## Introduction
For marketing teams, understanding the precise origin of leads is vital for measuring campaign effectiveness and optimizing spend. Google Analytics (GA) events provide granular interaction data on user activities such as button clicks or form submissions. However, linking these events directly to lead sources—whether from Google Ads, social media, email campaigns, or organic search—can be challenging because the attribution data often lives separately from event logs.
This article guides automation engineers and marketing operations specialists through building an automated workflow that captures Google Analytics event data and enriches it with corresponding lead source information. We will leverage tools like Google Analytics, Google Sheets, and Make (formerly Integromat) to automate this data linkage, enabling marketing teams to visualize and analyze high-fidelity conversions tied back to their original traffic sources.
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## Problem Statement
When a user submits a lead form or triggers an event on your website, Google Analytics records the event but does not always tie it cleanly to the traffic source, particularly if the lead closes in a CRM or offline later. Marketing teams need a reliable way to unify event data with campaign source data for accurate attribution.
**Beneficiaries:**
– Marketing teams wanting better ROI tracking
– Automation engineers seeking to integrate GA with CRM data
– Startup CTOs who require scalable lead tracking pipelines
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## Tools and Services Integrated
– **Google Analytics 4 (GA4):** To collect event data from your website.
– **Google Sheets:** To serve as a dynamic database for lead records and source attribution.
– **Make (Integromat):** A no-code automation platform to orchestrate data retrieval, processing, and updates.
Optional:
– **Slack:** To notify marketing when key leads are captured.
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## Technical Tutorial
### Step 1: Define and Ensure Proper GA Event Tracking
Before automating, validate that your website is sending the correct event data to GA.
– Confirm that key lead interactions (e.g., form submissions, demo requests) trigger custom or recommended GA4 events — for example, `generate_lead`.
– Ensure URL parameters and UTM tags (`utm_source`, `utm_medium`, `utm_campaign`) are correctly appended and captured.
Use GA DebugView and Realtime reports to verify events and parameters.
### Step 2: Create a Google Sheet as Your Lead Source Database
Structure a Google Sheet with columns such as:
– **Lead ID** (Unique identifier, e.g., email or form submission ID)
– **Event Timestamp**
– **Event Name**
– **Source** (`utm_source`)
– **Medium** (`utm_medium`)
– **Campaign** (`utm_campaign`)
– **Additional Details** (e.g., page URL, user agent)
This sheet will serve as your working data store, aggregating and linking event data with lead sources.
### Step 3: Set Up Make Scenario to Pull GA Events
1. **Trigger:**
– Use the **Google Analytics 4 > Get Events** module to pull recent lead-related events.
– Set filters to only retrieve `generate_lead` or relevant event names.
– Schedule this to run periodically (e.g., every 15 minutes) to check for new events.
2. **Parse Data:**
– Extract relevant event parameters including timestamp and event name.
– Extract user traffic source parameters from the event properties (e.g., `source`, `medium`, `campaign`). In GA4, this may be part of the event’s user properties or session data.
3. **Lookup or Append in Google Sheets:**
– Use the **Google Sheets > Search Rows** module to check if the lead (using Lead ID or unique identifier) already exists.
– If not found, append a new row with all event and source details.
– If found, update the existing row if necessary (for example, add missing campaign data).
### Step 4: Optional – Notify Marketing via Slack
Add a Slack module to send customized messages summarizing new leads along with their source data. This keeps the marketing team informed in real time.
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## Automation Workflow Summary
1. **GA4 records event:** User generates a lead on your website.
2. **Make scenario triggers:** Periodically pulls new lead events from GA4.
3. **Process data:** Extracts lead identifiers and associated UTM/source parameters.
4. **Update Google Sheet:** Appends or updates lead records with source attribution.
5. **Optional Slack alert:** Marketing receives notifications for new high-quality leads.
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## Detailed Breakdown of Each Step/Node in the Automation
### Make Scenario Nodes
– **Google Analytics 4 > Get Events:**
– Configure with your GA4 property ID.
– Filter events to the specific lead-generating events.
– Use parameters like `startDateTime` and `endDateTime` to paginate through new data.
– **Iterator (if needed):**
– If multiple events are returned in an array, use an Iterator to process them one-by-one.
– **Google Sheets > Search Rows:**
– Searches for existing leads by unique identifiers (email, form ID).
– **Router:**
– Branches to either **Add Row** or **Update Row** depending on whether the lead exists.
– **Google Sheets > Add Row:**
– Inserts a new record with all associated data.
– **Google Sheets > Update Row:**
– Updates lead record with any new campaign or event info.
– **Slack > Send Message:**
– Formats and sends a notification message.
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## Common Errors or Tips to Make It Robust
– **Lead Identifier Matching:** Ensure your lead IDs are consistent across GA events and Google Sheets. Emails often work best, but ensure privacy compliance.
– **Event Parameter Availability:** GA4’s API might have latency or missing parameters—test your filters carefully.
– **API Quotas:** Google APIs have rate limits; batch data pulls and insertions to avoid throttling.
– **Data Deduplication:** Use unique keys for leads; consider timestamp and event parameters to avoid duplicates.
– **Error Handling:** Include error-catching modules in Make, and alert your team on failures.
– **Timezones:** Align your Google Analytics timestamps with Google Sheets timezone settings to avoid confusion.
– **UTM Parameter Persistence:** Users might navigate multiple pages or sessions — consider also capturing first user source or storing UTM parameters on the user’s session.
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## Scaling and Adaptations
– **Integrate with CRM:** Extend your workflow to push enriched lead data from Google Sheets into HubSpot, Salesforce, or any CRM.
– **Multiple Event Types:** Track other conversion events and their respective lead sources.
– **Real-time Processing:** Switch the scenario to webhook triggers or near-real-time event streaming for ultra-low latency.
– **Advanced Attribution Models:** Cross-reference user journey data to assign lead source credit more accurately.
– **Enhanced Analytics:** Automate report generation or dashboard updates using Google Data Studio connected to your Sheets data.
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## Summary
Linking Google Analytics events to lead sources bridges a critical gap in marketing attribution—providing deeper insight into which campaigns are truly generating valuable leads. By automating this process with Google Analytics, Google Sheets, and Make, marketing teams gain real-time, actionable data without manual effort. This scalable, modular workflow empowers decision makers with clarity on campaign ROI and fuels smarter marketing strategies.
With careful design around event tracking, reliable unique identifiers, and robust error handling, this automation architecture can be adapted and expanded to integrate with CRMs, reporting tools, and notification platforms.
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## Bonus Tip: Preserve UTM Parameters Using Cookies or Local Storage
Because users often lose UTM parameters when navigating deep within your site or revisiting it later, setting cookies or localStorage values to preserve initial UTM source/medium/campaign info ensures that events triggered far downstream still retain accurate lead source attribution. Implement JavaScript on your site to capture UTMs on entry and attach them persistently to user sessions, so your automation pipeline receives consistent source data for each lead event.