Category: Excel

Export HubSpot pipeline velocity metrics and conversion rates to Excel

HubSpot lacks sophisticated velocity metrics and can’t calculate conversion rates across custom time periods or deal segments. You can’t track velocity changes over time or analyze conversion by specific pipeline stages effectively.

Here’s how to export the underlying deal data needed for advanced pipeline velocity and conversion rate analysis that HubSpot’s native reporting simply cannot provide.

Calculate advanced velocity metrics and conversion rates using Coefficient

CoefficientHubSpotenables advanced pipeline velocity and conversion rate analysis by importing the underlyingdeal data needed for these calculations. You get stage change timestamps, progression history, and all deal properties required for sophisticated Excel-based velocity analysis.

This approach provides custom velocity calculations and historical conversion tracking that HubSpot’s basic reports cannot match.

How to make it work

Step 1. Import deal data with stage progression timestamps.

Pull deal data including create date, stage progression dates, close date, and deal value. Include custom properties that affect velocity like deal source, sales rep, and company size for segmented analysis.

Step 2. Import historical data using Snapshots for trend analysis.

Set up monthly snapshots to capture deal progression over time. This historical data enables velocity trending analysis and conversion rate tracking across different time periods that HubSpot cannot provide natively.

Step 3. Create Excel formulas for velocity calculations.

Build formulas to calculate days in each pipeline stage using date differences. Create average time calculations from lead to close and stage-to-stage progression times. Use formulas like =AVERAGE(Close_Date-Create_Date) for overall sales cycle length.

Step 4. Calculate stage-to-stage conversion rates.

Use COUNTIFS formulas to calculate conversion percentages between each pipeline stage. Create formulas like =COUNTIFS(Stage,”Qualified”)/COUNTIFS(Stage,”Lead”) to track conversion rates across your sales funnel stages.

Step 5. Build advanced pipeline velocity metrics.

Calculate comprehensive pipeline velocity using the formula: (Number of qualified leads × Average deal size × Win rate) ÷ Sales cycle length. Segment this calculation by deal source, rep performance, or company characteristics for detailed insights.

Get the velocity insights HubSpot can’t calculate

Start calculatingThis approach provides comprehensive pipeline velocity metrics and conversion rate analysis capabilities that exceed HubSpot’s native reporting limitations through live data access combined with Excel’s analytical power.the velocity metrics that actually drive revenue growth.

Filter Salesforce accounts by opportunity stage and amount to find net new prospects

SalesforceFinding net new prospects requires sophisticated filtering combining opportunity stage and amount criteria. This complex analysis pushesnative filtering capabilities to their limits because standard reports struggle with the multi-criteria negative logic required for effective prospect identification.

Here’s how to build superior filtering capabilities for net new prospect identification using advanced spreadsheet formulas and dynamic criteria.

Build advanced prospect filtering using Coefficient

Coefficientprovides superior filtering capabilities for net new prospect identification by combining stage progression analysis with dynamic amount thresholds and automated prospect scoring.

How to make it work

Step 1. Import comprehensive prospect data.

Use Coefficient’s “From Objects & Fields” to import accounts and opportunities with comprehensive stage and amount data. Apply initial filters for data efficiency during the import process.

Step 2. Create sophisticated stage analysis formulas.

Build formulas that identify prospects based on stage progression:

Step 3. Set up dynamic amount thresholds.

Use Coefficient’s dynamic filtering to point to cells containing minimum amount criteria. This enables easy adjustment for different prospect qualification levels without rebuilding your analysis.

Step 4. Track stage progression for high-value prospects.

Create formulas that identify prospects in specific sales stages:

Step 5. Build prospect scoring system.

Combine stage and amount criteria to create prospect scores:

Step 6. Set up automated prospect alerts.

Configure Slack or email notifications when accounts meet specific prospect criteria, enabling immediate sales follow-up on qualified opportunities.

Find better prospects with smarter filtering

SalesforceStart buildingThis filtering approach provides more accurate net new prospect identification thanstandard account filtering capabilities.better prospect identification today.

