Most email marketing teams spend much of their available time building and optimizing creative. Most testing that takes place is on subject lines, calls to action, and other elements of the email creative.
If email teams have a little more time (and investment from their organization), they may invest in building triggered, contextual messaging programs that will drive deeper client relationships and more opens, clicks, and conversions per subscriber over time.
These are worthy investments. Based on my conversations with many email marketers over the last year, this focus on optimizing creative and more “contextual” programs is based on three factors:
These are well-understood investments. Marketers have made these sorts of investments before, and there are well defined “templates” to follow
These projects can be achieved with the people currently on the email marketing team. They don’t require (a lot of) additional people resources.
However, I think there is a third reason that, although subtle, is important:
Common email metrics drive focus on creative optimization and program strategy. The metrics commonly provided metrics by email service providers (ESPs) focus on campaign-level (and sometime program-level) open, click, and other performance data. This invariably leads to a focus on improving open and click rates by changes to subject lines, offers, calls to action, etc.
Let me present three alternative metrics that could (and in many cases would) drive focus on different “levers” for performance:
1. List quality: Reviewing the read rate performance (similar to open rate) for several thousand marketers across a consumer panel of 2.5 million mailboxes reveals a counterintuitive fact: The marketers that drive the highest read rates (and reads per subscriber per month) frequently use the least-sophisticated marketing. They use little segmentation and rely primarily on traditional “batch-and-blast” techniques.
How can this be? It turns out that the major factor determining read rate performance is quality of the subscriber list. If the marketer has a list comprised of highly active, primary accounts, their email marketing performance will inevitably be strong. Secondary or inactive accounts rarely respond to email.
So marketers should have access to reporting that shows the makeup of their list and gives them an understanding of the “natural limit” of what they can do with their email marketing program. This data could come from consumer panels or through data cooperatives that allow marketers to see how responsive each address on their list is with other email marketers.
If email marketers had access to this kind of metric, they would focus more on understanding the quality of addresses that come from each acquisition source and investing more on address acquisition from channels that drive higher quality addresses. They would focus on the value proposition and calls to action at time of signup to review which “treatments” drive higher quality subscribers.
2. List churn: One of the weaknesses in ESP reporting is the way unsubscribes and complaints are displayed — usually per campaign rates. Each campaign will show far less than 1% of subscribers churning off the list by unsubscribing or hitting the “report spam” button at a consumer mailbox provider.
However, over many campaigns, the number of terminations adds up. It’s not uncommon for a marketer to lose 20% to 50% of starting subscribers over the course of a year. Careful analysis of those who unsubscribe shows that they are better than average subscribers, which can mean that list churn causes the overall list quality to decline over time. Ideally, ESPs would show aggregate list churn over time and calculate the cost of list churn in terms of changes to list quality and future opens, clicks, and conversions that are now not possible.
With access to this kind of metric, it’s likely that marketers would focus more on cadence and targeting, increasing list quality, and dramatically increasing the expected lifetime value of the list as measured by clicks or conversions.
3. Competitive loyalty: Much of email marketing investment is justified by deepening the relationship with customers and building greater loyalty. However, there is little loyalty data available to email marketers to see how they are doing in terms of share of transactions, share of spend, or share of eyeballs. This kind of data is available through market research and through consumer panels.
To get this metric, marketers would likely run tests to see which program types optimize loyalty: lifecycle, contextual based on web activity, etc. They could also take some guidance from what is working for other email marketers
There are likely other “missing” metrics. What kind of metric would you like to see?