Category: HubSpot

Why does CRM merge overwrite existing data with blank fields from newer records

HubSpot’s merge logic prioritizes the “primary record” (typically the newer one) for most properties, which means blank fields from newer records will overwrite valuable existing data without considering data completeness.

This happens because HubSpot’s default merge behavior doesn’t evaluate whether fields are populated. You’ll learn how to analyze merge impacts before they happen and protect your data.

Analyze merge impacts before losing data using Coefficient

The key to preventing data loss is understanding exactly what will be overwritten before you merge. Coefficient lets you import both duplicate records into your spreadsheet to compare field completeness and make informed decisions about which record should be primary.

How to make it work

Step 1. Import your duplicate records for analysis.

Connect HubSpot to HubSpot through Coefficient and import both records with all their properties. Use filters to pull specific contact or company IDs you’re planning to merge. This gives you a complete side-by-side view that HubSpot’s merge preview doesn’t provide.

Step 2. Create formulas to identify potential data loss.

Build spreadsheet formulas that compare each field between the two records. Use conditional formatting to highlight cells where the newer record has blank values that would overwrite populated data in the older record. For example, =IF(AND(B2=””,C2<>“”),”DATA LOSS”,”OK”) will flag fields at risk.

Step 3. Calculate data completeness scores.

Create a formula that counts populated fields for each record: =COUNTA(B2:B50) for record one and =COUNTA(C2:C50) for record two. This helps you determine which record actually has more complete information, regardless of creation date.

Step 4. Set up automated backup snapshots.

Use Coefficient’s snapshot feature to capture complete record states before performing any merges. Schedule daily or weekly snapshots of your contact and company data so you always have recovery points if merge operations cause unexpected data loss.

Protect your data with smart merge analysis

HubSpot’s timestamp-based merge logic doesn’t consider data quality, but you can. By analyzing field completeness before merging, you’ll prevent valuable data from being overwritten with blanks. Start protecting your merge data today.

Why HubSpot deal stage history doesn’t update in funnel reports after retroactive changes

HubSpot’s funnel reports use snapshot-based logic that captures deal stage status at specific points in time rather than dynamically updating based on current deal status. When you retroactively update deal stages, the original funnel data remains unchanged because it’s based on historical timestamps, not current deal state.

This architectural limitation means deals marked as “missed” stay that way in reports even if you later move them to Closed Won.

Create dynamic funnel reporting that reflects updated deal progression

Coefficient bypasses this limitation by pulling live HubSpot deal data including complete stage history into spreadsheets. You can then build reporting logic that evaluates deal progression based on final outcomes, not just chronological movement.

How to make it work

Step 1. Import real-time deal data with complete stage history.

Pull current deal status and complete stage history from HubSpot , allowing you to build reports that reflect updated deal progression rather than static historical snapshots.

Step 2. Build custom funnel logic based on final outcomes.

Create formulas that evaluate deal stage progression based on current status. Deals that eventually close won can be properly classified as “converted” across all previous stages, regardless of when they were updated.

Step 3. Set up automated updates for continuous accuracy.

Schedule regular imports so your custom funnel analysis automatically reflects any retroactive changes made in HubSpot. This ensures reporting accuracy without manual intervention every time deal stages are updated.

Step 4. Track retroactive update patterns for process insights.

Identify which deals were retroactively updated and analyze patterns in timing or deal characteristics. This reveals potential process issues that cause initial stage misclassification.

Build funnel reports that reflect true deal progression

This approach provides funnel reporting that accurately reflects current deal reality instead of outdated snapshots. Get started with dynamic funnel analysis that updates automatically.

Why HubSpot’s reporting falls short for client-facing deliverables

Native HubSpot reporting falls short for client-facing deliverables because it prioritizes internal team functionality over external client communication needs. Fundamental design limitations prevent the professional presentation, custom branding, and contextual explanations that clients expect.

Here’s how to transform HubSpot data into professional client deliverables that justify premium service fees.

Create professional client reports using Coefficient

Coefficient transforms raw HubSpot data into polished client deliverables with branded formatting, executive summaries, and contextual explanations that HubSpot dashboards cannot provide.

How to make it work

Step 1. Address presentation quality limitations.

Import HubSpot data into Google Sheets or Excel where you can apply custom branding, professional formatting, and cohesive narrative structure. Create executive summaries and contextual explanations that guide client understanding.

Step 2. Eliminate technical accessibility barriers.

Present data in familiar spreadsheet environments that don’t require CRM training. Translate technical field names into business language and add guided explanations for complex metrics.

Step 3. Enable advanced data analysis.

Perform sophisticated calculations like customer lifetime value trends, attribution modeling, and ROI analysis that HubSpot’s report builder cannot handle. Combine HubSpot data with other business intelligence sources for comprehensive insights.

