#### Laying the Foundation for Future Analysis

Distribution is one of the foundational metrics for most businesses that do not have their own proprietary methods of retail. Regardless of how well their products are made or marketed, these companies depend on their distribution partners to reach their end consumers.

Mastercard and Visa, the two giants of the payments industry, are two great examples of how even massive brands depend entirely on distribution to keep business flowing. Both of these brands rely on banks around the world to get their products in the hands of consumers. Distribution metrics represent the foundation of their “vital signs” for both brands.

This week, we’ll take a look at the three basic forms of distribution analysis which can give you a starting point for some of the more advanced analysis we’ll be tackling later.

### Numeric Distribution

Starting with the most basic metric, **Number Distribution** represents a simple calculation of the number of retailers your business has partnered with versus the total number of retailers in any given category. In the case of Mastercard and Visa, this would be calculated by dividing the number of banks with which they have a relationship within any particular market by the total number of retail banks in that market.

While this metric is simple enough to calculate, there are significant limitations to the conclusions we can draw from its analysis because the metric does not weight the size of the opportunity with each partner.

### All Commodity Value

For a metric that begins to help us add more color to the state of our distribution, we turn to **All Commodity Value** or AVC. This calculation takes the total of the revenue at each of our retail partners and divides it by the total revenue of all retailers. This practice allows us to add weight to each retailer, showing us if our partners represent more or less of the total pie. Back to our Mastercard/Visa example, this metric would place a higher value on distribution with a massive bank, like Wells Fargo, versus a smaller, regional credit union.

However, this metric also has its own limitations due to a lack of context. While we can begin to understand which distribution partners are more valuable, we can’t see the whole picture.

### Product Category Value

For more of the picture, we need to turn to **Product Category Value** or PVC. This metric compares the total revenue within a particular product category of each distribution partner versus the total revenue within a particular product category of all retailers. In the case of Mastercard and Visa, this would involve looking at, for example, just the consumer credit revenues of their partners versus all banks. This allows you to understand the size of the slice of your specific pie.

### Going Beyond

In the case of the payment giants, the next steps of distribution data analysis would begin by placing additional weights for each of their distribution partners according to how much of each bank’s total business they make up, in order to understand just how much market penetration they have. However, in many cases, it is exceedingly difficult to come by the more granular data which allows you to calculate ACV or PCV. Therefore, you will need to be comfortable with using Numeric Distribution as just one data point in otherwise more complicated data analysis.