Category: Excel

How to export HubSpot activities from free version without reports access

HubSpot’s free version blocks access to reporting features that normally allow activity exports, but you can still extract your valuable customer interaction history through API connections.

Here’s how to bypass the free tier’s export limitations and pull complete activity data into spreadsheets for analysis or migration.

Extract complete activity data using Coefficient

CoefficientHubSpot’sconnects directly toAPI to pull activity data into spreadsheets, completely bypassing the free tier’s export restrictions. This works because the API access is more permissive than the UI export capabilities.

How to make it work

Step 1. Connect your HubSpot free account through Coefficient’s sidebar.

HubSpotInstall Coefficient and authenticate youraccount. The connection uses official API endpoints, so there’s no risk of violating terms of service or triggering anti-bot detection.

Step 2. Import engagement objects including notes, calls, emails, and meetings.

Select the specific engagement types you need and apply date range filters to focus on relevant time periods. Coefficient handles API pagination automatically to capture complete datasets.

Step 3. Use filtering to focus on specific contact segments or time ranges.

Apply up to 25 filters to narrow down your activity data by contact properties, deal associations, or activity types. This helps you extract exactly what you need for your analysis or migration.

Step 4. Export the resulting data as CSV for migration or analysis.

Once your activity data is in the spreadsheet, you can format it for your target system, perform calculations, or export as CSV for use in other tools.

Get your HubSpot activity data today

Start extractingStop letting HubSpot’s free tier limitations block access to your valuable activity data. Coefficient provides a reliable way to extract complete customer interaction history with proper timestamps and contact associations.your HubSpot activities today.

How to export HubSpot parent-child company data for cleanup in external tools

HubSpotnative export functionality has significant limitations for parent-child company data extraction, lacking comprehensive field selection and proper association formatting for external analysis.

Here’s how to extract complex hierarchy data with associations intact and prepare it for advanced cleanup in external tools.

Export comprehensive hierarchy data using advanced capabilities

CoefficientHubSpotHubSpot’s basic CSV exports can’t handle complex association data or provide the filtering sophistication needed for hierarchy-specific data extraction.is specifically designed to address these limitations and provides superior capabilities for parent-child company data extraction that work seamlessly with.

How to make it work

Step 1. Set up comprehensive association exports.

Use Coefficient’s advanced import functionality to extract companies with their parent-child relationships intact. Choose from Primary Association, Comma Separated, or Row Expanded display formats to match your external tool requirements, unlike HubSpot’s flat CSV exports.

Step 2. Select hierarchy-specific fields.

Export targeted fields including Company Name, Domain, Parent Company, Number of Child Companies, custom hierarchy properties, and associated contact/deal counts. Coefficient’s field selection capabilities far exceed HubSpot’s limited export options for complex data scenarios.

Step 3. Apply advanced filtering for targeted extraction.

Use up to 25 filters across 5 filter groups to focus on specific parent-child scenarios, such as companies with broken associations, mismatched domains, or circular relationships. Create filters like “Parent Company is empty AND Company Type equals Child” to target specific cleanup needs.

Step 4. Structure data for external tool compatibility.

Export data in formats optimized for your external cleanup tools, with proper relationship mapping and hierarchical structure preservation. Include validation columns and reference IDs that HubSpot’s flat exports can’t maintain effectively.

Step 5. Set up automated export scheduling.

Create scheduled exports to maintain current data for ongoing cleanup projects, ensuring your external tools always work with fresh HubSpot data. Set up alerts when export data changes significantly or new hierarchy issues appear.

Step 6. Prepare for seamless re-import.

Structure your export to include HubSpot Object IDs and proper field mapping for easy re-import after external cleanup. Use Coefficient’s import functionality to push corrected data back to HubSpot with proper association management.

Get your data ready for advanced cleanup

Start exportingThis approach provides comprehensive data extraction and structured export capabilities that HubSpot’s native tools simply can’t deliver for complex hierarchy cleanup projects.your company hierarchy data today.

How to export Salesforce data to Excel without paid connectors

SalesforceYou can exportdata to Excel without paid connectors using native tools, but these free methods come with significant limitations that make regular reporting frustrating.

We’ll show you the available free options and introduce a streamlined alternative that eliminates the typical workarounds and technical complexity.

CoefficientExport Salesforce data to Excel using

While free native options exist, they require complex workarounds and have major limitations. Coefficient provides direct Salesforce-to-Excel integration without the multi-step processes typically required with free methods.

How to make it work

Step 1. Connect Coefficient to your Salesforce org.