Step 4. Build narrative-driven reports.

Structure reports to tell a story, starting with key insights and drilling down to supporting data. Include comment sections for explaining trends, highlighting specific insights, and providing actionable recommendations.

Step 5. Create flexible delivery formats.

Generate professional PDF exports, interactive spreadsheets, or presentation-ready visuals that work in client meetings and board presentations. Enable offline review capabilities with maintained formatting.

Step 6. Add multi-source integration capabilities.

Combine HubSpot CRM data with website analytics, advertising performance, and other business metrics for comprehensive performance reporting that’s impossible with native dashboards alone.

Deliver reports that justify premium pricing

Professional client deliverables enable agencies to demonstrate sophisticated analysis capabilities while ensuring clients can easily understand and act on insights provided. This approach supports higher service fees through improved perceived value. Start creating professional client reports today.

Why non-technical stakeholders can’t understand HubSpot dashboards

Non-technical stakeholders struggle with HubSpot dashboards because they prioritize functionality over accessibility. Technical terminology, information overload, and lack of contextual explanations create barriers for executives who need insights without CRM training.

Here’s how to transform complex HubSpot data into stakeholder-friendly reports that anyone can understand.

Create accessible dashboards using Coefficient

Coefficient transforms HubSpot data into familiar spreadsheet formats with custom explanations and business-friendly language. Instead of technical CRM widgets, stakeholders get clear narratives with contextual guidance.

How to make it work

Step 1. Use familiar spreadsheet interfaces.

Import HubSpot data into Google Sheets or Excel – environments most stakeholders already understand. This eliminates the learning curve of navigating HubSpot’s complex interface.

Step 2. Add contextual explanations alongside data.

Include definitions, explanations, and business context directly next to metrics. Instead of showing “MQL to SQL conversion rate: 23.4%”, present “Marketing Qualified Lead Performance: 23 out of every 100 marketing leads become sales opportunities, representing a 15% improvement from last quarter.”

Step 3. Create executive summary sections.

Build dedicated summary areas with key takeaways written in business language rather than technical metrics. Start with high-level insights and drill down to supporting details in a logical narrative flow.

Step 4. Apply visual hierarchy and branding.

Use spreadsheet formatting to create clear information hierarchy, highlighting the most important metrics prominently. Maintain consistent company branding and professional formatting that matches stakeholder expectations.

Step 5. Structure reports to tell a story.

Organize data to guide stakeholders through insights logically. Start with performance highlights, explain what drove results, and conclude with actionable recommendations based on the data.

Make your data accessible to everyone

Stakeholder-friendly reporting transforms raw HubSpot data into digestible business intelligence that drives better decision-making across your organization. Start creating accessible reports today.

Workaround for aggregating multiple deal stages into single number in HubSpot reports

HubSpot’s custom report builder cannot aggregate multiple deal stages into unified metrics due to formula field limitations, forcing sales teams to work with fragmented data across separate widgets.

Here’s a robust workaround that provides true aggregation capabilities with real-time updates and advanced filtering options.

Import HubSpot data for native spreadsheet aggregation using Coefficient

Coefficient provides a solution by importing HubSpot data into spreadsheets where native aggregation functions are fully available. This eliminates the need for complex HubSpot reporting workarounds while providing enterprise-level capabilities.

How to make it work

Step 1. Create filtered imports for target deal stages.

Set up imports with up to 25 filters using AND/OR logic to include specific deal stages. Apply multi-stage filtering to capture exactly the deal combinations you need for your aggregated metrics.

Step 2. Build aggregation formulas for stage combinations.

Use formulas like =SUMPRODUCT((Stage=”Closed Won”)+(Stage=”Closed Lost”)) for complex stage combinations. Create dynamic aggregations that count, sum, or average across multiple stages in ways HubSpot simply can’t handle.

Step 3. Pull related contact and company data.

Import associated contact and company data alongside deal information for comprehensive stage analysis. This provides context that HubSpot’s limited association handling in reports can’t match.

Step 4. Set up real-time updates with scheduled refreshes.

Configure automatic refreshes to ensure aggregated numbers stay current. Schedule updates from hourly to monthly based on your reporting needs, with data staying synchronized automatically.

Step 5. Create automated alerts for significant changes.

Set up Slack alerts when aggregated numbers change significantly. Use conditional formatting to highlight key metrics and create snapshots to track aggregated metrics over time.

Get enterprise-level aggregation that surpasses native HubSpot functionality

This approach eliminates the need for complex HubSpot reporting workarounds while providing aggregation capabilities that far exceed what the platform offers natively. Start building the unified deal stage metrics your team needs.

