Don’t believe me? Consider (sources, Content Marketing Institute & Optinmonster):
When I talk with prospects about their sales, marketing and communication programs, there’s a lot of variance regarding the primary tools they use. The one thing they all have in common is the use of email.
Despite the ubiquity surrounding email communications, very little time is spent developing and executing a robust email strategy. I’m convinced that the reason this is true is because email feels easy and inexpensive. It’s just so easy to think that sending “one” bad/ineffective email is no big deal, we’ll just make it up on the next one. Then one becomes two; two becomes 12, and so on.
The reality is that email is one of the most expensive channels in the marketer's and salesperson’s communication toolkit. While sending an email doesn’t cause an immediate, direct cost, what happens after that is significant.
Six-months ago we sat down to completely re-imagine our entire approach to email. Recently, that method (and the results it’s gained) was featured as a case study by HubSpot. Since the case study was published, I’ve been asked several times how we did it. This post will highlight how we’ve lit our email strategy on fire and are expanding our competitive advantage because of it.
Our email program was not particularly effective. While I say that, I also need to point out that there was nothing obvious about the problem. The reality was that I would have been able to share the metrics of that email program with great pride. Our open rates, click-through rates and conversion rates were all above industry targets. Our emails were well written, got lots of positive comments and support the lead generation, management and sales processes. We literally had no reason (on the surface) to approach things differently.
However, despite all of the positives, I knew it wasn’t working. First, I knew that the common metrics that are used to measure email effectiveness are highly flawed. Second, I also saw the trends.
As I shared in the beginning of this post, despite email having virtually zero direct cost, it’s one of the most expensive channels available and it was clear to me that we were suffering many significant costs that had to be addressed. I shared a detailed analysis of the structural problems facing email earlier this year. Here are some of the highlights:
The cost of ineffective email is so high and the challenges so significant, that we actually made the decision to discontinue all emails that were not directly associated to delivering a blog subscription or to a lead nurture program. Not existing (by not sending emails to anyone else) was a more valuable decision than implementing a poor email strategy. Though clearly, not emailing significant chunks of our database was less than ideal as well. We knew we had to change something.
Two things happened that enabled us to begin to change our approach:
By integrating Seventh Sense’s Email Optimization Platform, we were able to do what we do best: hypothesize and test. We decided the best place to test was with our highest value asset: our blog subscription list.
The first thing we did was run an email fatigue analysis to determine levels of engagement. We broke our subscription list into four groups:
There are three leverage points when implementing an email strategy:
The test we designed would focus on the second two elements.
Cohorts and Content (The Strategy)
This is the area we’ve always done well with. From the beginning, we’ve implemented a clear segmentation strategy and are very focused on the what, how and why of the content we create for email (and just about everything else).
At the point of testing, we had two blog subscription lists; those who requested instant notification and those who requested weekly notification. For this test we eliminated that difference and broke subscribers into two cohorts:
Engagement (The Cadence)
Our original blog cadence was based upon the choice the subscriber made. In this test, we eliminated that choice and instead would send with the following cadence:
Send Time (Timing)
The third element was using send time. While we had read (and reread) numerous studies highlighting “the best time to send an email,” we knew that the best time to send an email was the time the recipient would be most likely to engage with it. To address this, we used Seventh Sense’s send time personalization capabilities.
Send Time Personalization (often referred to as send time optimization) is an optimization technique of using email engagement data (open and click data) and scheduling your emails to be delivered to each person when he or she is most likely to engage with your email.
The decision we had to make here was how broad a band to use for send time. We made the following decision:
Before running the test, our key metrics from the blog email looked like this (with very small differences between the instant and the weekly emails):
We knew that by breaking the groups apart by engagement levels we’d see increased metrics from our instant notification blog. We anticipated the open rates to regularly be above 30% and have been pleasantly surprised that they’re typically above 34%. We were very happily surprised to see clicks rates move to 6.5% - 9%.
We know from the data that these results are a combination of both a more highly engaged cohort and send time optimization. As we dug deeper into the numbers, we found something else that surprised us:
But, we were absolutely blown away when we saw the result from our less engaged cohort. Open rates have run 2.3 - 4.9% and click rates have run 0.25 - .77%. Absolutely horrible! I looked at those rates and had one thought, “Why are we even emailing these people?”
This has led to several changes to our email playbook, that we’re still in the process of implementing:
Stay tuned...In a future post, I’ll share the details of our new email playbook.