Category: HubSpot

Export HubSpot contacts to sort by company and surname in spreadsheets

Manual exports from HubSpot let you sort in spreadsheets, but the data becomes outdated immediately and requires constant re-exporting. There’s a better way to get live, automatically sorted contact data without the manual work.

Here’s how to maintain dynamic contact sorting that stays connected to HubSpot in HubSpot without manual exports.

Skip exports and get live sorted data using Coefficient

Coefficient elevates the export process by maintaining a live connection for custom property sorting with automatic updates. Your data refreshes on schedule while preserving your multi-level sort order.

How to make it work

Step 1. Set up live data import instead of manual exports.

Connect directly to HubSpot through Coefficient without manual exports. Import contacts with all properties including custom company fields, and your data refreshes automatically on your chosen schedule.

Step 2. Implement multi-level sorting on live data.

Select your data range (excluding headers) and access your spreadsheet’s sort function. Set your primary sort to Company property (A→Z) and secondary sort to Last Name (A→Z). New contacts automatically appear in the correct sort position when data refreshes.

Step 3. Configure automatic synchronization.

Set your refresh schedule to hourly, daily, or weekly based on your needs. Unlike static exports, deleted contacts are removed automatically and new contacts appear in the correct sorted position without manual intervention.

Step 4. Add enhanced functionality beyond basic exports.

Apply filters before import to work with specific segments, use dynamic filters linked to cells for flexible criteria, and add calculated fields that update with each refresh. Create multiple sorted views in different sheets for various organizational needs.

Step 5. Enable two-way sync capabilities.

Update contact properties based on sorted groupings, push sorted contacts to HubSpot lists, and manage associations while maintaining sort order. This bi-directional capability means you can act on your sorted data within HubSpot.

Transform static exports into dynamic organization

This approach eliminates manual export work while giving you live, automatically sorted contact data that stays current without intervention. Start building your dynamic contact organization system today.

Export recurring activities and meeting series data with original and updated details

Recurring activities and meeting series in HubSpot often change over time, but tracking both the original scheduling details and subsequent updates requires more sophisticated data capture than native exports provide.

Here’s how to maintain complete historical records of recurring activities while accessing current meeting information.

Track recurring activity changes using Coefficient

Coefficient’s snapshot functionality combined with comprehensive field selection lets you preserve historical versions of recurring activities while maintaining current data access through HubSpot integration.

How to make it work

Step 1. Create comprehensive Activities import.

Set up an Activities import in HubSpot with all recurring meeting fields including series information, recurrence patterns, and modification history. Select both standard and custom fields that track meeting series data.

Step 2. Configure scheduled snapshots for historical preservation.

Enable daily or weekly snapshots of your activity data to capture historical versions before they’re updated. This creates a permanent record of original recurring meeting details even as the series evolves.

Step 3. Set up regular import refreshes.

Schedule your main Activities import to refresh regularly (daily or weekly) to capture current meeting details and any changes to recurring series. This maintains real-time access to updated information.

Step 4. Include series-specific fields.

Select fields like “Meeting Series ID,” “Recurrence Pattern,” “Original Start Date,” “Series Status,” and any custom recurring meeting properties that track series modifications and scheduling changes.

Step 5. Create change tracking formulas.

Use spreadsheet formulas to compare current import data with historical snapshots, identifying when recurring activities were modified. This helps track the evolution of meeting series over time.

Step 6. Set up alerts for recurring activity changes.

Configure notifications when recurring activities are modified, helping you stay aware of changes to important meeting series and maintain accurate historical records.

Maintain complete recurring activity history

This approach provides both real-time access to current recurring activity data and comprehensive historical tracking of how meeting series evolved over time. Start tracking your recurring activity changes today.

Extract company-specific deal and fee data from HubSpot for client reporting

You can extract company-specific deal and fee data from HubSpot for client reporting by using advanced filtering and association management to isolate relevant data and perform complex fee calculations.

This method transforms raw HubSpot data into polished, client-ready reports with automated calculations and professional formatting.

