False clicks and opens generated by robots are a scourge for honest email marketers! But let's not kid ourselves, they are legitimate. They are the result of more or less rudimentary anti-spam filters which to protect the security of certain Internet users. This allows these filters to better understand which destination pages visitors are directed to after clicking on an email. It can also be used to check the content of email images.
They are especially in B2BAnd even more so when sending campaigns to small and medium-sized businesses. Why is this so? Because we spam filters in consumer e-mail services are much more advanced and are based on other types of data which they possess in far greater numbers. What's more, 2 phantom clicks on 4 emails sent to a company will pose a far greater statistical gap than 10 phantom clicks on 10,000 emails sent to a consumer e-mail service.
B2B campaigns are inherently much more granularIn a B2C campaign, the first 4 deliverability destinations often account for more than 80% of emails sent.
If you do your job properly, false clicks and false openings have no direct impact on your email deliverability. They're there for the spammers, not for you (I hope).
On the other hand, they do make a mess of your campaign statistics.
Identify the sources of false clicks and opens in emails
Your mission (if you accept it) is to identify the sources of false clicks and false opens in your emails. We can mainly identify two types of "prints which will enable you to identify false clicks and false openings in the future:
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- The user-agent : It's the footprint left by a browser or robot. It's like a model and a version number. For example, at the time of writing, my browser's user-agent is "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:120.0) Gecko/20100101 Firefox/120.0". Now you know I'm using Firefox 120 from Ubuntu. Please note, however, that some bots can pretend to be human. In this case, it will be undetectable.
- IP address This is the physical address of the server or computer that interacted with your message. In some cases, robots always use the same addresses or networks. So it's a good idea to map them to keep track of them. However, if the "real" human recipients of your e-mails use the same IP addresses or networks as the clicking robots, you shouldn't lump them all together.
Sometimes, it's impossible to detect a reliable, generalizable source to identify a robot. In these cases, we'll have to do the work "piecemeal", interaction by interaction... if at all possible.
You may be wondering where to find this data in your emailing tool ? This is where things get tricky. In some cases, they are in the database and can be retrieved via an API. But that's not always possible. In this case, you'll have to call in a developer to add an overlay to your links and create images dedicated to robot detection. Clearly, this is a highly technical affair, and the poor marketer won't be able to get by without a technical helping hand.
Implement tactics to detect robot clicks in your emails
To identify user-agents and IP addresses, we'll have to set traps. Here are several tactics you can implement. Ideally, this is the role of your emailing tool. But most of these tactics are highly technical and will rarely be implemented by your routing solution.
- Ultra-fast" click and open detection Human and automated behavior are often different. A human will take time to read an email and click on links, whereas a bot will do so almost instantaneously. It is therefore possible, for example, to detect bot behavior when they click on several links in an email in less than a second.
- Detection of clicks before opening To click on an e-mail, it must first be opened. We can therefore consider as suspicious an e-mail that is clicked without being opened. However, this technique is only valid for messaging systems that automatically load images before opening. See our article on calculation of email open rates.
- Detection of clicks on all links in an email : A sane human being is unlikely to click on all the links in your e-mail. This is another signal that you're probably in the presence of a bot.
- Creating links dedicated to robots These links or buttons, invisible to the human user but detectable by bots, can be used to identify automated clicks. You could, for example, place this link on a transparent pixel in your e-mails.
- URL modification detection : Some anti-spam solutions modify the parameters of URLs present in emails before accessing them. This should normally generate errors. By detecting these errors, it is then possible to cross-check suspicious behavior and identify bots.
- Analysis of click patterns Repetitive or unnatural click patterns may indicate automated activity. This is the case, for example, if all clicks are sequential in relation to the HTML code of your e-mail.
Correct your statistics to eliminate clicks and opens generated by bots
With the information above, it is likely that you have already managed to detect some of the interactions generated by robots. In this case, if you manage your own statistics dashboards, you'll be able to clean up your statistics.
Unfortunately, you won't necessarily be able to rely on your emaling mailing tool to do the job. And you probably won't be able to be exhaustive. In this case, you could try detecting destination domains with outlier statistics. This will enable you to reject them from your statistics, so that your click and open rates are closer to reality.
