The following are two hypothetical emails with different content. They were deployed last month at the same time, and after two weeks their results were recorded. This is how they fared:
December Newsletter A
View rate: 15%
Click rate: 2%
December Newsletter B
View rate: 30%
Click rate: 5%
A greater proportion of recipients viewed Newsletter B and clicked than Newsletter A. Looking at these metrics, it would suggest that Newsletter B was the stronger, more successful email.
But is this definitive? When you look beyond these topline results, certainly not.
Newsletter B’s delivery and unsubscribe rate were worse than Newsletter A’s. This suggests two things: firstly, that there was a data issue, indeed Newsletter B was sent to a few more thousand recipients than Newsletter A. More room for error. Secondly, that the recipients were not impressed with the content in the email: it was of no real worth to them, which led them to opt out.
Despite achieving a higher click rate, the quality of Newsletter B’s clicks was lower than Newsletter A’s. B’s recipients were quicker to drop out once they clicked through to the website. The majority were also missing the key information, instead clicking through from minor links, rather than the call to action buttons.
Email success is hard to call. No matter how many reporting stats are viewed, some personal judgement must be taken. You can at least make sure you’re on the right track with the following advice:
1) Look at the big picture. A stat in isolation is useless. Be curious, ask yourself what a 30% open rate actually means, and delve a little further.
2) Link metrics together. Study their impact on one another e.g. 10% click rate and 5% unsubscribe rate. It appears engagement is good, however why are there so many uninterested?
3) Track the recipient journey. For every weaker stat, ask yourself why these individuals have behaved in this way. Replicate their experience to better understand where the problems lie.
