Blog · AI and self-service analytics
Coverage intelligence is the practice of measuring, from a company's own sales data, which customers it reaches, how much of each customer's spend it holds, and where the gaps are, with every figure reconciled to the ledger. This guide defines it, sets out its five measures, coverage, share of wallet, gap at norm, dormancy and concentration, shows how they roll up, and distinguishes it from BI, CRM reporting and sales analytics.
Companies know their revenue by every dimension and their customers by name, and still cannot say which of the accounts they should be serving they are not, or how much of each customer's spend goes elsewhere. Coverage intelligence is the practice that answers those two questions from data the company already holds. This guide defines it, sets out its five measures, and says what it is not.
Coverage intelligence is the measurement, from a company's own ledger and CRM exports, of:
with every figure rolled up from account to rep to region to company and reconciled to invoiced revenue.
| Measure | Question | Formula, in short |
|---|---|---|
| Coverage | Which accounts do we reach? | accounts touched at cadence ÷ accounts assigned |
| Share of wallet | How much of each customer's spend do we hold? | our sales ÷ customer's category spend |
| Gap at norm | What would this customer spend if it bought like our best similar customers? | norm − actual, floored at zero |
| Dormancy | Who has gone quiet, against their own cadence? | days silent > multiple × own cadence |
| Concentration | How much of the book depends on how few? | top-n share; count to half |
Each has a page on this site with the formula, the rows it needs, a worked example and where it goes wrong.
Every measure is computed at the account and rolled up:
account → rep → team → region → company
With the identity that makes the report defensible:
Σ accounts' revenue = Σ reps' = Σ regions' = invoiced revenue
If the identity fails, the report says where, before anything else is read.
The reference for share of wallet and gap at norm is not an industry benchmark. It is the company's own customers of the same size and sector where the company holds most of the business: what they demonstrably spend, per unit of size. The norm is computed from the base, stated on every line, and versioned when the method changes.
Not dashboards. Lists:
| Coverage intelligence | ||
|---|---|---|
| Business intelligence | Describes what happened | Describes what did not, against a norm |
| CRM reporting | Reports activity as logged | Reconciles activity to the ledger and the book |
| Sales analytics | Revenue by dimension | Revenue against expected, per account, valued |
| Market share | The company against the market | The company against each customer |
| Account planning | A document per account, by hand | The same measures for every account, every week |
| Export | Used for |
|---|---|
| Ledger: account, date, product, revenue | Every measure's numerator |
| CRM: account, owner, activities | Coverage, hierarchy |
| Customer master: account, size, sector | Norm, segments |
| Stated wallets, where held | Share of wallet, higher quality |
Four files. Identifiers, not names. No live connection.
An assistant can find the movements, answer a plain-language question against the tables and write the first reading. It cannot make a number right. The measures are computed in deterministic code from stated definitions, and the assistant reads and cites. That division is what makes coverage intelligence with AI trustworthy, and it is the reason the model never does the arithmetic.
One export, the ledger, produces concentration and dormancy on the first day. Add the CRM export for coverage. Add the customer master for the norm, and share of wallet and gap follow. Covirage builds the five measures from those exports as they are. The sales intelligence solution describes the setup, and the coverage guide covers the first measure in depth.
Sales analytics describes what was sold: revenue by product, region and period. Coverage intelligence describes what was not: the accounts untouched, the spend held elsewhere, the customers gone quiet. It uses the same data, adds a norm from the company's own customers, and produces lists of what to do rather than charts of what happened.
No. The ledger, the CRM export and a customer master with a size measure are enough for the five measures. A wallet estimate improves with data the customer states, but the norm method works from the company's own base.
It is a practice first and a category of tool second. A spreadsheet can do it for a hundred accounts; past that, the roll-up, the reconciliation and the weekly refresh need to be built once and run on every export, which is what a coverage intelligence tool does.