Install the Coefficient add-in for Excel and authenticate with your Salesforce credentials. This one-time setup handles all the complex authentication that free methods require you to manage manually.

Step 2. Select your data source.

Choose from any existing Salesforce report, standard objects like Accounts or Opportunities, or write custom SOQL queries. Unlike free methods that limit you to bulk exports or manual report downloads, you get precise control over exactly which data you need.

Step 3. Import directly to Excel.

Your selected data appears in Excel instantly, maintaining proper formatting and structure. No CSV intermediates, no manual import steps, and no row limits beyond your Salesforce API allocations.

Step 4. Set up automated refreshes.

Schedule hourly, daily, or weekly refreshes so your Excel data stays current without any manual intervention. This automation capability simply doesn’t exist with free native methods.

Why free methods fall short

The main free options include Salesforce’s Data Export Service, manual report exports, and REST API calls through Excel Power Query. But here’s the problem: Data Export Service only provides full org exports on schedules you can’t control, manual exports require repetitive clicking for each report, and Power Query setup demands complex authentication knowledge plus SOQL expertise.

These limitations mean you’re either getting too much data (full org exports) or spending excessive time on repetitive manual tasks. Plus, authentication issues frequently break these connections, requiring constant troubleshooting.

Get your Salesforce data flowing

Try CoefficientFree methods technically work, but they create more problems than they solve for regular reporting needs.to eliminate the authentication complexity and get direct access to exactly the Salesforce data you need in Excel.

How to export Salesforce notes data when you don’t own the records

Salesforce’s standard reports only show notes you own or have explicit access to, creating blind spots when you need visibility into all opportunity-related notes across your team.

Here’s how to bypass these ownership restrictions and export comprehensive notes data using API-based extraction methods.

Export notes you don’t own using Coefficient

CoefficientSalesforce’sbypassesnative reporting restrictions by using custom SOQL queries to pull Notes data directly through the API. This approach often provides broader data visibility than standard reports because API permissions frequently exceed report-level access for Notes objects.

How to make it work

Step 1. Connect Coefficient to Salesforce and set up a custom SOQL query.

In Coefficient, select “Import from Salesforce” and choose “Custom SOQL Query.” This gives you direct API access to Notes data that may not appear in standard reports due to ownership restrictions.

Step 2. Write a SOQL query to access notes through parent object relationships.

Use this query structure:. This pulls all notes attached to opportunities you have access to, regardless of who created the notes.

Step 3. Join Notes data with Opportunity information for complete context.

Coefficient automatically handles complex joins between Notes and Opportunity records. Add fields like Parent.Name, Parent.StageName, and Parent.Amount to see notes within full opportunity context without manual data matching.

Step 4. Set up automated refresh schedules to maintain current data.

Configure hourly, daily, or weekly refreshes so your notes data stays current without manual intervention. This ensures you always have access to the latest notes from across your team.

Start accessing restricted notes data today

Get startedThis API-based approach transforms Salesforce notes from a restricted, ownership-limited dataset into comprehensive team visibility.with Coefficient to bypass notes ownership restrictions and build the reports you actually need.

How to export Salesforce report filters as metadata and import to different report type

SalesforceExportingreport filters as metadata requires using the Metadata API or tools like Workbench to extract report definitions, then manually modifying XML to match the target report type’s field structure.

This process is complex, error-prone, and often fails when field mappings don’t align between report types. Here’s a more practical approach that skips metadata manipulation entirely.

Recreate filtering logic without metadata complexity

CoefficientSalesforceprovides a more practical approach that bypasses metadata manipulation entirely by accessing yourdata directly and allowing you to recreate filtering logic through an intuitive interface.

How to make it work

Step 1. Access data directly instead of working with metadata.

Import your Salesforce data directly through Coefficient’s interface. This eliminates the need to extract, modify, and import XML metadata files that may not be compatible between report types.

Step 2. Build filter criteria using the visual filter builder.

Create complex filter criteria using AND/OR logic that supports all Salesforce field types. No metadata expertise required – just point and click to set up your filtering rules.

Step 3. Save reusable filter templates.

Save your filtering configurations within Coefficient, which can be applied to any Salesforce object or custom object regardless of report type constraints. These templates work across different data structures.

Step 4. Set up dynamic filtering with spreadsheet cells.

Use spreadsheet cells as filter parameters to create flexible templates that can be modified without reconfiguring the entire import. Change a cell value to update your filter criteria instantly.