Workaround for HubSpot report error “date field already used in compare by section”

This specific HubSpot error appears when you try to use the same date field in both the Compare by functionality and the Filters section, blocking your report creation entirely.

Here’s a complete workaround that eliminates this restriction and gives you unlimited date field usage for period comparisons.

Bypass HubSpot’s reporting engine completely using Coefficient

Coefficient eliminates this limitation by importing raw HubSpot data into spreadsheets where no such restrictions exist. You can use any date field multiple times across different filters and comparison logic without triggering HubSpot errors.

How to make it work

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

Set up the connection through Coefficient’s Connected Sources menu. This gives you direct access to your HubSpot data without going through the platform’s restricted reporting engine.

Step 2. Import the same data set multiple times with different date filters.

Create separate imports for different time periods using Coefficient’s dynamic filtering capabilities. For example, import Q1 2024 data in one tab and Q1 2023 data in another, using the same date field for both without any restrictions.

Step 3. Build custom comparison logic using spreadsheet formulas.

Use functions like SUMIFS, COUNTIFS, and AVERAGEIFS to create period-over-period analyses. Calculate differences, percentages, and trends using formulas like =(Current_Period – Previous_Period)/Previous_Period*100 for percentage change.

Step 4. Create visualizations and dashboards with unlimited date field usage.

Build charts, pivot tables, and conditional formatting that would be impossible in HubSpot due to the date field restriction. You can now analyze the same date field across multiple dimensions simultaneously.

Step 5. Set up automated refreshes and alerts.

Schedule these imports to refresh automatically (hourly, daily, or weekly) and configure Slack or email alerts when data updates. Your period comparison reports always reflect current data without manual intervention.

Turn HubSpot’s restriction into advanced analysis capability

This workaround transforms a HubSpot reporting limitation into an opportunity for more sophisticated analysis than the platform could ever provide natively. Get started with unlimited date field usage today.

Workaround for missing meeting association options in Zapier HubSpot integration

Zapier’s HubSpot integration doesn’t include meeting association options in its create association action, leaving you stuck when trying to link meetings to deals or contacts. This gap forces you to find alternative methods for managing these critical data relationships.

Here’s a reliable workaround that handles meeting associations more effectively than Zapier’s limited options.

Create meeting associations through spreadsheet automation using Coefficient

Coefficient provides comprehensive HubSpot object management that includes all the association options Zapier is missing. You can import meetings and deals from HubSpot , create association mapping in your spreadsheet, then export those relationships back to HubSpot automatically.

How to make it work

Step 1. Set up your data imports.

Connect Coefficient to HubSpot and import meetings using the object import feature (this supports all fields including meeting IDs). Also import deals with any custom properties containing meeting references, and apply filters to focus on unassociated meetings or specific date ranges.

Step 2. Create your association mapping sheet.

Build a mapping sheet with columns for Meeting ID and Deal ID. Use spreadsheet functions to match meetings to deals based on contact associations, custom properties containing meeting IDs, date/time proximity matching, or your specific business rules.

Step 3. Configure automated association exports.

Set up Coefficient’s export action to “Add Association” between meetings and deals. Map your Meeting ID and Deal ID columns to the appropriate fields, then schedule exports to run automatically every hour or daily. Use conditional logic to only create associations when both IDs are present.

Step 4. Build monitoring and maintenance systems.

Set up email or Slack alerts for association failures, create snapshot reports to track association success rates, and build a dashboard showing meetings without deal associations. This gives you visibility that traditional automation tools can’t provide.

Get better control than Zapier offers

This approach handles bulk associations efficiently, provides visual verification before pushing changes, and creates audit trails of all associations. You also avoid API call limitations and get more flexible matching logic using spreadsheet formulas. Start building your meeting association workflow today.

Workaround for missing user ID quick filter in HubSpot goal tracking dashboards

HubSpot’s goal tracking dashboards completely lack user ID quick filters, making it impossible to view individual performance metrics without manually editing dashboard filters or creating separate dashboards for each user. Both solutions are inefficient and time-consuming.

Here’s the definitive workaround that gives you the user ID quick filtering functionality HubSpot is missing.

Create user ID quick filtering using Coefficient

Coefficient provides the definitive workaround by importing HubSpot deal and user data with live connectivity, eliminating the need for HubSpot’s limited dashboard system. You can create user ID filter cells that instantly change the entire report view, essentially building the quick filter functionality HubSpot lacks.

How to make it work

Step 1. Set up live HubSpot data import with user associations.

Connect to HubSpot and import deals with owner associations included. This automatically handles the connection between deals and their owners, maintaining the relationships that manual exports often break.

Step 2. Create user selection filter cell.

Set up a user selection cell using either dropdown lists or manual entry. You can filter by both user ID numbers and user names, giving you the flexibility HubSpot’s system doesn’t provide.

