How to track clicks from emails in Google Analytics:
How to track clicks from emails in Google Analytics:

It’s essential to track clicks from emails in Google Analytics to be able to measure the performance of your email campaigns. However, email clicks are also an important step in most sign-up and password reset journeys.
Many off-the shelf solutions, such as Mailchimp, allow for automated integration with Google Analytics and so all clicks from emails are captured without any need to change email calls-to-actions. But many in-house email platforms and CRM solutions don’t automatically integrate with analytics solutions.
That’s why it’s worth checking if Google Analytics track clicks from emails from your company email campaigns. When I refer to ‘campaign’, I’m including registration and email password reset emails. These are often overlooked as this is perceived to be a process rather than a campaign that requires tracking.
1. How do you check if your tracking email clicks?
If your marketing or operations teams have already added the required parameters to your organisation’s emails you should see the evidence in the Acquisition>All Traffic>Channels tab on the left of the GA console. ‘Email’ should appear as a channel grouping.
However, you will also need to see which campaigns are tracking. Go to Acquisition>Campaigns>All Campaigns and if your email clicks are being tracked you should see the number of users for each separate campaign. If some or none of your campaigns are visible. You need to reach out to the email team to resolve the problem.
2. Adding campaign parameters to email CTA:
The process of tracking clicks from emails is a fairly simple process. All you need to do is add certain parameters to the URLs that are embedded into your buttons and links in your emails. Google has a campaign URL builder for you to use. Just enter the URL for the page users are being sent to, the campaign source (e.g. registration), campaign medium (e.g. email) and name (e.g. validation). The other parameters (Campaign Term and Content) are for paid search campaigns and A/B testing/content-targeted ads.
For our website this generates the following URL to for the registration email: https://www.conversion-uplift.co.uk/?utm_source=registration&utm_medium=email&utm_campaign=validation
This will carry all the information for Google Analytics to identify users landing on the website because of the registration validation email. Ask your email team to use the new URL for the call-to-action in the email. Get them to send you a test email so that you can check it works.
When you get the test email. Click on the calls-to-actions and check that data shows up in the ‘Realtime’ tab of Google Analytics under ‘Traffic Sources’. This will display the ‘Medium’ and the ‘Source’.
3. How to use email campaign tracking in Google Analytics:
Now that your email campaigns are correctly tracking in Google Analytics you can use the campaign information to create customer segments. This will allow you to identify users who come from each campaign and analyse them in ‘Custom Reports’. If you use the ‘Advanced’ – ‘Sequences’ approach to creating a segment you can also use campaign data to create complex funnels in Data Studio and identify drop-off rates at each stage of the user journey.
Summary:
Don’t assume your company email platform has been integrated with your web analytics. Check in your analytics console to see if all your email campaigns are tracking.
If campaigns are not showing up in your analytics console use the Google URL builder to create suitable URLs for call-to-actions in your email campaigns. Make sure you differentiate between different campaigns using the parameters provided.
Get your email team to send you a test email so that you can validate Google Analytics is capturing the parameters correctly. Use the ‘Realtime’ >’Traffic Sources’ tab in Google Analytics to view the data.
To enable analysis and reporting of email call-to-action clicks set up customer segments in Google Analytics. You can use these to create automated funnel reports in Data Studio.
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