Cross-Selling Part 3, the Mileage Chart

In this blog, Cross-Selling Part 3, we look at a simple report called “the mileage chart” that helps uncover cross-selling opportunities and simple cross-selling combinations.  We then describe how to prioritize and plan to make cross-selling work.

In Part 1, we looked at the human challenges of cross-selling successfully.  In Part 2, we looked at common data challenges. Later on in part 4, we will look at understanding and valuing customer behavior based on the number of categories they buy. 

To demonstrate the mileage chart, look at this example based on food, in this case a restaurant.  The example will be displayed in two ways, by counts and by percentage.  Here first is the example in percentage form:

	Appetizers	Desserts	Drink	Entrée	Salad	Sandwich
Appetizers	100%	13%	45%	84%	56%	21%
Desserts	10%	100%	41%	88%	50%	20%
Drink	11%	13%	100%	89%	54%	20%
Entrée	8%	11%	35%	100%	47%	14%
Salad	9%	11%	39%	85%	100%	15%
Sandwich	11%	13%	44%	78%	45%	100%

The report reads across, and is generated one row at a time. It is similar to the “mileage charts” in old road maps that showed distance between cities.  The highlighted numbers represent all the product buyers of one category.  The other numbers in the row represent the percentage of buyers of that column’s product and also the highlighted product in that same row.

For example, of all the customers who bought appetizers, 100% bought appetizers.  Of that 100% that bought appetizers, 13% bought appetizers AND desserts, 45% bought appetizers AND drinks, 84% bought appetizers AND entrée, 56% bought appetizers AND salad, and 21% bought appetizers AND sandwich. We start over again with desserts where 10% of dessert buyers bought appetizers, and so on.

You can quickly tell from looking at the chart which categories most (or least) commonly are bought with each other category.  Similar in thought to the “people who bought this also liked that” you often see when shopping online.

You may have noticed that 13% of appetizer buyers bought desserts and only 10% of dessert buyers bought appetizers.  That is because the total number of appetizer buyers is different that the total number of dessert buyers.  To demonstrate that, here is the same data that produced the percentage chart in counts form: 

	Appetizers	Desserts	Drink	Entrée	Salad	Sandwich
Appetizers	6,438	839	2,878	5,435	3,587	1,353
Desserts	839	8,388	3,435	7,358	4,195	1,637
Drink	2,878	3,435	26,861	23,959	14,606	5,373
Entrée	5,435	7,358	23,959	68,479	32,241	9,552
Salad	3,587	4,195	14,606	32,241	37,799	5,535
Sandwich	1,353	1,637	5,373	9,552	5,535	12,240

Now the highlighted numbers reveal the total number of customers buying in a category and the other boxes reveal the number of customers buying in the various 2-category combinations.  The most popular category is Entrée, with 68,479 customers.  The least popular is Appetizers with only 6,438 customers.

If we compare the two charts, we can see some differences in how we might develop offers by using both.  For example, in terms of total counts, more people buy entrée AND salad than any other combination.  But that is because entrée and salad are the two largest categories by customer count. 

While 85% of salad buyers purchased an entrée, on 47% of entrée buyers purchased a salad.  In terms of percentages, buyers of desserts and buyers of drinks were more likely to buy an entrée than salad buyers. 

Another way to look at the numbers is to find a cross-sell opportunity that has low cost in terms of cannibalization.  

For example, of the appetizer buyers, only 13% buy dessert.  If we can demonstrate that convincing a customer to add dessert will improve their Lifetime Value (we’ll discuss how we determine that in part 4) we have very little to lose in offering a dessert.  It will have little cannibalization of sales, and we can offer a product rather than a cash discount.

We can add to the mileage chart’s usefulness by looking at in in additional ways, for example:

1) Spending in one category versus the others.  I.e., of the people who spent a total of (let’s say) $10,000 in appetizers, they spent $500 in desserts, $3,250 in drinks, and so on. 

2) Compare 1^st visit cross-over by itself to determine which combinations appeal to new buyers, and then create a separate repeat-buyer only chart.

3) Compare 1^st visit to 2^nd visit – in this case determine based on what people bought in each category during their first visit what they bought during their second visit.  That helps us to optimize new-customer follow-up offers.

4) Compare Lifetime Value by cross-over, to optimize simple packages that attract the best customers. We can look at retention rates, average order, and longer-term value.

While the mileage chart is limited to simple cross-tab relationships, it represents a great deal of information on one page.  With a minimum of explanation, it provides useful insights to product and product managers or salespeople, and is a useful tool in management meetings and team goal-setting situations.  The same format of report can be created in several different views in order to explain different opportunities, which saves time for managers by having reports that are all read and interpreted the same way.

In the next blog, Cross-Selling Part 4, we’ll look at how to value cross-selling across categories in terms of retention rates; average sales, and lifetime value.