Pull targeted deal and fee data using Coefficient

Coefficient provides robust HubSpot data extraction capabilities specifically designed for company-specific metrics. You can import deals with custom field selection including fee structures, apply company-based filtering, and leverage association management to link deals to companies and related objects.

How to make it work

Step 1. Set up company-filtered deal imports with fee data.

Use Coefficient’s object import to pull deals with custom field selection including fee structures and commission data. Apply company-based filtering using up to 25 filters across 5 filter groups to isolate specific client data. Import deal line items for detailed fee breakdowns when needed.

Step 2. Configure automated calculations and associations.

Leverage Association Management to link deals to companies, contacts, and related objects for comprehensive reporting. Use Formula Auto Fill Down to automatically calculate commission, margins, and fee totals as new data arrives. Set up dynamic filtering that points to specific spreadsheet cells for flexible company selection.

Step 3. Implement advanced search and scheduling features.

Use the HubSpot Search Formula (=hubspot_search) to find deals with complex filter logic like “company=X AND deal_stage=Y” for precise data extraction. Set up scheduled snapshots to capture monthly or quarterly fee data for historical analysis while maintaining live data updates.

Transform raw data into client-ready reports

This approach eliminates manual export processes while providing real-time data that arrives formatted for immediate sharing with external stakeholders. Clients receive comprehensive deal and fee analysis they can easily understand and act upon. Start extracting company-specific HubSpot data for professional client reporting.

Filter HubSpot reports by company property for external stakeholder sharing

You can filter HubSpot reports by company property for external stakeholder sharing by using advanced filtering capabilities that isolate data before it reaches your reports, eliminating security concerns.

This approach transforms HubSpot’s limited external sharing capabilities into a robust, secure system for stakeholder reporting with professional presentation.

Apply company property filtering using Coefficient

Coefficient’s advanced filtering capabilities specifically address HubSpot reporting permissions challenges for external stakeholder sharing. You can use up to 25 filters with AND/OR logic to isolate data by company properties, apply dynamic filters that reference spreadsheet cells, and combine company filters with date ranges and custom field values.

How to make it work

Step 1. Set up property-based filtering with dynamic references.

Configure filters to isolate data by company properties using up to 25 filters with AND/OR logic. Point filter values to spreadsheet cells containing company names, IDs, or custom properties for flexible report generation. Combine company filters with date ranges, deal stages, and custom field values for precise data isolation.

Step 2. Implement advanced filtering with HubSpot Search Formula.

Use the HubSpot Search Formula like =hubspot_search(“deals”, “Company=ClientA AND Deal_Stage=Closed Won”) for complex filtering logic. Apply association filtering to filter across related objects such as deals associated with specific companies. Create dynamic filters by referencing cells containing company information for flexible report generation.

Step 3. Configure automated sharing and security features.

Set up scheduled refreshes to ensure stakeholders always have current data while maintaining complete data isolation. Use Snapshots to preserve historical reports for compliance and auditing. Share reports through spreadsheet permissions where each stakeholder receives precisely the data they need without CRM access requirements.

Secure your external stakeholder reporting

This solution provides granular control and audit trails while eliminating the need for expensive HubSpot licenses for external users. Stakeholders receive professional, clean spreadsheet reports instead of complex CRM interfaces. Transform your HubSpot external sharing capabilities today.

Generate company-level HubSpot reports with restricted data visibility

You can generate company-level HubSpot reports with restricted data visibility by creating true company-level data isolation that prevents users from accessing unauthorized information while maintaining professional reporting capabilities.

This approach transforms HubSpot’s broad data access model into a secure, restricted reporting system suitable for external stakeholders and sensitive company-specific metrics.

Implement true data isolation using Coefficient

Coefficient directly addresses HubSpot’s limitation in providing restricted data visibility by creating complete company-level data isolation. Native HubSpot lacks granular company-level permission controls, and view-only access still allows navigation to unauthorized data, but Coefficient provides granular filtering and dynamic access control.

