Marketers are still grappling with finding the real value of digital marketing efforts. At the end of a promotional campaign, marketers find even the most “trackable” of web visits difficult to value. If we didn’t know this already, a survey of chief marketing officers, conducted by Atlanta’s Heidrick & Struggles, clarified the problem.
Kevin Hillstrom, author of Multichannel Forensics, suggests a reasonable way to approach web campaign valuation. It works well for e-commerce site visits, and even sheds light on valuing other types of visitors.
Placing value on non-buying visitors
Start the valuation process with the obvious: Visitors who immediately convert to a sale. But then keep going. Apply common sense numbers to those visitors who do not immediately buy. And why not? Visitors may come back two, three or more times before making a purchase. Like a fish that nibbles before biting, these “lost” visits aren’t so lost after all. They should be fairly depreciated, not totally ignored.
Here’s what Kevin says about ignoring all but the “one-visit” purchasers:
We try our hardest to allocate orders to the advertising vehicle that caused the order, seldom considering a series of events.
Take paid search as an example. Assume that a paid search campaign results in a 3% conversion rate and a $100 AOV [Average Order Value]. We run a profit and loss statement on the 0.03 * 100 = $3.00 demand generated by the campaign, factoring in the cost of the campaign.
What about the 97% of visitors who did not purchase?
Hillstrom asks, “What if you had this data?”:
- Of those who are left [i.e., 97% of the base], 50% will visit the website again within one week, with 3% converting, spending $100 each.
- Of those who are left, 50% will not visit again. Those who are left will visit again within three weeks, with 3% converting, spending $100 each.
- Of those who are left, 50% will not visit again. Those who are left will visit again within one month, with 3% converting, spending $100 each.
- Of those who are left, 50% will not visit again. Those who are left will visit again within four months, with 3% converting, spending $100 each.
- Of those who are left, 50% will not visit again. Those who are left will visit again within six months, with 3% converting, spending $100 each.
He goes on to explain:
There is value in each case, value that most of us choose not to measure.
When I iterate through the five cases above, I calculate an additional $2.75 of future visitor value. [I get $2.68 in my number-crunching, as the number in the lower right of the graphic shows. Here’s my math in a Google Spreadsheet.]
In other words, we measure the $3.00 generated by short-term conversion. We don’t always measure the $2.75 of future conversions.
Now there may be additional expenses associated with the $2.75 number — that customer might require additional paid search expense or might use a shopping comparison site, whatever. So we need to run a true profit and loss statement on the additional $2.75 generated by future visits.
If each first-time visitor (one that doesn’t convert immediately) is worth $0.30 profit over the next twelve months, you think differently about attracting visitors, don’t you?
I agree. The BrandWeek article I linked to in the first paragraph said that the CMOs surveyed, “Expressed an awareness of digital’s potential, along with a recognition that they weren’t close to tapping it.”
Building sales models that take into account the messy realities of online behavior is one way we can start.
I’ve noticed the same thing with email marketing. Just because people don’t convert on the first email doesn’t mean they’ll never convert. Most of the time the first conversion doesn’t come until around the 7th or 8th email.
Another thing to keep in mind too is that just because someone converted once, doesn’t mean they can’t convert again.
You’re right, Jason. This is especially true of email marketing. The only help there is that you ordinarily send emails to past customers, whereas most PPC works on customer acquisition.
With email, you can always withhold part of your distribution list as a control group, if you really want to see the lift of that release. That’s not possible with campaigns to the public at large!
I agree, though, that email marketers have to look at new ways to evaluate their efforts. They’re a key driver of business in most online marketers’ promotional toolkit.
Jeff,
Interesting perspective. I find a lot of these customer/visitor value calculations to be exercises in futility though.
I think Hillstrom’s assumptions of 3% conversion per successive visit is likely very low. In my experience (and with most typical sales processes), the more touches, the higher the conversion rate.
IMO, his 3% is too conservative, especially for a web-driven campaign. The close rates for traditional sales campaigns looks like this:
1 touch – 2% max
2 touches – 3-4%
3 touches – 5-7%
4 touches – 10%
5 touches – 22%
6 touches – up to 40%
7 touches – up to 55%
With every successive touch, I believe the likelihood of a purchase grows. The prospect continues to qualify him/herself with each visit, so the close rate should be higher. Conversely, the remaining pool continue to disqualify themselves, which accounts for the 50% visitor attrition. I believe that ratio is reasonable.
The validation of campaigns is tricky business. If you’re too conservative, you look like you don’t believe in your strategies or tactics. Too aggressive, and you look foolish. Instead, I believe that if you take the real sales numbers and add a common sense value for potential successive visits, you can come up with a believeable evaluation of your campaign(s), even if not completely accurate.
Jason – I agree with you on repeat conversions. I believe that good e-marketing analytics includes silos for first conversion (new customer), repeat customer, and if appropriate, resurrected lost customers. This can be accomplished with integrated lead or customer management systems and a strong call to action to entice someone to add their name to the mailing list.
To me, the only real metric that matters is the number of people who are willing to give me their personal data. From there, it’s a simple numbers game to extract expected sales.