Category: HubSpot

How to exclude dates with no value from HubSpot report visualizations

HubSpot automatically includes all dates in your selected range, even those with no data. This creates zero values that disrupt trend lines and make sparse data visualizations difficult to interpret with no native way to exclude these empty dates.

You can filter out empty dates during import or after bringing data into spreadsheets to create cleaner, more meaningful visualizations.

Filter empty dates with advanced data controls using Coefficient

Coefficient provides multiple methods to exclude dates with no value from your HubSpot data before it reaches your HubSpot visualizations. You can filter during import or clean up data after it’s in your spreadsheet.

How to make it work

Step 1. Filter during import setup.

When configuring your HubSpot data import in Coefficient, apply filters to exclude records where key metrics equal zero or are empty. Use Coefficient’s advanced filtering with up to 25 conditions to precisely control what data enters your spreadsheet.

Step 2. Apply post-import filtering formulas.

If you need all data imported but want to exclude empty values for visualization, use these formulas:to exclude rows where column B equals zero, orfor more complex filtering conditions.

Step 3. Build dynamic visualizations that skip empty values.

Create charts using your filtered data ranges that automatically exclude empty periods. Build dynamic date ranges that adjust based on actual data presence and use Coefficient’s snapshot feature to capture only periods with meaningful data for historical analysis.

Step 4. Set up automated refresh and alerts.

Schedule Coefficient to refresh your filtered data automatically and set up alerts that notify you when new non-zero data appears. This ensures your clean visualizations stay current without manual intervention.

Build cleaner reports that show only meaningful data

Excluding empty dates creates trend lines that accurately represent your HubSpot marketing performance without the noise of zero-value periods. Start filtering your data for better insights today.

How to exclude retroactively updated deals from missed stage counts in HubSpot

HubSpot’s native funnel reports cannot exclude retroactively updated deals from missed stage counts because they’re based on historical timestamps rather than current deal status. Once a deal is marked as “missed” at a specific stage, it remains in that status even if later moved through all stages and closed won.

Here’s how to build missed stage calculations that account for retroactive updates and reflect true performance.

Create conditional missed stage logic using Coefficient

Coefficient provides precise control over missed stage calculations by enabling custom logic that accounts for retroactive updates. You can import deal data from HubSpot and build formulas that exclude deals from “missed” counts if they ultimately convert.

How to make it work

Step 1. Import deal status and history data for comprehensive analysis.

Pull HubSpot deals with Current Stage, Deal Stage History, Last Modified Date, and Close Date. Use filtering capabilities to focus on deals within your analysis timeframe.

Step 2. Build conditional missed stage logic that accounts for final outcomes.

Create formulas that exclude deals from “missed” counts if they ultimately convert. Use: =IF(AND(ISNUMBER(SEARCH(“Stage_2”, StageHistory)), CurrentStage<>“Closed Won”), “Missed”, “Converted”). This only counts deals as missed at Stage 2 if they never reached Closed Won status.

Step 3. Implement update cutoff dates for historical accuracy.

Set analysis parameters that exclude deals updated after specific dates to avoid counting deals that may still be in progress. Use =IF(LastModified>CutoffDate, “Exclude”, MissedStageFormula) to filter out recently updated deals that might skew historical analysis.

Step 4. Calculate clean conversion rates excluding retroactive updates.

Derive accurate stage conversion metrics by dividing successful progressions by total eligible deals, excluding those that were retroactively updated to successful outcomes. Formula: =SUM(Converted) / (SUM(Converted) + SUM(TrulyMissed)).

Step 5. Track retroactive update patterns for process insights.

Identify which deals were retroactively updated and analyze patterns in timing, deal characteristics, or sales rep behavior that lead to stage updates after initial “missed” classification.

Step 6. Set up automated exception handling for data quality.

Configure alerts when significant numbers of deals are retroactively updated, indicating potential process issues or data quality concerns that affect reporting accuracy.

Get clean missed stage reporting that reflects true performance

This approach provides accurate missed stage reporting that reflects true sales performance rather than data timing artifacts. Start building conditional logic that excludes retroactively successful deals from missed counts.

How to export companies from HubSpot workflow that only assigns owners without setting properties

When your HubSpot workflow only assigns owners without setting trackable properties, you can’t filter or export those companies using native reporting tools. This creates a significant data gap that makes it impossible to track which companies went through your workflow.

Here’s how to identify and export these companies by analyzing owner assignment patterns and workflow timing data.

