The first thing we need to do is find "equal" customers. If there's one thing I've learned over twenty-four years of analyzing customer behavior, it is this ... so much of the data we hear about in trade journals and vendor communications is biased and wrong, because customers have not been "equalized". So let's pick "equal customers", or at least do the best we can.
In this example, we evaluate the fabled "mobile" customer. Now, you lived through the e-commerce revolution ... you heard all the stories about how much more valuable e-commerce customers are. Then we lived through a decade of customer transition, and found out that e-commerce customers were not more valuable, not in the least bit. Instead, we learned that wealthy customers were the first to transition to e-commerce, completely blinding us to what was really happening.
The same thing is happening in the "mobile revolution".
When you run a query to measure the "impact of mobile", try to identify customers that are relatively equal.
- Freeze your customer file, on, say, July 1.
- Pick customers with a purchase in the past 0-3 months, and exactly two purchases in the past year.
- Segment customers ... e-commerce only vs. e-commerce and mobile in their history.
- Measure spend by channel, from July 1 to September 30.
Query results will look something like this:
Do you see an appreciable difference in subsequent customer behavior? No.
You'll see this situation transpire, often. Customers are switching channels. Channels are not offering additional value.
Now, you'll still have to invest in new channels, no doubt. But there's no inclination that the new channel will turbocharge your business into future riches.
This is an easy analysis.
Almost nobody chooses to do this style of analysis.
Perform the analysis!
This is an easy analysis.
Almost nobody chooses to do this style of analysis.
Perform the analysis!
Those looking for quick ways to make money online would be wise to take note of this. The risk of targeting the wrong market is just too much of a risk to ignore.
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