Multichannel Customer Value: A Case Study

Click on the image to enlarge it.

We make a lot of decisions on the basis of multichannel customers. And why not? Our industry leaders tell us our customers demand a seamless multichannel customer experience.

For me, frustration boiled over this past week, when industry leaders cheered J.C. Penney's decision to consolidate marketing and merchandising functions across channels.

When did it become so fashionable for industry leaders to cheer the loss of jobs, all in the name of operational efficiencies that allow vendors to profit from the sale of multichannel solutions?

The phrase that vendors, industry experts, research organizations, and trade journals most frequently use to promote a multichannel agenda is this one:

"Multichannel customers are the most valuable customers".

We now know that this statement isn't accurate. Business Intelligence teams that use fair queries, controlling for other factors, do not observe this relationship.

The analytics used to defend the statement are highly biased. The metric is backward looking, not forward looking. Analysts query a database, splitting customers into two groups --- those that purchased from multiple channels last year, and those who purchased from a single channel last year. Next, the analyst computes the mean of last year's net sales in each group.

By default, the multichannel group will have spent more. The query is designed to make this happen. A single channel customer is disproportionately skewed toward one purchase. A multichannel customer, by definition, had to purchase at least two times. This greatly biases the results of the query.

The bias benefits our entire vendor industry, from those offering inventory solutions to those promoting the use of paper advertising to those offering e-mail solutions to those promoting pay-per-click marketing to those providing website marketing products and services.

Now honestly, you might find that multichannel customers are your best customers. But it will be because your unbiased queries prove they are your best customers, not because somebody surveyed 849 customers and extrapolated the results to 300,000,000 residents of the United States.

What happens if we try to eliminate this bias?

The image at the start of this post illustrates future twelve month net sales, based on customer activity in the past twelve months for a client. Sure, this metric will be viewed by some as being biased. Maybe I'll spur a discussion that improves how we view our field.


Here's how you run the query.

Step 1: Identify all customers who purchased from your brand in 2006.

Step 2: Within this audience, select customers who were customers prior to 2006 (in other words, eliminate all new customers in 2006).

Step 3: Identify the top 25% cutoff point for spend in this audience in 2006. Say that amount is $350. Keep that amount in mind for subsequent analyses. Select only customers who spent at least $350.

Step 4: Within this universe of great customers, calculate the average number of channels the customer purchased in during 2006.

Step 5: Calculate the mean net sales spent by this audience in 2007. If a customer did not purchase in 2007, the customer spent $0.

Step 6: Repeat steps 1-5 for all prior years, using the $350 cutoff (or whatever your dollar cutoff is for really good customers) in each year you run the analysis.

Step 7: Plot average channels purchased from (x-axis) by mean net sales in the next twelve months (y-axis).

Step 8: Review your graph (the graph attached to this post).


If the experts are right, then this graph should have a linear relation, with future sales increasing as prior channels increase.

In this example, we don't observe a linear trend, do we? In fact, the correlation is negative. Among really good customers, years where there was high multichannel activity were followed by years of lower spend.

What caused increased spend? Merchandise productivity! When the brand offered great products, customers spent more. When the brand didn't have great products, customers spent less. Channels didn't play a significant role in increasing or lowering customer spend.

Our industry demands that we improve the multichannel customer experience, offering little proof that customers will spend more.

Data consistently tell us that when customers love the merchandise we offer, customers spend more.

Focus on merchandise, the main reason customers buy from your brand. Then allocate proportionately fewer resources to the vendor / expert / research / trade-journal agenda of multichannel excellence.