The many ways you can use the revenue per email metric to identify problem areas in your email program.
In my last column, I wrote 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. Today I want to present more ways to use RPE in analysis to identify areas of strength and weakness in your email program.
For this client, I calculated their revenue per 1,000 email delivered (RPME) on a quarterly basis. It's the same calculation we discussed in the previous column, but now you're dividing the total revenue from email for the quarter by the total number of email messages assumed delivered for the same period. Note that it's the number of messages assumed delivered, not the unique number of people you sent the email to, that's used.
This calculation, done over a two-year period, showed the RPME trending downward - it went from a high of nearly $80 to a low of about $35 (see the graph below). You don't need to have an advanced math degree to know that this isn't the direction you want your revenue per email going.
If your business is seasonal, it may be helpful to look at year-over-year figures (see the chart below).This is the same data as on the first graph, but now you can clearly see the year-over-year variance by quarter. The orange line represents performance in fiscal year 1, the red line, performance in fiscal year 2. Looking at the linear trend lines, you can see that not only did fiscal year 2 trend lower, but it declined at a faster pace than the fiscal year 1 line. Again, this is not good news.
The question to ask now is "what changed?" For simplicity, let's focus on the fourth quarter, where overall RPE dropped from about $60 to about $35, a 43 percent decrease.
Eleven business units generated revenue from email marketing in the fourth quarter of fiscal year 2, compared to just five business units in the fourth quarter of fiscal year 1. Let's start by looking at year-over-year performance for just the five reporting revenue in both quarters (much as retail stores report year-over-year earnings from stores open a year or more).
When we isolate these five business units, we see that RPME performance decreased by 40 percent; clearly while the new business units that came online didn't help performance, the primary cause of the drop is a decrease in year-over-year performance of business units that had been sending email. The quantity of email assumed delivered more than doubled, but revenue increased by less than 25 percent. These business units are sending more email, but the effectiveness of each email sent is less than it was a year ago.
A more granular view of RPME shows that four of these five business units (highlighted in orange below) experienced a decrease in RPME; three of them showed RPMEs down by 45 percent or more, with one (business unit D) showing a decrease of 96 percent! Of the six new business units coming online in FY2, just one of them generated an RPME equal to or greater than the FY1 overall RPME. And four of the six had RPMEs that were below the overall RPME for Q4 FY2.This suggests there's a macro issue that may be negatively impacting RPME across the board for the organization.
The most common macro issues that will decrease your RPME are:
In addition to one or more macro issues, there are also likely some micro issues that are depressing RPME. Again, for simplicity, let's hone in on the single business unit with the worst year-over-year performance, which is D.
Although the client's overall send quantity is up, business unit D actually sent less email in Q4 FY2 than they had in Q4 FY1. Even so, while send quantity was down by half, revenue dropped by 98 percent.
If business unit D increases their send quantities to the FY1 level, will the revenue and RPME also return to those levels? No. It's not that simple.
At this point, a deeper analysis into the lists and creative used by business unit D in Q4 FY1 and Q4 FY2 is in order. The goal here is to look at what worked in Q4 FY1 and what didn't in Q4 FY2. Then devise a strategic plan moving forward to boost RPME.
The same type of analysis and strategic planning will need to be done for each business unit on the list, identifying their strengths and weaknesses and devising a plan to improve performance. This organization may never get RPME back to FY1 levels, but they need to reverse the steep downward trend in RPME to continue to have a successful email program.
Until next time,
Revolutionize your digital marketing campaigns at ClickZ Live San Francisco (August 10-12)!
Educating marketers for over 15 years, our action-packed, educationally-focused agenda offers 9 tracks to cover every aspect of digital marketing. Join over 500 digital marketers and expert speakers from leading brands. Register today!
Jeanne Jennings is a recognized expert in the email marketing industry and managing director of digital marketing for Digital Prism Advisors. She has more than 20 years of experience in the email and online marketing and product development world. Jeanne's direct-response approach to digital strategy, tactics, and creative direction helps organizations make their online marketing initiatives more effective and more profitable. Digital Prism Advisors helps established businesses unlock significant growth and revenue opportunities in the digital marketplace; our clients learn to develop and implement successful digital strategies, leveraging data and technology to better meet bottom line goals. Want to learn more? Check out Jeanne's blog and Digital Prisim Advisors.
US Consumer Device Preference Report
Traditionally desktops have shown to convert better than mobile devices however, 2015 might be a tipping point for mobile conversions! Download this report to find why mobile users are more important then ever.
E-Commerce Customer Lifecycle
Have you ever wondered what factors influence online spending or why shoppers abandon their cart? This data-rich infogram offers actionable insight into creating a more seamless online shopping experience across the multiple devices consumers are using.