Category: Excel

How to display data from 3 connected objects in single junction object report in Salesforce

Displaying data from three connected objects in a single Salesforce report through junction objects presents significant technical challenges that often require complex custom report types or multiple separate reports.

Here’s how to consolidate data from multiple connected objects into a single, comprehensive view without technical complexity.

Why native Salesforce struggles with three-object reporting

Standard report types typically don’t include all three object relationships, formula fields become complex when traversing multiple relationship levels, and performance issues arise with multi-object joins in large datasets. This approach also requires advanced Salesforce configuration knowledge and offers limited flexibility for modifying field selections.

Consolidate three-object data using Coefficient

Coefficient excels at consolidating data from multiple connected objects into a single, comprehensive view. You can integrate data from your junction object and both related objects simultaneously in one streamlined process.

How to make it work

Step 1. Establish your junction object as the foundation.

Start with your junction object using Coefficient’s “From Objects & Fields” feature. This creates the primary data structure that will connect your three objects together in a single report.

Step 2. Select fields from the first connected object.

Expand the related object sections to browse and select specific fields from the first connected parent or child object. Coefficient displays all available fields in an intuitive interface without technical barriers.

Step 3. Add fields from the second connected object.

Navigate to the second related object section and choose the fields you need from this object. You can select fields from multiple objects simultaneously, creating a unified data view in your spreadsheet.

Step 4. Apply cross-object filtering and logic.

Set up AND/OR filtering conditions that work across all three objects simultaneously. This allows you to refine your dataset based on criteria from any of the connected objects while maintaining the unified view.

Step 5. Configure automated updates and analysis.

Set up scheduled refreshes to keep your three-object data current and leverage spreadsheet functionality for advanced analysis. Use dynamic filters pointing to cell values for flexible reporting without modifying import settings.

Start building comprehensive three-object reports

This approach transforms the challenge of three-object reporting from a complex technical project into a straightforward data import and analysis workflow. Begin creating your unified three-object reports today.

How to display data from different report folders in one Salesforce dashboard

While Salesforce dashboards can access reports from different folders, managing and refreshing multiple folder sources becomes complex and fragmented with large numbers of reports across your organization.

Here’s how to consolidate reports from any folder structure into a single, centrally managed dashboard view.

Consolidate reports from any folder location using Coefficient

Coefficient simplifies multi-folder reporting by providing centralized access to reports regardless of their folder location. You can pull reports from Sales folders, Marketing folders, Service folders, and any custom folders into a single dashboard view without navigating between different folder structures.

How to make it work

Step 1. Import reports from any folder in your organization.

Use Coefficient’s “From Existing Report” feature to import ANY Salesforce report you have access to, regardless of which folder it’s stored in. The system provides centralized access without requiring you to navigate folder structures.

Step 2. Organize imported reports in a single workbook.

Place all your imported reports from different folders into separate sheets within one workbook. This eliminates the need to create duplicate reports in specific folders just for dashboard purposes or manage multiple dashboard components across different folders.

Step 3. Set up unified refresh scheduling.

Configure refresh schedules that update all imported reports simultaneously, regardless of their original folder locations. This provides centralized management of your multi-folder data sources with consistent timing across all reports.

Step 4. Create cross-folder dashboard views.

Build unified dashboard sheets that combine data from reports across your entire folder structure. Use formulas to create metrics that span Sales, Marketing, Service, and custom folder reports in ways that would require multiple dashboard components in native Salesforce.

Step 5. Use Snapshots for historical cross-folder analysis.

Enable the Snapshots feature (available in Google Sheets) to preserve data from different folder sources at specific points in time. This creates historical views that span your entire report folder structure for trend analysis across departments.

Unify your folder structure into one dashboard

Stop managing separate dashboard components across different report folders. Start consolidating reports from your entire Salesforce folder structure into unified, centrally managed dashboards.

How to display outstanding vs paid Xero invoices on HubSpot project dashboards

You can display outstanding vs paid Xero invoices on HubSpot project dashboards by processing invoice data in spreadsheets and pushing calculated totals to project custom properties that feed your dashboard reports.

