal counts.

Eliminate duplicate deals with precise association handling using Coefficient

Coefficient eliminates duplicate deal issues through transparent association handling options. Unlike HubSpot’s custom report builder that can multiply deal records based on associations, Coefficient gives you specific control over how multiple contacts or companies are displayed for each deal.

How to make it work

Step 1. Configure association settings to prevent deal duplication.

When setting up your Coefficient import, choose “Primary Association” for contact and company fields. This ensures each deal appears only once by showing just the primary contact or company, eliminating the row expansion that creates duplicate deal entries in HubSpot’s native reports.

Step 2. Import key fields for duplicate detection and validation.

Include “Deal ID,” “Original Source,” “Deal Stage,” and relevant association fields in your import. The Deal ID serves as your unique identifier for validation, while association fields help you understand the relationship structure that might cause duplication in other reporting methods.

Step 3. Build validation formulas to detect any remaining duplicates.

Use COUNTIF functions on the Deal ID column to identify any duplicates: =COUNTIF(A:A,A2)>1. Create conditional formatting to highlight duplicate Deal IDs if they appear. This validation step ensures your association settings are working correctly and no deals are being duplicated in your analysis.

Step 4. Create pivot tables that count unique deals by marketing source.

Build pivot tables that count unique Deal IDs by marketing source rather than counting rows. Use “Deal ID” in the values area with “Count of Unique Values” if available, or create helper columns that identify unique deals before building your attribution analysis. This ensures accurate deal counting regardless of association complexity.

Get clean attribution reports without duplicates

Proper association handling eliminates the duplicate deal issues that plague HubSpot’s native custom reports and ensures your marketing attribution analysis is based on accurate, unique deal counts. Start building clean attribution reports with transparent deal counting.

HubSpot’s Salesforce integration imports all fields because it’s designed as an object-level sync rather than providing field-level control, stemming from how the integration maps entire objects between systems rather than allowing granular property selection.

This architectural limitation creates several problems and forces users to find alternative solutions for selective field import.

The technical reasons behind object-level sync

The integration operates on predefined field mappings for entire contact, lead, and account objects with no native interface for selective field import. Sync rules apply to all mapped properties simultaneously, and field mapping occurs at the integration setup level rather than per-sync operation.

This creates significant problems: unnecessary data transfers that slow sync performance, increased risk of overwriting valuable HubSpot data with outdated Salesforce information, impossible targeted backfills without affecting other properties, and complicated data governance when you only need specific fields updated.

Selective field import using Coefficient

Coefficient bypasses these integration limitations by providing true field-level sync control through Google Sheets . You get custom field selection during import setup, conditional exports that ensure updates only occur when specific criteria are met, and scheduled selective syncs that maintain ongoing property-specific import without manual intervention.

How to make it work

Step 1. Set up custom field selection.

Connect both Salesforce and HubSpot to Coefficient, then choose exactly which properties to sync during import setup. This gives you the granular control that native integration lacks.

Step 2. Create conditional export logic.

Use spreadsheet formulas to determine when specific fields should update. For example, =IF(ISBLANK(HubSpot_Field), Salesforce_Field, “”) ensures you only update empty HubSpot fields, preventing unwanted overwrites.

Step 3. Validate data before pushing to HubSpot.

Review and clean your data in the spreadsheet before export. This validation step prevents importing malformed values and gives you complete control over data quality.

Step 4. Schedule selective syncs.

Set up automated schedules for your field-specific imports, maintaining ongoing sync without the limitations of native integration. Use different schedules for different properties based on your business needs.

Take control of your data sync

This approach gives you the granular control that native Salesforce HubSpot integration lacks, enabling efficient selective field import workflows. Start building better data sync processes today.

Your channel counts exceed total deals because HubSpot’s attribution methodology assigns the same deal to multiple marketing channels when deals have multiple touchpoints, while the total count shows unique deals only.

You’ll learn how to implement custom attribution logic that ensures each deal is counted exactly once per source for accurate channel performance analysis.

Implement precise deal counting with custom attribution logic using Coefficient

Coefficient provides complete control over deal counting by importing your HubSpot deals dataset where you can see all source touchpoints and create calculated columns that define your specific attribution rules. This eliminates the over-counting that occurs in HubSpot’s native reports.

How to make it work

Step 1. Import deals with all source attribution fields.