Filter Salesforce accounts that have opportunities but none closed won or with amount greater than zero

SalesforceThis specific filtering scenario highlights wherereporting hits its limits. You need accounts that have opportunities but NOT closed won deals AND NOT positive amounts – that’s complex negative logic that standard reports can’t handle well.

Here’s how to build this multi-criteria filter using spreadsheet formulas that can process the “has X but not Y” logic effectively.

Build advanced account filters using Coefficient

Coefficientexcels at this type of account-opportunity relationship analysis because you can import both datasets and use unlimited filtering complexity in your spreadsheet formulas.

How to make it work

Step 1. Import both account and opportunity data.

SalesforceUse Coefficient’sconnector to pull accounts and opportunities with all relevant fields including Stage, Amount, and Account ID. This gives you the complete dataset for analysis.

Step 2. Create your multi-criteria filtering formula.

Build a formula that identifies accounts meeting all your criteria:

Step 3. Set up dynamic amount thresholds.

Use Coefficient’s dynamic filters to point to a cell containing your minimum amount criteria. This lets you easily adjust the threshold without editing your import settings.

Step 4. Add automated alerts.

Set up Slack or email alerts when new accounts meet these criteria. This enables immediate follow-up on accounts that match your target profile.

Find your ideal prospects faster

Try itUnlike Salesforce’s cross filters which can be slow and limited, this approach gives you real-time analysis with unlimited filtering complexity.for more sophisticated account targeting.

Export HubSpot calculated properties to Excel spreadsheet via workflow automation

HubSpot workflows can’t export calculated properties to Excel files, but there’s a comprehensive solution that imports all your calculated properties and lets you perform additional calculations in Excel.

This approach offers more flexibility than workflow automation attempts while giving you enhanced calculation capabilities that HubSpot simply can’t provide natively.

Import calculated properties with enhanced Excel calculations using Coefficient

CoefficientHubSpotprovides complete support for importingcalculated properties including custom calculations, score properties, formula properties, and rollup properties, with real-time updates as your HubSpot calculations change.

You can then apply Excel’s advanced calculation capabilities to perform analysis that goes far beyond what HubSpot’s calculated properties can handle alone.

How to make it work

Step 1. Import deals with calculated properties and associations.

Connect Coefficient to HubSpot and create an import that includes your calculated properties like “Days in Pipeline” and “Deal Velocity.” Include associated objects to get complete context for your calculations.

Step 2. Set up Formula Auto Fill Down for enhanced calculations.

Create Excel formulas that build on your HubSpot calculated properties to generate pipeline conversion rates, forecasting models, and performance metrics. Use Formula Auto Fill Down to automatically extend these calculations to new rows as data refreshes.

Step 3. Schedule regular imports to keep calculated properties current.

Set up daily or hourly refreshes to ensure your calculated properties stay current as HubSpot recalculates values. This maintains accuracy for any Excel calculations that depend on these properties.

Step 4. Create alerts and advanced reporting based on calculated thresholds.

Set up Slack or email alerts when calculated metrics exceed specific thresholds. Build executive dashboards that combine multiple calculated properties and create commission calculations based on HubSpot deal scores.

Unlock advanced calculated property analysis

Start analyzingThis approach provides superior calculated property export capabilities compared to attempting workflow automation, with enhanced calculation and analysis capabilities that extend far beyond HubSpot’s native limitations.your calculated properties today.

Export HubSpot deal forecast data with probability percentages to Excel

HubSpot’s forecast reports can’t be easily exported with all probability data and deal details needed for comprehensive Excel analysis. The native forecast exports lack field selection options and become outdated immediately after download.

Here’s how to export complete deal forecast data with probability percentages for advanced Excel-based forecast analysis that HubSpot’s native tools can’t match.

Access comprehensive forecast data with probability analysis using Coefficient

CoefficientHubSpotprovides superiordeal forecast access compared to HubSpot’s limited export options. You get live access to probability percentages, weighted values, and all custom forecast-related properties in Excel.