This approach overcomes HubSpot’s inability to access Xero data directly while maintaining the familiar dashboard interface your project teams already use.

Create financial dashboards with automated data processing using Coefficient

HubSpot’s dashboard tools can’t directly access Xero data, and its calculated properties lack the complexity needed for dynamic AR analysis across projects. Coefficient solves this by processing both data sources in spreadsheets and pushing calculated metrics to HubSpot or HubSpot project properties that power your dashboards.

How to make it work

Step 1. Import and process data with scheduled refreshes.

Set up scheduled imports for both Xero invoices and HubSpot projects, then use spreadsheet formulas to calculate outstanding vs paid amounts by project with automatic refresh. This creates the foundation for your dashboard metrics.

Step 2. Create calculated metrics with aging analysis.

Build formulas that categorize invoices by payment status and sum amounts by project, including aging calculations (30/60/90 days overdue). For example: =SUMIFS(Invoices!C:C,Invoices!A:A,B2,Invoices!D:D,”Outstanding”) to calculate total outstanding by project.

Step 3. Use snapshots for trending and historical data.

Leverage snapshot features to capture daily or weekly AR summaries, enabling trend analysis of outstanding amounts over time per project. This provides historical context that enhances dashboard value.

Step 4. Export summary data to HubSpot project properties.

Push calculated totals to HubSpot project custom properties like “Total Outstanding Amount,” “Total Paid Amount,” “Overdue Amount,” and “Days Sales Outstanding.” These properties become the data source for your dashboard reports.

Step 5. Build HubSpot dashboard with visual indicators.

Create dashboard reports using the populated custom properties, showing project financial health with visual indicators for payment status. Use HubSpot’s native dashboard tools to display the processed data.

Step 6. Set up automated alerts for threshold monitoring.

Configure alerts to notify project managers when outstanding amounts exceed thresholds or when aging increases beyond acceptable limits, ensuring proactive financial management.

Transform your project financial visibility

This automated approach provides complex financial calculations across external data sources while maintaining the familiar HubSpot dashboard interface. Build your financial dashboard today.

How to distribute monthly revenue across flight duration in HubSpot

HubSpot lacks the mathematical functions needed for monthly revenue distribution across variable flight durations, especially when flights span multiple months with different day counts and require complex proration calculations.

Here’s how to create precise monthly revenue distribution that accounts for varying month lengths and provides accurate financial reporting.

Distribute revenue accurately across flight periods using Coefficient

Coefficient provides comprehensive monthly revenue distribution capabilities by connecting your HubSpot line items to spreadsheets where you can build sophisticated formulas. This handles complex multi-month distribution scenarios that HubSpot simply can’t manage natively.

How to make it work

Step 1. Import flight data from HubSpot.

Connect HubSpot line items with flight dates and total revenue to your spreadsheet using Coefficient. This gives you the base data needed for distribution calculations across multiple months.

Step 2. Create month-by-month breakdown formulas.

Build formulas that identify each month within the flight period using SEQUENCE and EOMONTH functions. This automatically creates a row for each month that the flight spans.

Step 3. Calculate daily rates and monthly distribution.

First calculate the daily revenue rate: =Total_Revenue / (Flight_End – Flight_Start + 1). Then for each month, calculate: =Daily_Rate * (Days_in_Month_During_Flight). This ensures accurate distribution based on actual flight activity.

Step 4. Handle partial months accurately.

Use this formula to get actual days per month: =MAX(0, MIN(EOMONTH(month,0), Flight_End) – MAX(EOMONTH(month,-1)+1, Flight_Start) + 1). This handles flights that start or end mid-month with precise day calculations.

Step 5. Create summary reports and automation.

Build pivot tables that automatically sum distributed revenue by month across all flights. Schedule Coefficient to refresh calculations daily, ensuring distribution stays accurate as new flights are added to HubSpot.