Set up a Coefficient import that includes “Deal ID,” “Original Source,” “Recent Source,” “First Touch Source,” and any other attribution fields you use. This gives you complete visibility into all the touchpoints that might be causing the same deal to appear in multiple channels.

Step 2. Create a primary attribution source column.

Add a calculated column called “Primary Attribution Source” that assigns each deal to exactly one source based on your business logic. Use IF statements to prioritize paid channels over organic, or implement consistent first-touch attribution. For example: =IF(B2=”Paid Search”, “Paid Search”, IF(B2=”Social Media”, “Social Media”, C2)) where B2 is Original Source and C2 is Recent Source.

Step 3. Build validation tables to audit your attribution logic.

Create pivot tables that count unique Deal IDs by your custom “Primary Attribution Source” field. Set up a validation table that shows deals with multiple source touchpoints so you can understand which deals were causing the over-counting issue and verify your attribution rules are working correctly.

Step 4. Verify your channel totals match your deal count.

Use COUNTIF functions to count unique deals by your primary attribution source and compare the sum against your total deal count. They should match exactly when each deal is assigned to only one source. Create conditional formatting to highlight any discrepancies that need investigation.

Get channel metrics you can trust

Custom attribution logic ensures each deal is counted exactly once per source, giving you accurate channel performance metrics instead of inflated numbers. Start building attribution reports that show true channel effectiveness.

Marketing source reports double count deals when using multi-touch attribution models or when deals have multiple associated contacts with different original sources, causing the same deal to appear in multiple channels and inflating your performance metrics.

You’ll learn how to implement single-touch attribution logic with validation checks to ensure each deal is counted exactly once across all marketing channels.

Eliminate double counting with custom attribution methodology using Coefficient

Coefficient provides complete control over attribution methodology by importing all source-related fields from HubSpot and allowing you to create custom logic that assigns each deal to exactly one primary source. This eliminates the ambiguity in HubSpot’s native attribution reporting that causes double counting.

How to make it work

Step 1. Import all source attribution fields for complete visibility.

Set up a Coefficient import that includes “Deal ID,” “Original Source,” “Recent Source,” “First Touch,” “Last Touch,” and any other attribution fields you use. This complete dataset lets you see all the touchpoints that might be causing the same deal to appear in multiple channels.

Step 2. Create custom attribution rules for single-touch assignment.

Build a calculated column called “Primary Attribution Source” that assigns each deal to exactly one channel based on your business rules. Use IF statements to prioritize paid channels over organic or implement consistent first-touch attribution: =IF(B2=”Paid Search”,”Paid Search”,IF(B2=”Social Media”,”Social Media”,C2)) where you define clear precedence rules.

Step 3. Build validation checks to ensure accurate counting.

Use COUNTIF functions on Deal ID to verify each deal appears only once in your attribution analysis. Create a validation table that compares your individual channel totals against your overall deal count – they should match exactly when using single-touch attribution. Set up conditional formatting to highlight any discrepancies.

Step 4. Create pivot tables with unique deal counting.

Build pivot tables that group by your custom “Primary Attribution Source” field and count unique Deal IDs rather than rows. This ensures accurate channel performance metrics that eliminate the double counting issues present in HubSpot’s native multi-touch attribution reports.

Get attribution metrics you can actually trust

Single-touch attribution with validation checks eliminates double counting and provides reliable marketing channel performance metrics instead of inflated numbers that skew your analysis. Start building attribution reports with accurate deal counting across all channels.

Your deal counts don’t match because HubSpot’s native reporting creates attribution conflicts when deals have multiple touchpoints, null source values, or overlapping attribution models that count the same deal across different channels.

Here’s how to build transparent deal attribution reports that show exactly which deals are causing the mismatch and ensure accurate source counting.

Get accurate deal attribution with transparent counting using Coefficient

Coefficient solves deal counting discrepancies by importing your HubSpot deals data into spreadsheets where you can see every record and implement precise counting logic. Unlike HubSpot’s hidden attribution models, you get complete visibility into which deals are attributed to which sources and why your totals might not match.

How to make it work

Step 1. Import your deals data with source attribution filters.

Set up a Coefficient import with filters for “Deal Stage = Closed Won” and include fields like “Deal ID,” “Original Source,” “Recent Source,” and “Deal Amount.” Use the “Original Source is known” filter to exclude deals with missing attribution data that often cause counting mismatches.

Step 2. Create validation tables to identify attribution conflicts.

