ESP-provided campaign-level rate metrics: Open rates, click rates, click-to-open rates, etc. Clients are typically looking to improve these metrics over what they have achieved in the past. Usually these metrics are aggregated across campaigns.
Business attribution metrics: What percent of sales, registrations, etc. can be attributed to email actions? Typically clients use “last-click” attribution methods, though they do use other strategies as well.
Subscriber health/engagement metrics: More advanced marketers also take a look at trends in engagement within their subscriber base. What percentage of clients have opened/clicked or taken other action in the last 30/60/90 days?
These metrics are all useful. However, there are a variety of other campaign and program-level metrics that can be useful in understanding where to focus improvement efforts. These include:
Spam folder placement rate: If your mail doesn’t make it into the inbox, it cannot drive clicks and opens. Understanding campaign performance is difficult if you don’t know inbox placement rate.
Deleted-before-reading rate: Another term for this would be the “ignore rate.” It’s possible to have a high rate of customers reading and ignoring the same campaign. A high ignore rate is a sign of poor segmentation and targeting.
Reply rate: Some mailbox providers appear to use reply rate as a strong signal of user engagement. However, it’s not always clear what a high reply rate means for the quality of a campaign. Don’t try to do anything gimmicky to drive more replies, especially if it’s not consistent with your brand and business model. Still, might be a good idea to switch from a “noreply@” address to an address that is managed.
Forward rate: The number of emails that are forwarded to others is a great metric to measure engagement by. If the content you’re sending is interesting enough to forward on to others, your subscribers clearly think you’re doing something right.
In addition to campaign-based metrics, there are alternative metrics that I’d suggest taking a look at to understand program-level performance. These include:
List composition: What percentage of your list is made up of active email addresses that interact frequently with commercial email? How does that compare to other brands in your vertical? A list made up of active addresses will almost always outperform a list comprised mainly of secondary/inactive accounts. If you have a relatively “‘dead” list, taking a look at address quality by acquisition source is a logical next step.
Lifecycle engagement: What percent of your list is active when viewed by “weeks on list”? When does subscriber activity fall off? How does that compare to others in your market? If there is an obvious drop off in engagement at a given point in the clients’ subscriber lifecycle, this provides a clear indicator that you should build a re-engagement journey prior to that point for subscribers who show signs of disengagement. Take a look at competitors that have better activity curves than yours, see what they are doing, and copy it.
Messaging-type mix: What percentage of your messages are triggered/contextual vs. campaign-based? How does that compare to others in your market? What kinds of triggered messaging are you missing? How is your campaign-based and triggered messaging performing relative to other brands? Understanding the answer to these questions gives you a good understanding of where to make improvements to your email program.
Frequency and read rate: Compare the number of messages you send per subscriber per week relative to other brands, and see how that affects read rate, reads per subscriber per week, and overall list activity (percent of list “active” in last 30/60/90 days). Although it’s a somewhat complex comparison, you can frequently determine whether you are beyond the optimal range for frequency.
What do you think? What metrics do you find particularly useful that most email marketers ignore?