This enables sophisticated forecast analysis including weighted pipeline calculations and historical accuracy tracking that HubSpot simply cannot provide.

How to make it work

Step 1. Import deals filtered by close date and probability ranges.

Set up imports for deals within specific forecast periods using close date filters. Include probability ranges that matter for your forecasting – typically deals above 20% probability for pipeline analysis and above 70% for commit forecasts.

Step 2. Include probability percentages and weighted values.

Select deal probability, deal amount, and any custom forecast-related properties during field selection. Also include deal stage, close date, and deal owner to enable comprehensive forecast segmentation and analysis.

Step 3. Create Excel formulas for weighted pipeline calculations.

Build formulas to calculate probability-weighted pipeline values using =Deal_Amount*Probability_Percentage. Create SUMIFS formulas to calculate weighted totals by time period, sales rep, or deal source for detailed forecast analysis.

Step 4. Set up daily refreshes for current forecast data.

Configure daily scheduled refreshes to keep forecast data current as deal probabilities and amounts change. This ensures your Excel forecast analysis always reflects the latest pipeline updates without manual re-exports.

Step 5. Use Snapshots for forecast accuracy tracking.

Enable monthly snapshots to capture forecast states for accuracy analysis over time. Compare historical forecast snapshots to actual outcomes to calculate forecast accuracy metrics and improve future forecasting precision.

Build forecasts that actually help predict revenue

Start buildingThis approach provides live access to comprehensive deal forecast data with probability percentages, enabling sophisticated Excel-based analysis that HubSpot’s native forecast tools simply cannot deliver.more accurate forecasts today.

Export HubSpot pipeline data including custom calculated fields to Excel

HubSpot’s calculated properties are restricted to basic math operations and can’t handle cross-object calculations or complex conditional logic. You’re limited by HubSpot’s calculation capabilities when you need sophisticated pipeline analysis.

Here’s how to export HubSpot custom calculated fields and extend them with advanced Excel calculations that exceed HubSpot’s limitations.

Extend calculated field capabilities using Coefficient

CoefficientHubSpotexcels at importingcustom calculated fields and enables additional Excel-based calculations that extend beyond HubSpot’s calculation limitations. You get proper formatting preservation plus the ability to create advanced formulas using associated object data.

This combines HubSpot’s custom calculated fields with Excel’s superior calculation capabilities for comprehensive pipeline analysis.

How to make it work

Step 1. Import all HubSpot custom calculated properties.

Select all custom calculated properties during field selection to ensure proper formatting preservation. Include the underlying data fields used in calculations so you can extend or modify the calculations in Excel if needed.

Step 2. Include raw data fields for additional calculations.

Import underlying data like deal amounts, dates, percentages, and associated object properties. This enables cross-object calculations and time-based metrics that HubSpot’s calculated properties cannot handle.

Step 3. Create advanced Excel calculation columns.

Build Excel formulas adjacent to imported data that use complex conditional logic, statistical functions, and cross-reference analysis. Create calculations like weighted probability scores using multiple deal and contact properties simultaneously.

Step 4. Set up Formula Auto Fill Down for new deals.

Configure Formula Auto Fill Down to automatically apply your Excel calculations to new deals added during refreshes. This ensures consistent calculation application across your entire dataset without manual formula copying.

Step 5. Use conditional formatting based on calculated results.

Apply conditional formatting, data bars, and color scales based on your calculated values. Create visual indicators for deal scoring, risk assessment, or priority ranking that update automatically with your calculations.

Break free from HubSpot’s calculation limitations

Expand your calculationsThis approach combines HubSpot’s custom calculated fields with Excel’s superior calculation capabilities, creating a comprehensive pipeline analysis system that far exceeds HubSpot’s native calculation limitations.beyond what HubSpot allows.

