Why did Google Analytics clicks drop after moving email platforms?

Key findings

• Bot filtering claims: Some email platforms claim to filter or 'scrub' bot clicks before they even reach the final landing page or Google Analytics, potentially returning a 403 forbidden error to bot-like requests.
• JavaScript execution: Many bots that click links will not execute JavaScript on the landing page, meaning they will not trigger the Google Analytics tracking code. This can lead to a discrepancy between an email platform's internal click count and GA's reported sessions.
• GA data accuracy: Google Analytics attempts to filter known bot traffic, but it may still record some sophisticated bot activity. Other factors like browser settings, ad blockers, or cookie rejections also contribute to discrepancies in GA data compared to actual clicks.
• Engagement metrics: Consistent average engagement time in Google Analytics, despite a significant drop in total clicks, might indicate that the remaining clicks are from genuinely engaged users, or that the bot traffic previously had similar engagement patterns. This does not necessarily invalidate the drop.
• Potential deliverability: A sudden drop in clicks, especially when coupled with a large segment of previously active subscribers becoming unengaged, could signal underlying email deliverability issues with the new platform.

Key considerations

• Platform differences: Each email platform has its own methodology for reporting clicks and filtering bot traffic. What one platform counts as a click, another might dismiss. This is a common cause of data differences. For more information, read our article on why marketing automation platform switches can affect deliverability.
• Blocking legitimate bots: Blocking all bot-like activity with a 403 error may impede legitimate security scanners or pre-fetching by inbox providers, which can negatively impact your sender reputation and inbox placement. This could be a reason for why clicks are declining.
• Tracking configuration: Ensure that your Google Analytics tracking code is correctly implemented on all landing pages and that there are no issues with URL tagging or redirects from the new email platform. For a detailed guide on tracking email clicks in GA, refer to this Google Analytics email tracking guide.
• Investigate disengaged subscribers: A large number of previously active subscribers showing no engagement on the new platform should prompt a deeper investigation into inbox placement and deliverability for those segments. This may indicate emails are not reaching the inbox for these users.
• Data discrepancies: Be aware that data discrepancies between email platforms and Google Analytics are common. It is vital to understand the underlying causes rather than simply accepting a drop as 'bot filtering'. This Optimize Smart article explains common Google Analytics click discrepancies.

Key opinions

• Platform filtering methods: Marketers believe it is unlikely that email platforms completely 'block' bot traffic. Instead, they likely filter internal analytics based on HTTP headers (like user agent or ASN) to not log bot activity.
• GA bot interaction: A common opinion is that bots often do not run JavaScript on landing pages. If the bot does not run JavaScript, it won't load the Google Analytics tracking code, leading to fewer reported clicks in GA.
• Discrepancy validation: A 50% drop in clicks, even if partially due to bot filtering, is considered significant enough to warrant a detailed investigation, as it could indicate other issues beyond just cleaner data.
• Impact of 403 errors: There's concern that blocking bots with a 403 forbidden error, particularly those checking for malware or phishing, could negatively impact deliverability and sender reputation.
• Deliverability indicators: Finding a large segment of previously active subscribers (e.g., 9,000) who are no longer engaging after a platform switch strongly suggests a deliverability problem, regardless of bot filtering claims.

Key considerations

• Questioning platform explanations: Marketers should press their new email platforms for detailed explanations on how bot clicks are being filtered and what exactly causes a 403 error for some clicks.
• ISP-level analysis: If possible, breaking down clicks and engagement by ISP (Gmail, Yahoo, etc.) can provide valuable insights into where deliverability issues or bot filtering might be having the greatest impact. This can help troubleshoot why Gmail click rates dropped.
• Holistic view of data: Relying solely on one data point like GA clicks after a platform migration can be misleading. Marketers should compare data from various sources and look for patterns. For more on this, check out this article on why Google Analytics is inaccurate.
• Review email program health: If clicks have dropped but open rates remain, it suggests emails are landing in the inbox but something is preventing the click from being recorded or the link from being attractive. This could be a tracking issue or a content problem. Our guide on how to increase email click-through rate provides helpful steps.
• Consider the whole subscriber journey: The existence of 9,000 previously active subscribers who are now unengaged suggests that the issue might be broader than just bot filtering. It could indicate that emails are no longer reaching these subscribers' inboxes at all due to deliverability challenges stemming from the platform migration. This could lead to a sudden drop in email open rates for some segments, even if overall numbers appear stable.