Get precise monthly revenue distribution

This creates accurate monthly revenue distribution that accounts for varying month lengths and partial months, providing financial reporting precision that HubSpot cannot deliver natively. Start building your revenue distribution system today.

How to export Salesforce tabular reports as Excel spreadsheets

While tabular reports seem simple to export via Apex, you’ll hit JSON parsing complexity, memory limits, and Excel formatting challenges that make custom development unnecessarily complicated.

Here’s how to export tabular reports to Excel with unlimited rows, advanced filtering, and automated refreshes without writing any code.

Export unlimited tabular report data to Excel using Coefficient

Coefficient optimizes tabular report exports with direct field mapping, dynamic filtering, and formula integration. You get unlimited rows without the 2K limit restrictions and real-time updates that eliminate stale data issues.

How to make it work

Step 1. Import your tabular report using the “From Existing Report” method.

Connect to your Salesforce org and select any tabular report. Coefficient automatically maps all report columns to Excel columns, preserving field names and data types without manual configuration.

Step 2. Apply dynamic filters for flexible data subsets.

Set up filters that point to cell values, allowing you to change filter criteria without editing import settings. Use complex AND/OR logic with Number, Text, Date, Boolean, and Picklist fields to create exactly the data subset you need.

Step 3. Configure Formula Auto Fill Down for calculated columns.

Place formulas in columns immediately right of your imported data. When the report refreshes, Coefficient automatically copies these formulas to new rows, maintaining your calculated fields and analysis without manual updates.

Step 4. Set up automated refresh scheduling and alerts.

Schedule refreshes from hourly to weekly intervals. Enable Slack or email alerts for data changes, and use the Append New Data feature to maintain historical context while incorporating updates from your Salesforce tabular reports.

Get enterprise-level automation without the development overhead

This approach provides unlimited tabular report processing with advanced Excel functionality that Apex simply can’t match, all without custom code maintenance. Start exporting your Salesforce tabular reports to Excel today.

How to export SSN and bank account numbers from HubSpot when CSV export blocks sensitive fields

HubSpot’s CSV export intentionally blocks SSN and bank account numbers as a security measure, but you can still access this sensitive data through direct API connections that bypass these export limitations.

Here’s how to extract highly sensitive properties from HubSpot without hitting the CSV roadblocks that prevent bulk data migration.

Access sensitive fields through direct API connections using Coefficient

Coefficient connects directly to HubSpot through API rather than relying on CSV exports. This means it can import highly sensitive properties that are blocked in standard export functions, giving you access to SSN and bank account fields that CSV exports won’t touch.

How to make it work

Step 1. Connect Coefficient to HubSpot with proper permissions.

Navigate to the “Connected Sources” menu in Coefficient’s sidebar and establish your HubSpot connection. You’ll need Super Admin access to grant permissions for highly sensitive properties during the initial setup process.

Step 2. Create a new import targeting your sensitive data objects.

Select your contact or deal objects that contain the SSN and bank account custom properties. The field selection interface will show these sensitive fields that CSV exports typically block.

Step 3. Apply filters to target specific records.

Use Coefficient’s filtering capabilities (up to 25 filters) to pull only the records you need for your data migration. This lets you target specific loan records or customer segments without downloading everything.

Step 4. Set up automated refresh for ongoing data sync.

Configure scheduled imports to keep your sensitive data current during migration processes. This eliminates manual copy-paste operations for hundreds of loan records and ensures data stays synchronized.

Start accessing your blocked sensitive data today

This API-based approach solves the bulk export challenge for HubSpot data migration while maintaining security protocols. Ready to bypass those CSV limitations? Get started with Coefficient today.

How to extract hour timestamps from HubSpot ticket create date for analysis

HubSpot stores complete timestamp data but provides no built-in way to extract hour components for analysis, and its calculated properties can’t perform time-based extractions from existing timestamp fields.

You’ll learn how to access HubSpot’s complete timestamp data and use powerful extraction formulas to create the foundation for granular time analysis.