How to make it work

Step 1. Configure granular filtering and access controls.

Use up to 25 filters across 5 filter groups to isolate specific company data completely. Point filters to spreadsheet cells containing authorized company IDs for dynamic access control. Control which related objects (contacts, deals, tickets) are visible per company and choose specific HubSpot fields to import while hiding sensitive information.

Step 2. Implement advanced search and conditional filtering.

Use the HubSpot Search Formula like =hubspot_search(“deals”, “Company_Name=AuthorizedCompany”) for precise data retrieval. Apply conditional filtering using spreadsheet logic to show or hide data based on user permissions. Set up automated refresh schedules that maintain current data while preserving restrictions.

Step 3. Establish security features and audit controls.

Create complete data isolation where each company report contains only authorized data, eliminating the need for HubSpot login credentials. Implement audit trails to track report access and modifications through spreadsheet permissions. Use Snapshot Archiving to create historical reports with consistent visibility restrictions for compliance.

Secure your company-level reporting

This solution provides true data isolation and professional presentation without CRM complexity while offering cost-effective reporting that eliminates additional HubSpot licenses. Each stakeholder sees only their authorized company data with automated distribution. Transform your HubSpot reporting permissions today.

How much time does it take to build and maintain a Python lead scoring model vs HubSpot manual scoring

Choosing between manual HubSpot scoring and custom Python models means weighing time investment against accuracy gains. Manual scoring takes 200-400 hours annually, while Python development requires 110-180 hours upfront plus ongoing maintenance.

Here’s a detailed breakdown of time requirements and a powerful alternative that delivers most ML benefits without the development overhead.

Time investment comparison and a faster alternative using Coefficient

Manual HubSpot scoring requires 4-8 hours for initial setup, then 2-5 minutes per lead with 10-15 hours monthly maintenance. For 1,000 leads per month, you’re looking at 200-400 hours annually. Python models need 110-180 hours for initial development (data extraction, feature engineering, model building, deployment) plus 10-20 hours monthly maintenance, totaling 230-420 hours in the first year.

Coefficient offers a middle-ground approach using spreadsheet-based scoring that delivers 80% of Python model benefits with just 8-16 hours initial setup and 32-64 hours annually including maintenance.

How to make it work

Step 1. Import all HubSpot contact data and engagement metrics.

Connect HubSpot to your spreadsheet and pull contact properties, engagement data, and behavioral metrics. This takes 30 minutes compared to 20-40 hours of API development for data extraction.

Step 2. Build scoring logic with spreadsheet formulas.

Create weighted scoring formulas using familiar functions:. Test different weighting approaches quickly without coding, iterating on your scoring logic in real-time.

Step 3. Test and refine your scoring model.

Use historical conversion data to validate your scoring approach. Create pivot tables to analyze score distribution and conversion rates by score range. Adjust weights based on actual performance data from your sales team.

Step 4. Automate score updates to HubSpot.

Push calculated scores back to HubSpot custom properties automatically. Schedule daily or weekly updates so your sales team always has current lead scores without manual intervention.

Step 5. Monitor and optimize performance.

Track which leads convert and adjust your scoring formulas accordingly. Set up alerts when high-scoring leads don’t convert or when low-scoring leads become customers, indicating your model needs refinement.

Choose the right approach for your team

Manual scoring works for small volumes but doesn’t scale. Python models offer maximum accuracy but require significant technical investment. Coefficient-powered spreadsheet scoring delivers advanced lead scoring capabilities with minimal time investment, perfect for teams who need better than manual scoring without full ML development. Try Coefficient free and build your scoring model today.

How to aggregate event and content campaign data into single performance dashboard

HubSpot treats event campaigns and content campaigns as separate entities with different properties and metrics. Native dashboards cannot easily combine these campaign types into a single, cohesive view with normalized metrics for true performance comparison.

Here’s how to create unified campaign dashboards that aggregate both event and content performance into comparable metrics.