Export workflow companies by analyzing owner assignment data using Coefficient

Coefficient solves this limitation by pulling comprehensive company data and analyzing owner assignment patterns as a proxy for workflow processing. Since HubSpot can’t filter companies by workflow enrollment, you’ll reconstruct this information through data analysis.

How to make it work

Step 1. Import company data with owner assignment history.

Connect to HubSpot and pull all companies with these key fields: Company Owner, HubSpot Owner Assigned Date, Last Modified Date, and any properties that match your workflow’s enrollment criteria (company size, industry, etc.). Apply filters to narrow down to companies within your workflow’s active timeframe.

Step 2. Create owner assignment pattern analysis.

In your spreadsheet, build formulas that identify companies where the owner assignment date aligns with your workflow’s execution period. Cross-reference these results with your known workflow trigger criteria to validate which companies likely went through the workflow.

Step 3. Set up automated tracking for ongoing monitoring.

Schedule automatic imports using Coefficient’s refresh features to capture new owner assignments as they occur. Use the Snapshots feature to preserve historical data while continuing to refresh current information, and configure alerts when new companies meet your owner assignment criteria.

Step 4. Export your identified companies back to HubSpot.

Create a custom property in HubSpot to mark workflow-processed companies, then use Coefficient’s export functionality to update these companies with a tracking property for future reference and easy filtering.

Start tracking your workflow companies today

This approach overcomes HubSpot’s workflow enrollment export limitations by leveraging owner assignment timestamps and criteria matching. You’ll finally have the company list you need without relying on non-existent enrollment history. Get started with Coefficient to begin tracking your workflow companies.

How to export HubSpot companies with IDs for Excel matching before re-import

Exporting HubSpot companies with IDs for Excel matching is crucial for preventing duplicates during re-import, but HubSpot’s native export tools have limitations with data relationships and field mapping.

You’ll learn how to export comprehensive company data with proper ID mapping and build matching workflows that enable seamless re-import without duplicate creation.

Export with advanced ID mapping using Coefficient

Coefficient provides superior export capabilities compared to HubSpot’s native tools, including automatic ID hyperlinking, live data refresh, and seamless re-import field mapping without row limits or manual configuration.

How to make it work

Step 1. Configure comprehensive company export with IDs.

Use Coefficient to export HubSpot companies including the company unique identifier (automatically hyperlinked), domains, names, phone numbers, addresses, and any custom properties needed for matching logic.

Step 2. Create Excel matching formulas using exported IDs.

Build lookup formulas to match your Excel data against exported companies: =INDEX(hubspot_ids, MATCH(excel_domain, hubspot_domains, 0)). This populates HubSpot IDs where domain matches exist.

Step 3. Build validation columns for data quality.

Create columns for match confidence scores, data quality flags, and action recommendations (UPDATE vs INSERT). Use conditional formatting to highlight potential issues before re-import.

Step 4. Execute re-import with automatic field mapping.

Since your data originated from Coefficient exports, field mapping happens automatically during re-import. This eliminates manual configuration and reduces errors compared to HubSpot’s native import process.

Eliminate re-import mapping headaches

Proper ID export and matching prevents duplicate companies while maintaining data relationships through automated field mapping. Try exporting with live data refresh and automatic ID hyperlinking instead of static HubSpot exports.

How to export HubSpot deal data for custom win/loss analysis

HubSpot’s basic data exports are static snapshots that quickly become outdated and require manual updates, making them inadequate for ongoing win/loss analysis that needs current data.

Here’s how to create live data connections that automatically update your win/loss analysis without the limitations of manual exports.

Create live HubSpot deal data connections using Coefficient

Coefficient provides a superior alternative to static HubSpot exports by creating live connections to HubSpot deal data that automatically update. This eliminates manual export work while providing more current and comprehensive data.

How to make it work

Step 1. Set up live data connection to HubSpot deals.

Instead of static exports, create live connections to HubSpot deal data that automatically update. Choose only the specific deal fields needed for your analysis like outcome, close date, amount, competitor, and sales rep information.

Step 2. Apply advanced filtering for targeted analysis.

Apply up to 25 filters to focus on specific deal segments, time periods, or criteria. Use dynamic filters that reference spreadsheet cells so you can easily adjust your analysis parameters without recreating the entire data pull.

Step 3. Schedule automatic data refreshes.

Set up automatic data updates (hourly, daily, weekly) so your analysis always reflects current deal status. This ensures your win/loss analysis stays current without any manual intervention or repeated exports.

Step 4. Preserve historical data with snapshots.

Use snapshots to maintain historical win/loss data even as deals continue to update in HubSpot. This gives you both current data and historical trends in the same analysis framework.