Build a validation section that counts unique deals by source using COUNTIFS formulas. Create a summary table that shows total deals versus the sum of all source-specific counts. This immediately reveals if deals are being double-counted or excluded from your attribution analysis.

Step 3. Implement custom attribution logic for consistent counting.

Add a calculated column called “Primary Attribution Source” that assigns each deal to exactly one source based on your business rules. Use IF statements to prioritize paid channels over organic or implement first-touch attribution consistently. This eliminates the overlapping counts that HubSpot’s native reports create.

Step 4. Set up dynamic filtering for different attribution scenarios.

Use Coefficient’s dynamic filtering feature to create dropdown selectors for different attribution models. Reference these cells in your import filters so you can test how different attribution rules affect your deal counts and identify the source of discrepancies.

Build reports that actually add up

Transparent deal attribution eliminates the guesswork in HubSpot’s native reporting and ensures your marketing source analysis is accurate and reliable. Start building attribution reports that show exactly how your deals are counted.

Removing company associations from deals won’t delete your historical activities or timeline events, but the association removal itself becomes part of the deal’s activity history with a timestamp.

Here’s what stays intact, what changes, and how to create protective data snapshots before making bulk association changes.

Protect your data while removing associations using Coefficient

While HubSpot preserves most historical data when you remove associations, Coefficient lets you create comprehensive data snapshots before making changes. This gives you restoration options if association removal has unintended consequences that HubSpot’s native activity timeline can’t fully address.

How to make it work

Step 1. Create comprehensive data snapshots before removal.

Use Coefficient’s snapshot feature to capture complete association history with timestamps, activity counts per association, and backup datasets. This creates a historical record that supplements HubSpot’s native activity timeline and provides restoration options if needed.

Step 2. Assess potential impact on your data.

Export association data to see activity counts per association for impact assessment. This helps you understand which associations have significant activity history and might need special consideration before removal. Look at email counts, meeting records, and other logged activities tied to each association.

Step 3. Set up scheduled backup monitoring.

Configure automated snapshots on a scheduled basis to create ongoing historical records of your association data. This ensures you always have recent backups available and can track changes over time, even after associations are removed.

Step 4. Document what remains intact after removal.

Understand that all logged activities (emails, calls, meetings, notes) stay on both deal and company records, timeline entries showing when associations were created/removed remain visible, and historical reporting data where activities were already attributed stays unchanged.

Step 5. Plan for what changes after removal.

Be aware that future activities won’t auto-associate between the deal and removed company, association-based automated workflows may stop triggering, and some reports filtering by current associations may show different results going forward.

Remove associations safely with proper data protection

Creating comprehensive snapshots before association removal gives you peace of mind and restoration options that HubSpot’s native tools can’t provide. Start protecting your association data today.

When your reporting platform only supports monthly goals, you face the mathematical impossibility of evenly distributing monthly targets across weeks, since months contain 4-5 weeks and don’t align with week boundaries.

Here’s an effective workaround that moves your goal visualization outside the constrained reporting platform to get proper weekly alignment.

Move goal visualization outside platform constraints using Coefficient

The core issue is that platforms with monthly-only goals create jagged goal lines that don’t represent your actual weekly targets. Coefficient provides a workaround by extracting your data and rebuilding goal visualization with proper weekly alignment.

How to make it work

Step 1. Extract raw data from your reporting platform.

Use Coefficient to pull your sequence enrollment data from HubSpot or HubSpot into spreadsheets. This bypasses the platform’s goal distribution logic entirely.

Step 2. Group data by week using spreadsheet functions.

Use functions like WEEKNUM and SUMIFS to aggregate your data by proper weekly periods. This gives you clean weekly groupings without monthly period interference.

Step 3. Create a separate goal line data series.

Add your true weekly goal (like 20 companies) as a separate column for each week. This becomes a consistent horizontal goal line regardless of calendar variations.

Step 4. Build charts with properly aligned series.

Create visualizations where both actual performance and weekly goals display as separate, properly aligned series. You can add multiple goal scenarios or benchmarks as needed.

Step 5. Set up dynamic updates with consistent goals.

Schedule Coefficient imports to refresh actual data while maintaining consistent goal lines. Use the snapshot feature to track historical goal performance over time.

Eliminate the period mismatch problem

This workaround eliminates the fundamental period mismatch that causes visualization problems in platforms with monthly-only goal settings. Start building your proper weekly goal visualization today.