Skip the metadata headaches

more flexibilityRather than exporting and importing metadata that may not be compatible between report types, you can recreate the same business logic for filtering data across any Salesforce objects withthan the rigid report type framework allows.

How to extract full Salesforce report data without export permissions

When your organization disables export buttons in Salesforce reports, you might consider browser console scripts to extract data. But this approach is technically complex, unreliable, and may violate security policies.

Here’s a legitimate method that bypasses disabled export buttons while maintaining security compliance and providing complete data access.

Access report data through API connections using Coefficient

CoefficientSalesforceSalesforce’sprovides controlled data access that works even whenexport buttons are disabled. The tool connects throughAPI rather than the user interface, so disabled export permissions don’t block data access.

How to make it work

Step 1. Install and connect Coefficient to your Salesforce org.

Add Coefficient to your Google Sheets or Excel environment. Connect to Salesforce using your existing credentials – you’ll need API access permissions, which are separate from UI export permissions.

Step 2. Select “Import from Existing Report” in the Coefficient sidebar.

Browse your available Salesforce reports, including those with disabled export buttons. The API connection bypasses UI restrictions while respecting your underlying data access permissions.

Step 3. Import the complete dataset directly to your spreadsheet.

Choose your target report and import all rows at once. This provides the same data you’d get from an export, but through a controlled spreadsheet connection instead of downloadable files.

Step 4. Set up audit trails and permission controls.

Use spreadsheet sharing permissions to control who can access the imported data. This provides better oversight than bulk file exports while maintaining the data access your team needs for analysis.

Get the data you need while staying compliant

Start using CoefficientThis approach addresses why organizations disable exports – preventing uncontrolled file downloads – while still enabling legitimate business analytics. You get complete report access with better security controls than traditional file exports.for compliant data access.

How to extract list of created but unused Salesforce accounts when login date filter won’t accept null values

Salesforce’s login date filters reject null values, making it impossible to extract unused accounts through standard reporting when you need to identify accounts that have never been accessed.

Here’s how to extract comprehensive lists of created but unused accounts using spreadsheet-based analysis that naturally handles empty login timestamps.

Extract unused accounts naturally using Coefficient

CoefficientSalesforceSalesforcesolves this by accepting and filtering null login dates naturally through spreadsheet-based analysis. Unlike nativefilters that won’t accept null values for login dates, Coefficient’s spreadsheet environment naturally handles empty login timestamp cells, enabling comprehensive extraction of created but unused accounts for security compliance and license optimization throughintegration.

How to make it work

Step 1. Import User object without filter constraints.

Pull all User records including Id, Username, Email, IsActive, LastLoginDate, and CreatedDate fields. This gives you the complete dataset without login date filter constraints that would exclude unused accounts from your analysis.

Step 2. Filter for created but unused accounts with timeline analysis.

Apply conditions where IsActive = TRUE AND LastLoginDate is null, then sort by CreatedDate to prioritize oldest unused accounts. Add account age calculation usingto show how long accounts have remained unused.

Step 3. Implement advanced unused account analysis.

Cross-reference with Permission Set assignments to identify high-risk unused accounts, include Profile.Name to analyze which user types are most commonly unused, and create aging buckets (30 days, 60 days, 90+ days unused) for prioritized cleanup efforts.

Step 4. Set up automated maintenance workflows.

Schedule daily imports to maintain current unused active accounts lists, configure Slack notifications when new unused accounts are created, and export cleanup recommendations back to Salesforce with specific deactivation priorities based on account age and risk level.

Extract your unused accounts today

Start extractingThis approach enables comprehensive extraction of created but unused accounts while naturally handling empty login timestamp data that standard filters reject.your complete unused account data without null value limitations today.

How to extract NPS raw data for custom segmentation analysis

Extracting raw NPS data from HubSpot typically means manual exports that become outdated quickly. You’re working with static snapshots while new survey responses continue flowing in, making your analysis stale before you finish it.

Here’s how to get direct access to raw survey response data with live connections that enable sophisticated segmentation analysis updating in real-time.

Connect directly to individual survey responses using Coefficient

Coefficientprovides direct access to raw NPS survey response data with live connections that update automatically. Instead of static exports, you get granular, current data that enables dynamic segmentation analysis as your customer base evolves.

How to make it work

Step 1. Import individual responses with complete associated data.

HubSpotHubSpot’sConnect toand import each survey response with timestamp, contact ID, actual score (0-10), and all associated contact and company properties. This gives you the granular dataset thatstandard reports aggregate away, with no volume limitations.