Step 3. Point import filters to reference the selection cell.

Configure your Coefficient import to dynamically reference your user selection cell. When you change the user in that cell, the entire report instantly filters to show only that person’s deals and goal progress.

Step 4. Build goal tracking calculations.

Use spreadsheet formulas to create goal tracking metrics that automatically update with your filtered data. Calculate gap-to-goal, conversion rates, and pipeline health that refresh when you change users.

Step 5. Schedule automatic data refreshes.

Set up hourly, daily, or weekly refreshes to maintain current information while preserving your user filtering functionality. This gives you real-time accuracy without manual intervention.

Get the user filtering HubSpot should have

This workaround delivers the user ID quick filtering that would require custom development within HubSpot’s ecosystem. You get instant individual performance views without the limitations of native dashboards. Implement this solution and transform your goal tracking today.

Workarounds for HubSpot’s two-period limitation in social media reporting

HubSpot’s social media reporting only allows comparisons between two time periods, which makes it nearly impossible to track long-term trends or analyze seasonal patterns. This limitation forces you into a narrow view of your social media performance.

The good news is you can work around this restriction by implementing alternative tracking methods that preserve unlimited historical data and enable comprehensive multi-period analysis.

Build unlimited period comparisons with custom tracking using Coefficient

Coefficient provides powerful workarounds for multi-period analysis by helping you implement alternative tracking methods that bypass HubSpot’s native limitations entirely.

How to make it work

Step 1. Create custom properties for key social metrics.

Set up custom properties on your Deals, Companies, or Contacts to track important social media KPIs. This might include monthly engagement rates, follower growth, or social-driven lead counts that you update regularly.

Step 2. Set up monthly snapshots to preserve historical data.

Use Coefficient’s snapshot functionality to capture monthly data points automatically. Schedule these snapshots for the first of each month to build a comprehensive historical dataset that HubSpot can’t provide natively.

Step 3. Configure scheduled imports with dynamic filtering.

Set up automated imports that pull your custom social media properties from HubSpot. Use dynamic date filtering to segment data by specific time ranges, giving you flexibility that HubSpot’s two-period limit doesn’t allow.

Step 4. Build trend formulas using historical snapshot data.

Create formulas that reference your historical snapshots to calculate year-over-year comparisons, quarterly trends, and seasonal performance patterns. Coefficient’s formula auto-fill ensures these calculations apply to new data automatically.

Step 5. Set up automated alerts for significant changes.

Configure email or Slack alerts when your social media metrics hit specific thresholds or show significant period-over-period changes. This gives you real-time insights into performance trends.

Get the historical analysis HubSpot can’t provide

This approach completely bypasses HubSpot’s two-period limitation while maintaining automated data updates and historical preservation. You’ll have unlimited period comparisons and the ability to spot trends that would be impossible to see otherwise. Start building your comprehensive social media trend reports today.

Workarounds for missing “became customer date” property in HubSpot company records

The removal of HubSpot’s native “became customer date” property creates a fundamental data gap since the platform lacks built-in functionality to automatically calculate when companies first converted based on deal activity.

The most effective workaround reconstructs this missing data using deal history analysis and provides more reliable customer conversion tracking than the original deprecated property.

Recreate customer conversion dates using deal data reconstruction

Coefficient serves as the most effective workaround by providing the missing calculation layer that HubSpot removed. This approach often delivers more reliable and flexible customer conversion tracking than the original property ever provided.

How to make it work

Step 1. Import complete company deal history.

Use Coefficient to import all HubSpot companies with their complete deal history using association imports. This recreates the missing timeline data needed to calculate accurate conversion dates.

Step 2. Calculate accurate conversion dates.

Use MIN and FILTER functions to identify the earliest “Closed Won” deal date for each company. Create formulas like =MIN(IF(company_column=company_name,IF(stage_column=”Closed Won”,date_column))) to effectively recreate the “became customer date” logic.

Step 3. Implement data integrity validation.

Build spreadsheet checks to handle edge cases like companies with multiple won deals on the same date, deal types that shouldn’t count as customer conversions, and archived or deleted deal records. This ensures accuracy beyond what the original property provided.

Step 4. Choose your output approach.

Keep calculated dates in spreadsheets for advanced analysis, export them back to custom HubSpot company properties, or maintain both for maximum flexibility. Each approach serves different reporting and workflow needs.

Step 5. Automate ongoing updates.

Schedule regular imports and calculations to ensure your workaround stays current without manual intervention. This maintains the automation you had with the original property while providing better accuracy.

Get better customer tracking than before

This workaround not only replaces the missing functionality but provides more reliable customer conversion tracking with audit trails and data validation capabilities. Start rebuilding your customer conversion tracking today.