Build unified campaign performance dashboards using Coefficient

The solution involves importing both campaign types separately, then normalizing their metrics for unified analysis. Coefficient handles the data transformation and aggregation that HubSpot can’t perform natively, creating true cross-campaign visibility.

How to make it work

Step 1. Create separate imports with standardized field selection.

Set up separate imports for event campaigns and content campaigns from HubSpot . Standardize field selection to include common metrics like Name, Type, Start date, Impressions, Conversions, and Revenue. Add a custom “Campaign Category” column to distinguish between event and content types.

Step 2. Implement data normalization process.

Map different metric names to unified columns (for example, “Attendees” for events equals “Engaged Users” for content). Create calculated fields for comparable metrics across types. Use IF statements to handle type-specific calculations and ensure consistent measurement.

Step 3. Build aggregated performance metrics.

Create a master dashboard combining both data sources. Calculate unified conversion rates using this formula: Conversions / (Impressions or Registrations). Create weighted performance scores that account for campaign type differences and business impact.

Step 4. Set up continuous data aggregation.

Use Append New Data to continuously build a unified campaign database. Apply consistent date ranges across both campaign types. Set up automated data refresh schedules to keep your dashboard current with the latest HubSpot data.

Step 5. Create cross-campaign analysis capabilities.

Compare event vs content campaign effectiveness using normalized metrics. Track total marketing impact across all campaign types. Identify optimal campaign mix by business unit and time period for strategic planning.

Step 6. Build a structured dashboard layout.

Organize with separate sheets for event campaign imports, content campaign imports, unified metrics table with normalized data, and visualization layer with combined performance charts, campaign type comparisons, and trend analysis over time.

Get complete campaign visibility

Aggregating event and content campaigns into unified dashboards reveals performance patterns that individual campaign reports miss. This comprehensive view enables better resource allocation and strategic decision-making across all campaign types. Start building your unified campaign dashboard today.

How to aggregate sequence engagement data by associated campaign in HubSpot reports

Aggregating sequence engagement data by campaign in HubSpot’s native reporting is impossible due to the event data source limitation. You can’t combine sequence metrics with campaign associations in a single report.

Here’s how to create powerful aggregation capabilities that solve this challenge completely and give you the campaign-based sequence insights you need.

Build comprehensive sequence engagement aggregation using Coefficient

Coefficient enables the data aggregation that HubSpot simply can’t provide. You can import comprehensive data sets and create custom aggregation frameworks that deliver insights impossible with native reporting.

How to make it work

Step 1. Import comprehensive engagement data.

Pull sequence engagement metrics (opens, clicks, replies, meetings booked) and campaign association data for all contacts from HubSpot . Include contact properties to enable multi-dimensional analysis across different segments.

Step 2. Create your aggregation framework.

Import sequence enrollments with contact IDs, then import campaign associations with contact IDs. Use SUMIF and COUNTIF formulas to aggregate sequence data by campaign, then build pivot tables for dynamic aggregation views.

Step 3. Build custom metrics HubSpot can’t provide.

Calculate average reply rate per sequence grouped by campaign, total meetings booked from sequences by campaign source, engagement velocity (time to reply) segmented by campaign, and revenue attribution from sequence conversions by campaign.

Step 4. Implement dynamic filtering.

Point filters to spreadsheet cells for real-time campaign selection, create dropdown menus to switch between campaign views instantly, and build date range filters for time-based performance analysis.

Step 5. Set up automated refresh and alerting.

Schedule hourly imports from HubSpot to keep aggregated data current, set up Slack alerts when sequence performance exceeds campaign benchmarks, and create email notifications for significant changes in engagement rates.

Transform raw data into actionable campaign insights

This solution converts raw HubSpot data into actionable insights with aggregation capabilities that far exceed native reporting limitations. Start building the cross-object sequence reports you need today.

How to automate monthly metrics reports to management using free solutions

Automating monthly metrics reports eliminates the repetitive manual work that typically consumes days at month-end, transforming a 16-24 hour monthly task into a 30-minute review process.