Move beyond static data exports

This approach eliminates the manual work of repeated exports while providing more comprehensive and current data than HubSpot’s native export functionality allows. Start building live win/loss analysis that updates automatically.

How to export HubSpot payment links with product names prices and URLs to Excel

Getting payment link data out of HubSpot with all the product details you need isn’t straightforward with native exports. You need payment link URLs, product names, prices, and associated data in one clean Excel file.

Here’s how to set up automated exports that pull complete payment link data with product associations, eliminating manual export tasks.

Export complete payment link data using Coefficient

Coefficient connects HubSpot directly to Excel, letting you pull payment links with associated product data in a single automated export. Unlike HubSpot’s native exports that require multiple steps and manual data joining, you get everything in one view.

How to make it work

Step 1. Connect HubSpot to Excel through Coefficient.

Install Coefficient in Excel and connect your HubSpot account through the “Connected Sources” menu. This creates a direct data pipeline between your CRM and spreadsheet.

Step 2. Configure your payment link import with custom field selection.

Create a new import targeting payment link objects. Select the fields you need: payment link URLs, names, status, creation dates, and any custom properties. Use the “Row Expanded” option to pull associated product data alongside each payment link.

Step 3. Map product associations to include names and prices.

Configure association handling to pull product names, SKUs, prices, and descriptions. This eliminates the need for separate product exports and manual data matching that HubSpot’s native process requires.

Step 4. Apply filters to focus on active or relevant payment links.

Use Coefficient’s filtering options to target specific payment links. Filter by status, creation date, expiration date, or associated product categories. You can apply up to 25 filters with AND/OR logic.

Step 5. Schedule automatic updates to keep your data current.

Set up hourly or daily scheduled refreshes so your Excel file stays synchronized with HubSpot changes. New payment links appear automatically, and price updates flow through without manual intervention.

Get your payment link data working for you

This automated approach saves hours of manual export work while giving you complete payment link visibility with product context. Start your free trial to set up automated HubSpot payment link exports today.

How to export HubSpot social media data to Excel when native export is unavailable

HubSpot’s native social media export options are limited, especially when you need specific performance data that isn’t readily available through standard reports. The platform stores most social media analytics in Marketing Events objects that can’t be directly exported.

But there are workarounds. You can still get your social media data into Excel if you know where to look and how to structure your data collection approach.

Export social media data through custom properties and activities using Coefficient

While Coefficient can’t access HubSpot’s native social media analytics directly, it can help you export social media data that’s stored in accessible objects like Contacts, Companies, Deals, and Activities.

How to make it work

Step 1. Set up custom properties for social media tracking.

Create custom properties on your Contacts, Companies, or Deals to capture key social media metrics. This might include engagement scores, social media source attribution, or campaign performance data that you manually input or capture through other integrations.

Step 2. Log social interactions as Activities.

Use HubSpot’s Activity feature to track social media interactions with your contacts. This creates a record that Coefficient can access and export, giving you detailed interaction history tied to specific contacts.

Step 3. Connect Coefficient to HubSpot and import your data.

Open Coefficient’s sidebar in Excel, connect to HubSpot, and select the objects containing your social media data. Use filtering options to focus on social media-related records, custom properties, or specific activity types.

Step 4. Schedule automatic refreshes for ongoing data collection.

Set up scheduled imports to automatically update your Excel file with new social media data. This builds a historical dataset over time, something HubSpot’s native tools struggle with for social media analytics.

Step 5. Apply formulas for custom calculations and trend analysis.

Use Excel’s formula capabilities to calculate engagement rates, conversion metrics, and trend analysis that HubSpot can’t provide natively. Coefficient’s formula auto-fill feature will apply these calculations to new data automatically.

Start building better social media reports

This approach gives you more flexibility than HubSpot’s limited native social media exports. You can create custom metrics, historical tracking, and detailed analysis that fits your specific reporting needs. Try Coefficient to start exporting your HubSpot social media data today.

How to extract customer health score data with timestamps from HubSpot CS space

HubSpot’s CS space blocks timestamp access for customer health score data, making it impossible to track score changes over time through native reporting channels.

Here’s how to extract timestamped health score data and build the historical tracking capabilities that HubSpot’s CS space can’t provide.

Extract timestamped health score data using Coefficient

Coefficient connects directly to HubSpot’s API to pull customer health score data with full timestamp preservation. This bypasses the CS space reporting limitations that block timestamp access in native HubSpot dashboards.

How to make it work

Step 1. Set up your HubSpot connection and import health score data.

