Blog · Data quality and reconciliation
How to segment a B2B customer base from data the company holds: the two or three fields that make a segment useful for norms, size, sector and channel, why behavioural fields like order frequency and product mix belong in the measures rather than the segment definition, the minimum segment size that makes a norm mean something, the test that a segmentation is good, and why personas do not survive contact with a ledger.
A company has personas from a workshop and segments from a marketing tool, and neither can be assigned to a row of the ledger by rule. Segmentation for analytics has one job: to put each customer beside the customers it should be compared to. This guide sets out the fields that do that, the ones that must not, the size floor, and the test.
A segment is the set of customers whose norm applies to each other.
Share of wallet, products per customer, gap at norm, expected basket: every one of them compares a customer to its segment's norm. The segment is the denominator's definition.
| Field | Why | Source |
|---|---|---|
| Size band | Bigger customers buy more; the norm scales | Customer master: employees, sites, revenue band |
| Sector | Different sectors buy different mixes | Customer master: SIC or the company's own code |
| Channel or type | Direct, distributor, chain, independent | Customer master |
Two or three fields. All from the master, none from the ledger.
| Field | Why not |
|---|---|
| Revenue with the company | The segment becomes "customers who buy a lot from us"; the norm is circular |
| Order frequency | Same |
| Product mix | Same |
| Share of wallet | The measure the segment exists to compute |
Behaviour is what the segment measures, not what defines it.
Per segment cell, a minimum member count, thirty is common, below which the norm is greyed and the cell is merged upward. The report shows the count on every cell.
A segmentation is good when a customer's measures are closer to its segment's norm than to the base's:
spread of share of wallet within segments < spread across the base
If the segments do not tighten the spread, they are not separating anything, and the fields are wrong.
Fields: size band (3), sector (6 after merging), type (2). 36 cells; 22 above the floor.
| Cell | Members | Median products per customer | Share of wallet, interquartile spread |
|---|---|---|---|
| Large, manufacturing, direct | 84 | 5.8 | 18 points |
| Mid, manufacturing, direct | 210 | 3.9 | 14 points |
| Small, services, distributor | 31 | 1.6 | 22 points |
| Base, unsegmented | 2,400 | 2.8 | 41 points |
Within each cell the spread is a third to half of the base's. The segments separate. The norms per cell are usable, and the small services cell at thirty-one members is just above the floor and says so.
Behavioural fields in the definition. Every customer at norm; no gap anywhere.
Too many cells. Norms from six customers.
Personas as segments. Not assignable by rule; no norm.
Segments never re-tested. The spread test once a year says whether they still separate.
Mapped once, the customer master produces the segments, the counts per cell and the spread test, and every norm on the site is computed within them. Covirage builds this from the exports as they are. The sales intelligence solution describes the setup, and the norm guide covers what is computed inside each segment once it exists.
Because the point of the segment is to say what a customer should be doing, from what similar customers do. If the segment is defined by what the customer does, high-share customers are in one segment and low-share in another, and every customer is at its segment's norm by construction. The norm says nothing.
As few as give a stable norm in each. Three size bands times eight sectors is twenty-four cells; if half have fewer than thirty customers, merge sectors until they do. The report shows the count per cell and greys the ones under the floor.
A persona describes a buyer's motivations for marketing. It is not on any row of the ledger, cannot be assigned to a customer by rule, and cannot produce a norm. Segments for analytics come from fields on the customer master; personas can sit on top for messaging.