Access complete timestamp data with Coefficient

HubSpot’s custom fields can’t automatically populate with hour values from existing timestamp fields, leaving you unable to perform granular time analysis within the platform. But HubSpot does store full timestamp information that you can extract and manipulate in spreadsheets.

How to make it work

Step 1. Import full timestamp data from HubSpot.

Connect to HubSpot tickets and import the “Create Date” field, which contains complete timestamp information including hours, minutes, and seconds. This raw data is what you’ll use for all subsequent time extractions.

Step 2. Use hour extraction formulas.

In adjacent columns, use =HOUR(B2) where B2 contains your HubSpot timestamp to extract just the hour component in 0-23 format. This creates a new column showing only the hour when each ticket was created.

Step 3. Extract additional time components.

Add more time analysis columns using =WEEKDAY(B2) for day of week, =DAY(B2) for day of month, or =MINUTE(B2) for more granular analysis. Each formula targets a specific time component from the same timestamp.

Step 4. Enable automated formula application.

Turn on Formula Auto Fill Down so new tickets automatically get their hour components calculated when data refreshes. This eliminates manual work as your dataset grows.

Step 5. Apply time zone adjustments if needed.

For multi-timezone analysis, use formulas like =HOUR(B2+TIME(offset_hours,0,0)) to standardize timestamps across different regions. Replace “offset_hours” with the appropriate timezone difference.

Step 6. Create analysis-ready time groupings.

Build calculated columns for meaningful business periods using formulas like =IF(HOUR(B2)>=6,IF(HOUR(B2)<12,"Morning","Afternoon"),"Night") to group hours into business-relevant time ranges.

Build the foundation for time-based insights

This timestamp extraction creates the foundation for all subsequent hourly ticket analysis, transforming HubSpot’s raw date data into actionable time-based insights. Start extracting your timestamp data today.

How to extract HubSpot deal data for MRR calculations in external spreadsheets

HubSpot’s native reporting can’t handle the complex MRR calculations that subscription businesses need. You can see deal amounts and close dates, but calculating expansion MRR, contraction rates, and rolling revenue metrics requires formulas that HubSpot simply doesn’t support.

Here’s how to extract your HubSpot deal data into spreadsheets where you can build the sophisticated MRR calculations your business actually needs.

Extract live deal data for custom MRR formulas using Coefficient

Coefficient connects your HubSpot deal pipeline directly to HubSpot spreadsheets, giving you access to all the deal properties you need for MRR calculations. Unlike HubSpot’s limited reporting, you can pull deal amounts, subscription dates, custom revenue fields, and stage information into spreadsheets where complex formulas actually work.

How to make it work

Step 1. Connect to your HubSpot deal data.

Install Coefficient and connect to HubSpot through the sidebar. Select your deal object and choose the fields you need: deal amount, close date, deal stage, subscription start/end dates, and any custom MRR properties you’ve created. Use up to 25 filters to focus on subscription deals or specific date ranges.

Step 2. Set up automatic data refreshes.

Schedule hourly or daily imports so your MRR calculations always reflect current HubSpot data. This means when new deals close or existing subscriptions change, your spreadsheet formulas automatically recalculate without manual updates.

Step 3. Build your MRR calculation formulas.

Create formulas for new MRR, expansion MRR, contraction MRR, and churn calculations using standard spreadsheet functions. For example, use SUMIFS to calculate monthly recurring revenue by grouping deals by close date and subscription type. Build rolling 12-month calculations and MRR waterfall analysis that HubSpot can’t generate natively.

Step 4. Apply formulas to new data automatically.

Enable Formula Auto Fill Down so your MRR calculations automatically apply to new deals as they’re imported. This maintains consistent calculations across your entire dataset without manual intervention every time your HubSpot data updates.

Start building better MRR insights today

Extracting HubSpot deal data into spreadsheets unlocks the MRR analysis capabilities that subscription businesses actually need. With live data connections and automated formula application, you can finally build the revenue calculations that drive real business decisions. Get started with Coefficient today.