Key opinions

• Bot traffic importance: Experts stress that a significant portion of what is perceived as 'bot traffic' comprises legitimate security scanners and link pre-fetching by mailbox providers. These automated interactions are essential for inbox placement and security checks.
• Risks of aggressive blocking: Blocking legitimate bots (e.g., with 403 errors) can be detrimental to sender reputation and deliverability, as it might signal problematic content or non-compliance to receiving mail servers.
• Impact of platform changes: A new email platform introduces changes in IP addresses, sending infrastructure, and potentially tracking domains. These changes can affect how mailbox providers perceive your mail and how clicks are recorded.
• Deliverability as a cause: When open rates remain consistent but clicks drop, experts often suspect deliverability issues. This could mean emails are landing in less prominent folders or that initial pre-fetching activity is occurring, but actual user engagement is reduced.
• Google Analytics limitations: Google Analytics data is influenced by client-side factors like JavaScript execution, ad blockers, and cookie consent, making it inherently imperfect for reflecting all email clicks. It's a measure of web sessions, not raw link clicks.

Key considerations

• Audit tracking setup: Verify that all Google Analytics tracking codes, UTM parameters, and any intermediate redirects from the new email platform are correctly configured and working as expected. Inaccurate tagging can lead to 'unassigned' traffic in GA4, as explained by Analytics Mania.
• Monitor sender reputation: After a platform migration, closely monitor your domain and IP reputation using tools like Google Postmaster Tools. A drop in reputation can lead to emails landing in spam, thus reducing actual clicks. Our guide to improving domain reputation can assist.
• Analyze deliverability metrics: Beyond open and click rates, examine other deliverability metrics like bounce rates, spam complaint rates, and inbox placement across different ISPs. An increase in bounces or complaints on the new platform can indicate issues. Read our article on email deliverability issues.
• Warm-up period consideration: New IPs and sending domains require a proper warm-up period to build reputation. A sudden shift to a new platform without a gradual warm-up can cause deliverability disruptions, impacting clicks.
• Review subscriber engagement: The observation of 9,000 previously active subscribers becoming unengaged is a critical data point. Investigate if these users are simply not receiving emails or if something about the new platform is deterring their engagement post-delivery.

Key findings

• GA bot exclusion: Google Analytics documentation states that GA uses filters to exclude known bot and spider traffic based on specific rules and exclusion lists. However, it also acknowledges that not all bot traffic can be perfectly filtered.
• Client-side tracking reliance: Google Analytics largely relies on client-side JavaScript execution to collect data. If a click does not result in a browser loading the landing page and executing the GA code (e.g., due to a 403 error or non-JS bot), it won't be recorded.
• Measurement protocol: The Google Analytics Measurement Protocol defines how hits are sent to GA servers. Proper configuration of client IDs and event parameters is critical for accurate data, especially when dealing with custom tracking or redirects.
• URL redirect complexity: Email click tracking often involves multiple redirects, where the email platform acts as an intermediary. Each redirect layer presents an opportunity for data modification or filtering before the user reaches the final URL with GA tracking.
• Traffic classification: Standards and research papers highlight the difficulty in precisely classifying all web traffic as human or bot, as bot sophistication continues to evolve, making comprehensive filtering a moving target.

Key considerations

• Review GA implementation: Refer to Google Analytics documentation to ensure that your GA tracking is correctly installed across all pages your emails link to, especially after a platform migration. Verify no scripts are broken.
• Understand bot filtering: Consult documentation from both your old and new email platforms regarding their specific methods for handling and reporting on bot clicks. Different filtering logic will naturally lead to different reported numbers.
• UTM parameter consistency: Ensure that UTM parameters for campaign tracking are consistently applied and formatted across all email links. Any change or error in these parameters can cause traffic to be miscategorized or appear as 'unassigned' in Google Analytics.
• Redirect chain analysis: Investigate the full redirect chain for your email links. Tools that show HTTP headers and redirects can reveal if the new platform is indeed returning 403 errors to certain traffic before it reaches your site, impacting GA data. For discrepancies in GA, this Optimize Smart article provides context.
• Data collection discrepancies: Familiarize yourself with common reasons for discrepancies between data sources, as outlined in Google Analytics help documentation. These often include user privacy settings, ad blockers, and differences in how clicks and sessions are defined. Our guide on why your deliverability rate is wrong covers hidden factors.