Export HubSpot pipeline data with associated contact and company information to Excel

HubSpot’s native exports break the connections between deals, contacts, and companies. You end up with separate files that require manual matching in Excel, losing valuable relationship context for your pipeline analysis.

Here’s how to export pipeline data with all associated contact and company information preserved in a single Excel file for comprehensive relationship analysis.

Preserve data relationships during pipeline export using Coefficient

CoefficientHubSpotexcels at handlingdata relationships through its Association Handling capabilities, which preserve complex data connections during Excel import. You get deals with their associated contacts and companies in the same rows, eliminating manual data matching.

The key advantage: you can analyze pipeline performance by contact source, company characteristics, and stakeholder engagement without complex VLOOKUP operations.

How to make it work

Step 1. Import deals with association display configured.

Select deals as your primary object and configure association display options. Choose “Primary Association” to show the main contact and company for each deal in the same row, or “Comma Separated” if you need multiple associated contacts visible.

Step 2. Select relevant contact fields for analysis.

Include specific contact properties like name, email, title, lead source, and engagement scores. These fields will appear alongside deal data, enabling analysis of how contact characteristics affect deal progression and outcomes.

Step 3. Include company fields for comprehensive context.

Add company properties such as name, industry, company size, annual revenue, and custom company scoring fields. This creates a complete picture of each deal with full stakeholder and account context in single Excel rows.

Step 4. Set up scheduled refreshes to maintain current associations.

Configure automatic refreshes to keep association data current as relationships change in HubSpot. This ensures your Excel analysis always reflects the latest contact and company connections without manual updates.

Step 5. Create relationship-based analysis formulas.

Build Excel formulas to analyze pipeline performance by contact source, company industry, or engagement level. Use SUMIFS and COUNTIFS to calculate conversion rates by company size or deal velocity by contact title.

Stop losing valuable relationship context in your exports

Preserve your data relationshipsThis unified approach provides complete HubSpot pipeline data with maintained relationships, enabling Excel analysis that would require complex manual data combining with standard exports.and unlock deeper pipeline insights.

Creating unified Salesforce reports for opportunities with specific related products and product-less opportunities

SalesforceCreating a unifiedreport that includes both opportunities with specific related products and product-less opportunities is impossible using native reporting due to cross filter logic limitations.

Here’s how to create these unified reports by extracting and consolidating Salesforce data outside of platform restrictions.

Build unified reports with comprehensive data consolidation

CoefficientSalesforceexcels at creating unified reports by extracting and consolidatingdata outside of platform restrictions. You get single comprehensive views that eliminate the need to switch between multiple reports with real-time unified analysis impossible with native reporting.

How to make it work

Step 1. Import comprehensive data with relationship mapping.

Import opportunities with all relevant fields including Name, Amount, Stage, Close Date, Account, and Owner. Import OpportunityLineItem data including Product2.Name, Product2.Family, and Quantity. Use Coefficient’s relationship mapping to maintain data connections between opportunities and products.

Step 2. Apply unified filtering logic for both scenarios.

Apply complex criteria that Salesforce cannot handle:. This unified filtering combines both opportunity types in a single query that cross filters fundamentally cannot process.

Step 3. Consolidate data with advanced spreadsheet functions.

Use spreadsheet functions to merge both datasets:. Add categorization columns:. Calculate unified metrics across both opportunity types for comprehensive analysis.

Step 4. Enable advanced unified report features.

Create segmented analysis to compare conversion rates between product-based and service-only opportunities. Build pipeline forecasting that includes all opportunity types and track revenue attribution from both specific products and services. Monitor trend analysis for changes in product vs. service opportunity mix.

Step 5. Implement automated unified reporting.

Schedule automatic data refresh to maintain unified view accuracy and set up alerts for new opportunities in either category. Create snapshots for historical unified analysis and export consolidated results back to Salesforce for team access.

Connect Salesforce Data to Spreadsheets

Get comprehensive insights impossible with separate reports

Start buildingThis unified approach transforms what requires multiple disconnected Salesforce reports into a single, comprehensive analysis tool. You’ll have cross-category metrics and comparisons not available in separate reports with streamlined reporting that reduces manual data management.your unified opportunity analysis today.

