The email marketing chain: where's the break?

So we're looking at the chain of events that leads from sending an email to getting a click. Our challenge is to find the weak links where people are dropping out.

Here's that graphic again, showing the progression:


Last week we discovered ways of assessing whether Event 1 (Delivery) was the problem. And if you thought those techniques lacked certainty, it gets worse.

Despite all our clever tools, there is no reliable data to tell whether someone, for example, didn't click because they deleted your email before looking at it (failure at the recognition stage) or whether they read it voraciously but the final call to action hit the wrong tone (failure at the interaction stage).

Weep and wail. How can we optimize the chain when we don't know which part needs optimizing?

There is no simple answer, much as we'd all like one. Though there are moves afoot to find one.)

The practical approach, as so often, is to look at the numbers you can get out of campaign reports and apply a heavy dose of intuition and interpretation.

That's easily said, but difficult to explain or implement of course.

Typical result metrics (sales, downloads, registrations) don't help too much here. You need to examine the intermediate numbers. Let's explore a few examples...

Open and clickthrough rates

You can get into long arguments about open rates in particular. But put them to one side and consider some possibilities...

Have a lot of people never, ever clicked or opened an email? If it's not a delivery problem, it suggests a failure at the recognition or pre-interest stage. You're not getting them involved with your email at all.

Do you have high opens, but very few clicks? That tells you that you've overcome the recognition and pre-interest hurdles. But the main content isn't holding the reader's interest. Or the opportunity to interact (usually a call to action) isn't doing its job.

Do you have low opens, but high clicks? Since those that do get to the email seem to click, the problem is likely at the recognition or pre-interest stage: you're failing to make that initial connection.

[You're probably asking, what counts as high? What counts as low? That's where experience and intuition comes in.]

Unsubscribe and complaint rates

For someone to unsubscribe from your email, they have to at least give the contents some consideration, even if only to find the unsubscribe link. So a high unsubscribe rate suggests you have a problem with "interest": your content is not attractive enough to those readers.

Look particularly (if you can) at the number of people who unsubscribe after receiving their first email. If people aren't even giving you a second chance, then it suggests a big disconnect between what people expect and what you're sending.

If complaint rates are particularly high, it's possible the problem is a little earlier in the chain: perhaps people aren't recognizing the email they signed up for and think you're spamming them?

Care with assumptions

The reason why intuition, interpretation and experience play such a role here is because there are often numerous possible explanations for why a number is notably high or suspiciously low.

For example, high open rates are often put down to a winning subject line. But here are 14 other reasons your open rate might be doing so well.

If a lot of people unsubscribe after their first email from you, it might be because what you send isn't as valuable as they expected. Or maybe they subscribed for the coupon incentive you offered in the sign-up form and never had any intention of staying subscribed anyway.

Best practice comparisons

A safer way of evaluating your email marketing chain is to simply list best practices for optimizing each link in that chain and then compare that with what you actually do.

What are these best practices? Watch out for the next post.

Any other suggestions for pinpointing the weak areas in your emails?

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