How to extract Salesforce leads with all related activities and notes to spreadsheet

Salesforce’s native export tools can’t combine leads with their related activities, notes, and interaction history in a single export, making comprehensive lead analysis and engagement tracking nearly impossible.

Here’s how to extract leads with complete activity data in a unified format that preserves all engagement history and relationships.

Extract comprehensive lead engagement data using Coefficient

Coefficient excels at extracting leads with complete activity data through multiple approaches. You can include activity summary fields directly in lead imports, create separate activity object imports, or use custom SOQL queries to join multiple objects with proper relationship mapping.

How to make it work

Step 1. Set up your primary lead import with activity summary fields.

Connect Salesforce to your spreadsheet through Coefficient. Use “From Objects & Fields” to select the Lead object and include activity-related fields like LastActivityDate, LastModifiedDate, and any custom activity summary fields your org has created.

Step 2. Create separate imports for detailed activity objects.

Set up individual imports for Task, Event, and Note objects filtered by lead relationships. Use filters like “WhoId = Lead.Id” for tasks and events, and “ParentId = Lead.Id” for notes. This captures all activities with complete details including descriptions, dates, and outcomes.

Step 3. Import email activity and interaction history.

Create an import from the EmailMessage object to capture email interactions related to your leads. Filter by RelatedToId or other relationship fields to connect emails to specific leads and build a complete communication history.

Step 4. Use lookup fields to include activity summaries in lead data.

When setting up your lead import, include related activity information through Salesforce lookup relationships. Add fields that show the most recent activity type, last communication method, and next scheduled follow-up activities directly in your lead export.

Step 5. Set up ongoing activity tracking with scheduled refreshes.

Configure automatic refreshes to maintain current activity data and use the Append New Data feature to build historical activity logs over time. This creates a comprehensive lead engagement database that updates automatically as new activities are logged.

Build a comprehensive lead engagement database

This approach creates a complete view of lead engagement that’s impossible to achieve with standard Salesforce exports, combining current lead data with full activity history in one accessible format. Start tracking complete lead engagement today.

How to filter and identify deals with multiple company associations missing primary labels in HubSpot

HubSpot’s native reporting can’t show you association label information or filter deals based on how many companies they’re connected to, making it nearly impossible to spot problematic relationships.

You’ll learn how to export association data with labels and set up filters to automatically identify deals that need attention.

Export association data with complete label visibility using Coefficient

Coefficient gives you the association label data that HubSpot’s interface hides. You can see which associations are marked as “Primary,” “Secondary,” or have missing labels entirely, then filter this data to find exactly the deals that need cleanup.

How to make it work

Step 1. Configure your import for association visibility.

Import your deals object with company associations set to “Row Expanded” display. This creates separate rows for each company association and includes the label information (Primary, Secondary, or custom labels) that HubSpot normally keeps hidden. Each row shows the deal ID, company ID, and association metadata.

Step 2. Apply filters to identify problematic deals.

Set up multiple filters to find deals with more than one company association using deal ID counts. Then filter for associations where the label doesn’t equal “Primary” or where the label field is completely empty. You can also filter by specific date ranges if you know when duplicate associations were created.

Step 3. Create analysis formulas for deeper insights.

Use formulas in adjacent columns to count total associations per deal, flag deals missing primary labels, and identify the most recent association (which is likely the intended primary). This gives you a clear picture of which deals need immediate attention and which associations should probably be removed.

Step 4. Set up automated monitoring.

Configure scheduled imports with email alerts to notify you when new deals with multiple associations are detected. This prevents the problem from growing and lets you catch association issues as they happen rather than discovering them weeks later.

Step 5. Build your cleanup action plan.

Export the filtered results to create a prioritized list of deals that need association cleanup. Include the deal IDs, company IDs, and association types so you can take targeted action on the relationships that actually need to be removed or relabeled.

Get complete visibility into your deal associations

This approach reveals association problems that HubSpot’s standard interface simply can’t display, enabling data-driven cleanup decisions instead of manual guesswork. Start analyzing your deal associations today.