My Wish List For Email Analytics In 2017

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by George Bilbrey Email marketers spend a lot of time on email analytics. Various studies put the amount of time spent on analyzing ...

by George Bilbrey


Email marketers spend a lot of time on email analytics. Various studies put the amount of time spent on analyzing the results of their email marketing activities between 15 percent and 25 percent.
However, the kinds of reporting provided by email platforms don’t make it easy to answer the key questions that email marketers are being asked. Most platforms do a good job at several things, including:

  • Provide a good understanding of how a campaign or mail stream performs on key email metrics (opens, clicks, click to open ratio, unsubscribes, complaints). Frequently ESP reporting will show trending on these metrics over time.
  • Typically, most platforms provide a high-level measure of subscriber and list health: size of list, growth over time, unsubscribe, and complaint rate.
  • Some platforms add a revenue component to the standard reporting: average order value, revenue per subscriber.
Of course, there are many different email marketing platforms, with many different approaches to email analytics. The above is a generalization based on experience with a handful of the most popular.
Unfortunately, the above approach doesn’t help clients answer the most common questions that email marketers ask themselves, especially: “My campaign didn’t perform as expected. What is causing the variance from expected?”
When I hear this, the first thing I like to check is to see if the campaign was actually “normal.” Ideally, reporting could show:
  • Did I send to the same subscribers as usual?
  • Have I sent more mail to these subscribers than usual?
  • Did I send at roughly the same time as usual?
  • Was the template changed?
  • Are the offers and calls to action different from the usual?
Assuming that the campaign was sent as usual, the next question is: “Did the mail make it into the inbox in a usual way?”  Reports could answer questions like:
  • Was my mail accepted by the receiving mail server?
  • How does that differ between major mailbox providers?
  • Once my mail was accepted for delivery,  was it placed in the inbox?
  • How does that vary for subscribers who normally open/click vs. those who don’t?
  • Which Gmail tabs were my messages sorted into?
  • Were other marketers sending a lot of mail around the time that this campaign was sent? (Crowded mailboxes may depress results.)
If the mail makes it into the inbox in the “usual” way, what else might be causing performance to dip? A subset of interesting questions include:
  • Were open rates different than usual for different engagement and purchase segments?
  • Did open rates for other marketers change in the same direction at the same time this campaign was sent? If not, what were the subject lines for those competitive campaigns that did well at that time?
  • Did “dwell time” on this campaign differ from normal? (If subscribers aren’t spending time on my message, presumably there is something about content that is less engaging than in the past.)
  • Per open, were click rates different from usual for various engagement and purchase segments?
  • Assuming a standard template is being used, which areas of the template are seeing the biggest dip in click rates? For example, if you typically have a hero image at the top of the email with a customized product offer, is that area seeing the same decline as other parts of the email?
  • Do opens and clicks differ from usual by kind of email client (mobile, webmail, etc.).?
This is a lot of data for a marketer to go through for each and every campaign. The ideal email analytics package would highlight those areas where the marketer needs to focus.
What is on your wish list for email analytics?
This post originally appeared on Media Post.

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