Connect to HubSpot through Coefficient’s sidebar and select your customer health score data from the CS space. Use custom field selection to pull the specific health score metrics you need along with customer identifiers and any associated properties.

Step 2. Configure scheduled snapshots for timestamp preservation.

Set up daily or weekly snapshots using Coefficient’s snapshot feature. This captures point-in-time copies of your health score data with preserved timestamps, creating the historical dataset that HubSpot’s native reporting blocks.

Step 3. Enable automated data refresh with append functionality.

Configure your import to append new health score readings without overwriting previous data. This builds a comprehensive time-series dataset where each row includes automatic timestamp tracking for when the data was captured.

Step 4. Build time-series analysis with auto-fill formulas.

Use Formula Auto Fill Down to automatically calculate health score changes, trend velocity, and period-over-period comparisons as new timestamped data arrives. Create formulas like =B2-B1 for score changes and =(B2-B1)/B1 for percentage movements.

Start tracking health score trends today

This approach transforms HubSpot’s timestamp-blocked health score data into a robust tracking system that enables proactive customer success management. Get started with Coefficient to build the historical health score analysis that HubSpot’s CS space limitations prevent.

How to extract filtered closed won total from Salesforce report using REST API

Salesforce’s REST API can technically access report data, but it doesn’t return pre-calculated totals and requires complex SOQL queries plus custom aggregation code.

Here’s a simpler approach that gets you the same filtered closed won totals without wrestling with API limitations or authentication headaches.

Get filtered closed won totals directly in spreadsheets using Coefficient

Coefficient eliminates the need for complex REST API calls by importing your Salesforce Opportunity data directly into Google Sheets or Excel. You can apply up to 25 filters to match your report criteria exactly, then use simple SUM functions for instant totals.

How to make it work

Step 1. Connect Salesforce to your spreadsheet.

Install Coefficient and authenticate your Salesforce connection through the sidebar. This handles all the API authentication automatically so you never have to manage tokens or refresh cycles.

Step 2. Import Opportunity data with filters.

Select Opportunities as your object and choose the Amount field along with any other fields you need. Apply filters like Stage = “Closed Won” and set your date ranges using AND/OR logic to match your report exactly.

Step 3. Set up automatic aggregation.

Use a simple SUM formula on the imported Amount column to get your closed won total. The formula automatically handles null values and currency conversions that would require custom code in a REST API solution.

Step 4. Schedule automatic refreshes.

Set up hourly, daily, or weekly refreshes to keep your totals current. You can even point filter values to specific cells, so changing a date range updates your data without rebuilding queries.

Start pulling Salesforce data without API complexity

This approach gives you the same filtered closed won totals as complex REST API solutions while eliminating authentication management and custom aggregation code. Try Coefficient to streamline your Salesforce reporting.

How to extract HubSpot payment link analytics data to spreadsheet for reporting

HubSpot’s native reporting provides limited customization options for payment link analytics and struggles with cross-object analysis connecting payment links to broader sales metrics. You need flexible reporting that combines payment link performance with deal conversion and revenue data.

Here’s how to extract comprehensive payment link analytics for advanced reporting and dashboard creation.

Extract comprehensive analytics using Coefficient

Coefficient provides superior payment link analytics extraction compared to HubSpot’s native reporting limitations. You can create custom metrics, maintain historical data, and build sophisticated dashboards with real-time updates.

How to make it work

Step 1. Configure multi-object data import for comprehensive analytics.

Set up imports to pull payment link performance metrics, associated deal conversion data, contact engagement statistics, and revenue transaction details. This creates a complete view of payment link effectiveness.

Step 2. Use snapshot features for historical data preservation.

Capture monthly payment link performance baselines, track conversion rate trends over time, and preserve historical analytics for year-over-year comparisons that HubSpot reports can’t maintain.

Step 3. Build advanced reporting calculations with spreadsheet formulas.

Create payment link ROI calculations, conversion funnel analysis, product performance comparisons, and sales rep attribution metrics using Excel or Google Sheets’ calculation capabilities.

Step 4. Set up automated report generation with scheduled updates.

Schedule daily performance summaries, weekly trend analysis, and monthly comprehensive reports that update automatically as new payment link data flows from HubSpot.

Step 5. Create dynamic dashboards with real-time performance charts.

Build dashboards with real-time payment link performance charts, conversion rate tracking, and revenue attribution analysis using your spreadsheet’s visualization tools.

Unlock payment link insights

Advanced analytics extraction transforms basic payment link data into actionable business intelligence with historical context and custom metrics. Start building comprehensive payment link analytics reports today.