E-mail open rate is an unreliable metric – here’s why

Szerző: Nagy Ádám Közzétéve:

In the last couple of years, backing up any kind of results with data and numbers has been becoming increasingly important in the corporate world. It’s a trend that I totally agree with, but today, I would like to introduce a slightly different aspect of the question: what happens if we handle existing numbers incorrectly and build our work on unreliable data? There is one certain metric that causes similar problems quite easily – it’s the email open rate.

The technical reason: the calculation of the open rate

So far, there’s been only one working solution to measure the open rate of newsletters: the newsletter platform (e.g. Maileon, Mailchimp) hides a transparent, tiny, one-pixel image somewhere in the mail, and the actual measurement is based on how many times the user loads this picture. This raises a very simple, yet unsolved problem: there are too many different e-mail platforms out there, and each of these manages pictures in a totally different way. Maybe the “tracking pixel” appears automatically in Outlook, but it only appears as a red X in Gmail or on your phone, meaning that it won’t count towards the opening rate. To further complicate matters, there are devices – typically mobile email clients – that display emails in plain text format, and there are also some clients (like Outlook) where there is a preview field, also distorting the opening rates.

Based on these, it is clear that there is a high degree of uncertainty in the calculation of the e-mail open rate, which is why this metric is not accurate on its own. If an email has an open rate of 25%, that does not necessarily mean that only one in four people have read it – the number might actually be much higher, but we won’t know due to the different platforms people use.

The human reason: the real significance of the open rate

There is another aspect that slightly undermines the reliability of the opening rate – the human factor. We tend to attach too much importance to this single metric: this serves as feedback for us about the message’s content, wording, visual world, effectiveness, and so on… But in fact, this number means much less: as the name suggests, it’s only about how many people have actually opened that letter. It does not tell how good the content was (as we do not know how many people read the whole letter at all), it does not tell us whether we used good colours and pictures, or whether the main message was well-received or not; we cannot measure these in this way, only through comparison, and that’s something we’ll cover a few paragraphs later.

There are a few factors that – if used well – can consciously influence the open rate, such as the subject of the letter, the sender or the time of sending. Unfortunately, on the other hand, there are many other factors beyond our control – people may not have opened the mail because they didn’t have the time, were not in the right mood or were simply dealing with another task. I’m sure these are familiar situations for all of you; sometimes, it’s simply the circumstances that stop us from reading an email.

But what’s the real use of open rates then?

Before we finally acknowledge the open rate as a totally useless metric, let’s look at the options for leveraging the data we have: what it can actually be used for, and what alternatives do we have to get real feedback on the effectiveness of our newsletters.

As I wrote earlier, the open rate on its own does not work well, but what if we have a whole series of open rates? The situation is wholly different in this case because the trends and patterns that emerge from these numbers are real, usable data. If we send out a newsletter every week for six months to the same target audience, but with different subject lines, and the open rates vary between 60% and 30%, there’s a reason for that – some topics are more relevant to the readers, while others are less interesting. That’s why this metric is also ideal for A / B testing, which I wrote about earlier (available in Hungarian – translation coming soon :)

Another solution to eliminate the inaccuracy of the open rate is to focus on measuring clickthrough rates instead: a much clearer and more realistic feedback on how many people are actually interested in a certain topic. There are no platform or client-specific circumstances here, and there is relatively little chance that someone will just accidentally click on one of the links in the newsletter – a click is a clear statement that we have won the attention of the reader.

In short, the lessons learned are the following:

  • The open rate is a number that should be treated carefully – it cannot be interpreted by itself, only in terms of comparisons, for showing short-term or long-term trends or for A / B tests.
  • The moment you start writing a new email, think ahead and put links, call-to-actions into the text that will later give you reliable, accurate click-through rates.

More English language Komm365 articles are available here.

Nagy Ádám

Kommunikációs szakértő, kreatív geek, blogger. 🦸‍♂️💬 Közel hét éve segítek vállalatoknak abban, hogy a belső kommunikáció következő szintjére lépjenek - nem csupán tartalom, hanem a használt digitális eszközök és a színfalak mögött zajló folyamatok terén is.

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