Dynamic cross-object filtering for Salesforce dashboards without creating duplicate dashboards

Salesforce dashboard filters only apply to components from the same object or related objects through lookup relationships. When objects like Opportunities, Leads, and custom Forecast objects aren’t directly related, you’re forced to maintain separate dashboards for each filter value.

You can eliminate dashboard duplication by creating a single dynamic view that filters across multiple objects instantly, without the limitations of Salesforce’s native filtering system.

Build dynamic dashboard filtering with Coefficient

CoefficientHubSpotHubSpotprovides a superior alternative for dynamic dashboard filtering across multiple objects by importing all relevant data into a single spreadsheet environment. This eliminates the need for multiple dashboards while enabling global filtering across non-related objects that share common field values inor.

How to make it work

Step 1. Import all relevant objects into one workbook.

Use Coefficient’s Salesforce connector to import Opportunities, Leads, and custom objects into separate tabs or sections of the same spreadsheet. Ensure each import includes your common filtering field like “Business Line.”

Step 2. Establish a master filter cell.

Create a dedicated cell that controls data display across all imported datasets. This becomes your central command for filtering all objects simultaneously, regardless of their Salesforce relationships.

Step 3. Apply dynamic filters to all imports.

Use Coefficient’s dynamic filters feature to reference your master filter cell from each import. This enables instant filtering without editing import settings or refreshing individual components.

Step 4. Set up dashboard-like visualizations.

Create conditional formatting and pivot tables to build visual representations of your data. These update automatically when you change your master filter selection.

Step 5. Configure automatic refresh schedules.

Set up hourly, daily, or weekly refresh cycles to maintain data currency across all objects. This ensures your unified dashboard always reflects current Salesforce data.

Step 6. Enable complex filter combinations.

Implement AND/OR filter logic to support advanced filtering scenarios. You can combine business line filtering with date ranges, ownership, or status filters across all object types.

Replace multiple dashboards with one dynamic solution

Start buildingThis approach delivers forecast dashboard consolidation while maintaining the flexibility to view all business lines or focus on specific segments. You get immediate filter updates without page refreshes or dashboard navigation, all within a single automatically updating interface.your unified dashboard solution today.

Export all Salesforce report folder sharing rules and profile assignments to CSV

Salesforce provides no direct export functionality for report folder sharing rules and profile assignments, requiring manual compilation from multiple Setup areas with no consolidated view available.

Here’s how to automate this entire export process through comprehensive SOQL queries and built-in CSV export capabilities.

Export comprehensive sharing rules automatically using Coefficient

Coefficientautomates this entire export process with comprehensive SOQL queries targeting all permission-related objects. You get single-click CSV export, automated scheduling for regular permission backups, and cross-referencing between sharing rules and profile assignments.

How to make it work

Step 1. Set up automated data extraction for sharing rules.

SalesforceConnect toand create a consolidated folder sharing rules export:

Step 2. Import profile assignment mappings.

Get user-profile relationships:. This creates the cross-reference between sharing rules and profile assignments in your unified export.

Step 3. Use Coefficient’s join capabilities for unified data.

Link sharing rules with user/profile data using VLOOKUP formulas (auto-filled by Coefficient). This creates a comprehensive dataset showing sharing rules alongside user and profile information.

Step 4. Apply filtering for specific export requirements.

Use dynamic filtering for specific folders, profiles, or date ranges. Apply conditional formatting to highlight different sharing rule types or access levels before export.

Step 5. Schedule automated exports and CSV downloads.

Set up scheduled refreshes for current data and use your spreadsheet’s native CSV export functionality for immediate download. Configure automated snapshots for historical permission tracking.

Get complete sharing rule export automation

SalesforceStart exportingThis provides complete sharing rule and profile assignment export automation thatcannot achieve natively, with scheduled backups and compliance documentation.your sharing rules automatically today.