You’ll learn how to create a completely hands-off monthly reporting system that delivers consistent, accurate performance metrics to management without manual intervention.

Build fully automated monthly reporting using Coefficient

Coefficient excels at monthly metrics automation by combining scheduled data imports with automated alerts and snapshots. You can create a complete hands-off system that pulls data from HubSpot and other sources, performs calculations, and distributes reports automatically each month.

How to make it work

Step 1. Configure automated data collection.

Schedule imports for the 1st of each month at 12:01 AM to pull prior month’s complete data from all connected sources. Use date-based dynamic filters like “Date = LAST_MONTH()” to automatically capture the correct time period, and set up multiple data source connections for comprehensive monthly reporting.

Step 2. Structure your automated report template.

Create separate tabs for Executive Summary with auto-calculated KPIs, Sales Performance metrics from your CRM, Financial Dashboard from accounting systems, Operational KPIs from project management tools, and Historical Trends using the Snapshots feature for month-over-month comparisons.

Step 3. Build automated calculations and insights.

Set up formulas for month-over-month growth percentages, quarterly rolling averages, year-to-date accumulations, and variance analysis against budgets. Create dynamic commentary using formulas like =IF(B2>B1,”Revenue increased by “&TEXT((B2-B1)/B1,”0%”)&” this month”,”Revenue decreased by “&TEXT((B1-B2)/B1,”0%”)&” this month”).

Step 4. Configure monthly snapshots and distribution.

Set Coefficient to capture snapshots on the last day of each month to preserve historical data for trend analysis. Configure email alerts to send “Monthly Report Ready” notifications with direct Google Sheets links, and set up conditional processing to only send reports when all data sources have updated successfully.

Step 5. Add data quality checks and backup processes.

Include automated flags for incomplete data, create data quality validation formulas, and set up backup notification systems. Use Google Apps Script for automated PDF generation if needed, and configure Slack integration to post key metrics to management channels.

Transform your monthly reporting process today

Automated monthly reporting saves 200+ hours annually while ensuring management receives consistent, accurate performance metrics without delays or manual errors. Start building your automated monthly reporting system with Coefficient’s free platform.

How to automatically export form submissions to Google Sheets every week

You can automatically export form submissions from HubSpot to Google Sheets every week using scheduled data imports. This eliminates manual downloads and keeps your sales team working with fresh data.

Here’s how to set up a weekly automated export that runs in the background and delivers updated form submission data directly to your spreadsheet.

Set up weekly automated form exports using Coefficient

Coefficient creates a live connection between HubSpot and Google Sheets, allowing you to schedule weekly imports that pull form submission data automatically. Your sales team gets direct access to updating data without any manual export steps.

How to make it work

Step 1. Connect Coefficient to your HubSpot account.

Install Coefficient from the Google Workspace Marketplace, then open your Google Sheet and click the Coefficient sidebar. Select “Connected Sources” and add your HubSpot account through the authentication process.

Step 2. Create an import for your form submission data.

Click “Import from” in the Coefficient sidebar and select HubSpot. Choose “Contacts” as your object since form submissions create contact records. Select the fields you need like name, email, company, form name, and submission date.

Step 3. Apply filters to capture only form submissions.

In the filter section, add conditions to focus on form data. Filter by “Original Source” equals “Organic Search” or “Form submission” depending on your setup. You can also filter by specific form names or submission date ranges.

Step 4. Schedule the import for weekly refresh.

Click “Import Settings” and select “Schedule.” Choose “Weekly” and pick your preferred day and time (like Monday mornings at 8 AM). Enable “Append New Data” if you want to preserve historical submissions alongside new ones.

Step 5. Share the sheet with your sales team.

Use Google Sheets’ sharing settings to give your sales team access to the automatically updating data. They’ll see fresh form submissions after each weekly refresh without any manual work from you.

Start automating your form data today

Weekly automated exports save hours of manual work while ensuring your sales team always has access to the latest form submissions. Get started with Coefficient to eliminate manual exports and keep your data flowing automatically.