Step 2. Set up real-time updates with scheduled imports.

Schedule imports to refresh hourly, daily, or weekly so your raw dataset stays current as new responses are collected. This eliminates the export-refresh cycle and ensures your segmentation analysis always includes the latest customer feedback.

Step 3. Create sophisticated segmentation analysis.

Use the raw data for advanced analysis like cohort analysis by signup date, segmentation by multiple variables simultaneously (geography + product + customer tier), and custom scoring models using response patterns. The granular data enables statistical analysis that aggregated reports can’t support.

Step 4. Build dynamic segments that evolve with your data.

Create segmentation rules that automatically categorize new responses as they arrive. Set up filters and formulas that adapt to changing customer characteristics, product associations, and business segments without manual intervention.

Analyze customer sentiment with the depth your business deserves

ExtractRaw NPS data extraction enables segmentation analysis that evolves with your customer base and survey responses in real-time. You get the granular insights that drive strategic decisions instead of surface-level summaries.your raw NPS data for custom analysis today.

How to filter Salesforce reports when object has both direct and chained lookup relationships to same parent

Salesforce’s native Report Builder struggles with filtering when objects have both direct and chained lookup relationships to the same parent, creating confusion about which relationship path the filter applies to.

Here’s how to create precise filters that work correctly for each relationship path without the confusion of native report filtering.

Apply precise filtering with advanced AND/OR logic using Coefficient

Coefficient’sSalesforce’sadvanced filtering capabilities provide precise control over complex relationship filtering scenarios. You can create separate imports for each relationship path and apply specific filters to each, something impossible withstandard report filtering.

How to make it work

Step 1. Create separate imports for each relationship path.

Set up one import for the direct D→A relationship and another for the D→C→B→A chain. This allows you to apply different filtering criteria to each path based on your specific business requirements.

Step 2. Apply path-specific filters.

Filter the direct relationship based on Object A’s criteria while simultaneously filtering the chained relationship based on different criteria from the intermediate objects. Use AND/OR logic to create complex filtering conditions for each path.

Step 3. Set up dynamic filters for interactive control.

Use dynamic filters that point to cell values in your spreadsheet. This enables interactive filtering that users can adjust without editing import settings, particularly powerful when filtering the same parent object differently based on relationship path.

Step 4. Write custom SOQL for ultimate filtering flexibility.

Create WHERE clauses that explicitly handle the logic for multiple relationship paths. For example: WHERE (Direct_Parent__c = ‘Value1’) OR (Intermediate__r.Parent__c = ‘Value2’) allows conditional filtering based on which relationship path contains data.

Step 5. Combine filtered data intelligently.

SalesforceUse spreadsheet formulas to merge your separately filtered relationship paths. Apply business logic that determines which relationship path takes precedence when both contain data for the same parent object in.

Get the filtered data you actually need

Start using CoefficientThis approach eliminates the confusion and limitations of standard Salesforce report filtering when dealing with complex relationship structures.to create filters that actually work the way you need them to.

How to filter Salesforce users with null login dates when date picker is mandatory

Salesforce’s native reporting forces you to select date ranges for LastLoginDate filters, which automatically excludes users who have never logged in since they have null login dates.

Here’s how to bypass this limitation and identify active users with no login history using direct data access.

Access user data without date picker constraints using Coefficient

CoefficientSalesforceeliminates the mandatory date picker problem by connecting directly to yourdata through API calls rather than the constrained reporting interface. This gives you complete access to User object data, including records with null login dates that standard reports can’t capture.

How to make it work

Step 1. Import User object data directly.

SalesforceIn, select “From Objects & Fields” and choose the User object. Include fields like Id, Username, IsActive, LastLoginDate, CreatedDate, and Profile.Name. No date picker will appear since you’re accessing raw object data.

Step 2. Apply null login date filters.

Use Coefficient’s advanced filtering with “LastLoginDate is blank” condition combined with “IsActive = TRUE” to identify active users who have never logged in. This filtering happens in your spreadsheet environment, which naturally handles empty cells.

Step 3. Use custom SOQL for complex queries.

For more control, write a custom query:. This bypasses all UI limitations entirely.

Step 4. Set up automated monitoring.

Schedule daily refreshes to track unused active accounts for security compliance. You can also create formulas liketo categorize users automatically.

Start tracking unused accounts today

Get startedThis approach gives you complete visibility into active users with null login dates while eliminating the date picker constraints that block native Salesforce reporting.with Coefficient to access your full user data without limitations.