Learn how to calculate revenue per email and use it at a cell level to determine winners in your testing process. Columnist Jeanne Jennings shares success stories and record high RPMEs from recent campaigns.
Two years ago, I wrote a column about the value of the revenue per email (RPE) metric; how to calculate it and how to use it to use it at a cell level to determine the winner when you’re testing. I followed that up with a column on more ways to use RPE in analysis, to identify areas of strength and weakness in your email program.
I’ve continued to use RPE or, in cases where the RPE figure is small, revenue per thousand emails (RPME) with clients. Here’s an update on successes we’ve had thanks to focusing on this metric.
As you can see in the chart above, we’ve driven record high RPMEs in the last two quarters. Revenue generated per 1,000 emails sent has gone from double to triple digits and their bottom line has benefited.
The key to success here isn’t sending more email; it’s being smarter about the email you send.
When I began working with this client a few years ago, their year-over-year quarterly send quantities (they’re a seasonal business, so year-over-year makes more sense for them than quarter-over-quarter) were increasing at a rapid pace. In 2010 and 2011, there was only one quarter with a single digit year-over-year increase. In more than half those quarters, the increase exceeded 25 percent.
At the same time, their universe of prospects and customers wasn’t increasing dramatically. What was going up was their frequency. The number of people receiving an average of one email message every other day increased by 368 percent, while the number of people receiving an average of more than one email every other day went up by 9,115 percent (see the chart below).
The majority of these increases weren’t driven by people opting in to receive more email – they were driven by business units dramatically increasing the frequency by which they were sending to the company’s house list. At trade shows and in other communications with customers and prospects, many reported feeling bombarded with email from the company.
In mid-2012, corporate management mandated a decrease in send quantities for all business units. The only exceptions were email newsletters, which recipients were explicitly opting to receive, and new business units with no historic email program.
Going back to the first chart, you can see that increases in year-over-year quarterly quantities assumed delivered (and, although not shown here, quantities sent) decreased dramatically beginning in Q3 2012. The largest year-over-year quarterly increase since then was just 13 percent; a far cry from the high of 59 percent seen in Q1 2011.
It took a while for business units to embrace the idea of mailing smarter instead of mailing more. The RPME took a hit in Q3 2012, falling once again below the Q3 2010 figure. But then things began to turn around.
In addition to mandating send quantity decreases, the company’s internal agency ratcheted up creative testing and, most significantly, the internal list team worked more closely with business units on segmentation and the targeting of lists. By analyzing past results, we were able to identify the list segments most likely to respond to specific offerings. Ongoing testing of segments allowed us to continue to refine this targeting and to improve the RPME figures for each individual send.
Q1 2013 saw the first decrease in year-over-year quarterly send and delivered quantities, along with a slight increase in RPME over the same quarter in 2011 and 2012 (we were still below the 2010 figure, unfortunately).
As you can see, in the second and third quarters of 2013, this new approach to email has significantly improved RPME; we’re at the highest levels in the four years we’ve been tracking it. We saw small, single digit increases in year-over-year quarterly send quantities, primarily due to new business units using email. But the improvement in RPME, 58 and 150 percent respectively, was dramatic.
Hopefully your head isn’t swimming from all these numbers. Taking a quantitative approach to your analysis is critical for long term success. If you aren’t looking at your email program in this way, it’s time to start! Use the articles I linked to from 2010 to get started and then move forward. By doing this analysis for each business unit in your organization, or for each product you offer, you can identify areas to target to improve your bottom line metrics. Give it a try and let me know how it goes!
Until next time,
Jeanne
