Why are email click rates inflated and how to solve the issue?
Summary
What email marketers say11Marketer opinions
Email marketer from HubSpot explains the importance of regularly cleaning email lists to remove inactive subscribers and potential spam traps. Maintaining a clean list helps to reduce the impact of inflated email metrics.
Email marketer from Email Uplers shares that excessively high click-through rates can stem from several sources, including internal link tracking errors, bot clicks, and incorrect campaign setups. They suggest auditing tracking parameters and segmenting bot traffic.
Email marketer from Email Geeks explains they use a mixture of different attributes around metadata to flag bot clicks, with the goal to minimize false positives.
Email marketer from Stack Overflow shares that high click-through rates may come from a faulty tracking link or a mistake in the setup. Verify link syntax and campaign configuration.
Email marketer from Email Geeks shares information on a beta feature that removes bot clicks from reporting. Users can get access by contacting Francis Baker or support.
Email marketer from Mailjet responds that Apple's Mail Privacy Protection (MPP) can inflate open rates, which indirectly impacts click-through rates. MPP loads all images by default, leading to inflated open rates that make click rates appear lower than they actually are.
Email marketer from SuperOffice shares that a high click-through rate could stem from mobile users accidentally clicking on links due to smaller screen sizes and larger finger contact areas. Consider optimizing email design for mobile devices to mitigate this.
Email marketer from Sendinblue responds that segmenting email lists based on engagement can help isolate and reduce the impact of bot clicks. Focusing on highly engaged segments provides more accurate metrics.
Email marketer from Litmus explains that inflated click rates are often due to bot activity, where security software clicks links to check for malicious content. This artificially inflates metrics.
Email marketer from Gmass explains that some email clients' preview panes might automatically load images and links, leading to inflated open and click rates. They suggest being cautious of the initial results and focusing on trends over time.
Email marketer from Reddit explains that analyzing click IP addresses and user agents can identify bot clicks. Consistent IPs or unusual user agents often indicate non-human interaction.
What the experts say3Expert opinions
Expert from Spam Resource responds that focusing on engagement metrics beyond just opens and clicks can help mitigate the impact of inflated click rates. They recommend analyzing reply rates, forward rates, and conversion rates to get a more accurate picture of campaign performance.
Expert from Word to the Wise explains that bot detection is complex, requiring constant adaptation as bots evolve. They emphasize the importance of analyzing click patterns and user behavior to identify non-human interactions.
Expert from Email Geeks shares that Microsoft seems to have increased their following all links behavior sometime at the end of 2023, continuing through 2024, targetting certain senders for some period of time.
What the documentation says4Technical articles
Documentation from RFC explains identifying bots by looking up the hostname from the IP address (reverse DNS). Many bots use servers with names that don't resemble real users (e.g., crawl-66-249-66-1.googlebot.com), so you can often flag them based on these patterns.
Documentation from Validity explains methods to identify and filter pre-click activity (bot clicks) from email reports. This involves analyzing IP addresses, user agents, and click patterns to distinguish between human and non-human clicks.
Documentation from Cloudflare explains using bot management solutions to identify and mitigate bot traffic. This can involve analyzing request patterns, user behavior, and employing challenges like CAPTCHAs to distinguish between human and bot interactions.
Documentation from Google Analytics explains how to filter bot traffic from website analytics. This involves using the bot filtering feature in Google Analytics settings to exclude known bot IPs and user agents.