Sometimes, E-Mail's Not the Problem
A funnel analysis can help identify the true source of the problem -- and save your e-mail program's reputation.
A funnel analysis can help identify the true source of the problem -- and save your e-mail program's reputation.
“Sales are down. Send more e-mail.”
If you’ve worked in e-mail marketing for any length of time, you’ve heard (or thought) this. But sometimes, the e-mail isn’t the problem.
The “funnel” is common in sales and marketing channels. It refers to the large number of contacts or leads you must start with to finish with just a few sales. Online marketing is particularly well-suited to this model, since you can tell, at each step, how many people are moving toward the sale, and how many are dropping out). For example:
First Send: The Baseline | ||
---|---|---|
Metric | Baseline | Baseline (%) |
Send | 100,000 | 100.0 |
Bounces | 12,000 | 12.0 |
Assumed delivered | 88,000 | 88.0 |
Opens | 26,400 | 30.0 |
Clicks | 2,200 | 2.5 |
Order page 1 conversions | 2,200 | 100.0 |
Order page 2 conversions | 1,430 | 65.0 |
Sales | 1,073 | 75.0 |
Here we start with a send quantity of 100,000, in other words, a list of 100,000 e-mail addresses we’ll mail to. We’ll assume 12.0 percent (an industry benchmark, according to Jupiter Research) will bounce, leaving us with 88,000 e-mail addresses that receive our message. We’ll also use Jupiter’s benchmark for opens, 30.0 percent, so 26,400 people open the message.
Moving forward, 2.5 percent of those who receive the e-mail clicked through to the first page of the order process to take advantage of the offer. But only 65 percent of those people completed the first order page and go on to the second; and only 75 percent of these people went all the way to the order confirmation page.
We’re left with 1,073 sales from an e-mail send to 100,000 people. Not bad.
But what happens when sales drop?
Say sales drop from 1,073 to 924 the second time the message is sent, a loss of 149 units. As the e-mail marketer, you may get a frantic call from a higher-up explaining the e-mail isn’t working and needs to be fixed because sales are down:
Second Send: Conversion Decrease | ||||
---|---|---|---|---|
Metric | Baseline | Baseline (%) | Conversion | Conversion (%) |
Send | 100,000 | 100.0 | 100,000 | 100.0 |
Bounces | 12,000 | 12.0 | 12,000 | 12.0 |
Assumed delivered | 88,000 | 88.0 | 88,000 | 88.0 |
Opens | 26,400 | 30.0 | 26,400 | 30.0 |
Clicks | 2,200 | 2.5 | 2,200 | 2.5 |
Order page 1 conversions | 2,200 | 100.0 | 2,200 | 100.0 |
Order page 2 conversions | 1,430 | 65.0 | 1,320 | 60.0 |
Sales | 1,073 | 75.0 | 924 | 70.0 |
Variance | -149 | 86 |
But is it always the e-mail’s fault? Sometimes it’s not. It’s not unusual for organizations to seek the easiest or most visual suspect. Performing a comprehensive funnel analysis can help you identify the true source of the problem and, possibly, save your e-mail program’s reputation.
In the above example, sales are down, but the e-mail is consistently performing. The drop occurred within the order process itself. In this case, page-to-page conversions decreased. Instead of 65 percent of people who landed on the first page of the order process going on to page 2, only 60 percent did. The same happened with page 2 of the order process, where only 70 percent (not 75 percent, as before) going on to the confirmation page, completing the sale. The result is a drop in sales of 14 percent, or 149 units.
Although you can try to correct this with e-mail, it’s a blunt tool. To get sales back up to the baseline, you’d need to increase the list quantity over 16 percent, to 116,100. This will drive more traffic into the order process, so even with the lower page-to-page conversion rates you’ll still meet baseline sales goal:
Third Send: List Increase | ||||
---|---|---|---|---|
Metric | Baseline | Baseline (%) | List Increase | List Increase (%) |
Send | 100,000 | 100.0 | 116,100 | 116.1 |
Bounces | 12,000 | 12.0 | 13,932 | 12.0 |
Assumed delivered | 88,000 | 88.0 | 102,168 | 88.0 |
Opens | 26,400 | 30.0 | 30,650 | 30.0 |
Clicks | 2,200 | 2.5 | 2,554 | 2.5 |
Order page 1 conversions | 2,200 | 100.0 | 2,554 | 116.1 |
Order page 2 conversions | 1,430 | 65.0 | 1,533 | 60.0 |
Sales | 1,073 | 75.0 | 1,073 | 70.0 |
Variance | -149 | 86 |
While this is an option, anyone who works to grow a list can tell you accomplishing 16 percent growth, particularly in a short period, is no small feat.
Another approach would be to try to increase the CTR (define). By moving from a 2.5 percent CTR to a 2.9 percent CTR, you could increase traffic to the first page of your order process enough to compensate for the lower page-to-page conversion rates and meet your base-line sales goal:
Third Send: CTR Increase | ||||
---|---|---|---|---|
Metric | Baseline | Baseline (%) | CTR Increase | CTR Increase (%) |
Send | 100,000 | 100.0 | 100,000 | 100.0 |
Bounces | 12,000 | 12.0 | 12,000 | 12.0 |
Assumed delivered | 88,000 | 88.0 | 88,000 | 88.0 |
Opens | 26,400 | 30.0 | 26,400 | 30.0 |
Clicks | 2,200 | 2.5 | 2,556 | 2.9 |
Order page 1 conversions | 2,200 | 100.0 | 2,556 | 116.2 |
Order page 2 conversions | 1,430 | 65.0 | 1,533 | 60.0 |
Sales | 1,073 | 75.0 | 1,073 | 70.0 |
Variance | -149 | 86 |