Blog · Wallet share and penetration
How to compute products per customer from a sales or holdings ledger, why the raw average misleads, how to set the norm per segment from the customers who buy most, the gap per customer that comes out, the roll-up per rep and region, and the three mistakes: counting SKUs as products, mixing segments, and using a competitor's figure as the target.
Products per customer is the simplest cross-sell measure and the one most often set against the wrong target. This guide gives the count, why the raw average misleads, how to set the norm per segment from the company's own customers, the gap, and the roll-up.
Products per customer = distinct product lines with sales or holdings in the period
Per customer, per period, from the ledger. The product list is short and fixed: lines, not SKUs.
A base of 2,000 customers averages 2.8 products. The top segment averages 5.1; the bottom averages 1.6. Setting 2.8 as the target tells the top segment to do nothing and the bottom segment to do the impossible. The norm is per segment.
Per segment, one of:
Either is defensible. It is the company's own customers proving what a customer of that kind will buy. State which method, and use it everywhere.
Gap = segment norm − customer's count, floored at zero
And which lines are missing, from the product list, ranked by what similar customers most often hold.
| Segment | Customers | Median count | Norm (75th pct) |
|---|---|---|---|
| Large | 140 | 4 | 6 |
| Mid | 620 | 3 | 4 |
| Small | 1,240 | 1 | 2 |
| Customer | Segment | Count | Norm | Gap | Missing, most common first |
|---|---|---|---|---|---|
| 4471 | Large | 3 | 6 | 3 | Lines C, E, F |
| 2210 | Mid | 4 | 4 | 0 | |
| 9034 | Small | 1 | 2 | 1 | Line B |
Customer 4471 is three lines below what large customers buy, and the three named lines are the ones large customers most often hold that it does not. That is the account manager's next conversation, with a reason.
Per rep: customers, average gap, and gap count by line. Per region: the same. The identity:
Σ customers' product counts = Σ (customer, product) pairs with sales in the ledger
A trivial check that catches a product list applied inconsistently.
SKUs counted. A customer with sixty SKUs in one category shows sixty products and no gap. Lines, not SKUs.
Segments mixed. One norm for everyone is wrong for everyone.
External target. Somebody else's product list.
Gap without the lines. A gap of three is a number; the three lines are a conversation.
Period too short. A product bought annually shows as missing in eleven months of the year. Use a trailing twelve.
Mapped once, the ledger and the customer master produce the counts, the segment norms, the gaps and the missing lines every month, rolled up per rep and region. Covirage builds this from the export as it is. The cross-sell measurement guide applies this to banking, and the defining the norm guide covers the norm method in full.
A product line the company sells and manages as a line: a category, a service, a policy type, a fund strategy. Not a SKU. Fifty SKUs in one category are one product for this measure, and the product list is written down once.
Per segment, from the company's own base: the count held by customers at a stated upper percentile of the segment, the seventy-fifth say, or the median among the customers where the company is the main supplier. State which and keep it the same.
Because their product list is not yours. A bank with twelve products and a bank with six cannot share a target. The norm comes from what your customers demonstrably buy.