The seven-part template every measure page on this site follows, and why: the answer in one paragraph, the formula in a line, the rows needed with identifiers only, one worked table, the roll-up and its identity, the four mistakes, and the three questions answered in full. What each part is for, the order and why it is fixed, the length each part gets, and how a company can use the same template for its own definitions document.
16 Sept 20264 min readA fair account of what a spreadsheet does well for sales analysis, the point at which it stops, and the four signs a team has passed it: the same measure computed two ways by two people, a monthly refresh that takes days, a roll-up that does not reconcile and nobody knows why, and a number in a deck that nobody can trace. What changes when the measures are computed from stated definitions on every upload, and what does not need to change at all.
16 Sept 20263 min readThe five checks a commercial analyst runs on a workbook before its totals go into a deck: the SUM range covers every row, hidden and filtered rows are counted or excluded on purpose, no number is typed over a formula, the pivot matches the sheet, and the total matches the source system. Each with the symptom it catches and the one-minute test.
16 Sept 20263 min readA plain guide for a sales leader and a data protection officer evaluating an analytics tool under GDPR and UK GDPR: which fields coverage and share-of-wallet analysis actually needs, why customer and contact names are not among them, what pseudonymisation at export means in practice, the lawful basis question, the data that stays in the building, and the six questions a DPO should ask before an export leaves.
16 Sept 20263 min readWhy 'real-time' is the wrong answer to how often sales data should be refreshed, the cadence each measure actually needs, weekly for coverage and pipeline, monthly for share of wallet and concentration, quarterly for norms and segments, annually for definitions, what a refresh more frequent than the measure's cadence does to the reader, and the export schedule that follows.
16 Sept 20262 min readEvery penetration, fit, share or whitespace figure needs a denominator: what a customer like this one usually buys. This guide sets out how to build that norm from your own customers by banding them on type and size, the majority rule, the minimum band size, and how to record overrides so the gap list stays credible.
16 Sept 20263 min readWhat a data map is and how to build one from any sales export: the six roles a column can play, region, team, person, account, product, value, plus date, how to tell which column is which when the headers do not say, the columns to drop, the roll-up check that proves the map is right before anything is computed, and the mistakes that produce a map that looks fine and rolls up wrong.
16 Sept 20263 min readA practical checklist for getting a CSV or Excel export from a CRM, ERP or billing system into a state where coverage and share measures can be computed from it: one row per fact, a header row that names the column, identifiers instead of names, one date format, no subtotals, and a control total from the source system to reconcile against.
16 Sept 20263 min readA reading guide for the norm table that every gap on a report depends on: the population column that says which customers the norm was drawn from, the cell count that says how many, the greyed cells under the floor, the method column, median or percentile, the version and date, the norms that moved since last quarter and why, and the test of a good norm table, that a reader can defend any gap on the report by pointing at one row of it.
16 Sept 20263 min readA gap list is only a plan when each gap has a number beside it. This guide compares the three ways to value a missing product, account or lane, at list price, at the customer's own rate, and against an external wallet, with the cases each fits, the bias each carries, and the rule of stating the basis on every list.
16 Sept 20263 min readThe difference between a norm, computed from the company's own customers of the same kind where the relationship is full, and a benchmark, a figure from outside describing an average company, why every gap on this site is against a norm, the three things a benchmark cannot do, be defended to a rep, be applied to a specific customer, or be versioned with the base, the two places an external figure is allowed, as a wallet fallback and as context, and the rule that it is always labelled.
16 Sept 20263 min readThe difference between pseudonymised and anonymised data as it applies to a sales export, why coverage and share-of-wallet analysis needs the first and cannot use the second, what pseudonymisation at export looks like in practice, the lookup that stays in the building, what is still personal data and what is not, and the three mistakes that turn a pseudonymised file back into a named one.
16 Sept 20263 min readThirty sales and commercial measures defined in one sentence each with the formula, grouped by what they describe: coverage and activity, wallet and depth, retention and churn, pipeline and forecast, concentration and reporting, and data quality. Each links to a full definition. Written so that a team can adopt the definitions as its own, version them, and stop arguing about what a number means.
16 Sept 20264 min readWhat sales intelligence means when it is built from finance, CRM, activity, product and benchmark data a company already has: the five sources, how they join on the client, the roll-up that reconciles them, and the questions a salesperson can then ask that no dashboard anticipated.
16 Sept 20263 min readEvery measure on this site is computed from a handful of exports a company already has. This hub gives, for twelve industries, the three or four files, which system each comes from, the columns that matter in each, the identifier that joins them, and the control total to note before exporting, so that a team knows exactly what to drop before it drops anything.
16 Sept 20263 min readA practical checklist for the analyst or operations person who refreshes a coverage report each month from exports: what to export, in what order, the control totals to note before uploading, the validation lines to read after, the three failures that stop the refresh and what to do about each, and what to send the team when it is done.
16 Sept 20263 min readEvery gap on this site is measured against a norm from the company's own best customers of the same kind, and what the same kind means changes by desk: same menu type and covers, same size band and sector, same tenure band, same rig count, same property type and market. This hub gives, for twelve industries, the fields that define similar, the unit of size the norm scales by, the population the norm is drawn from, and the guide for each.
16 Sept 20263 min readA hub for the role pages on this site: for each leader, from CFO and CRO to the head of a trading desk or a foodservice distributor, the ten questions they ask, the tables that answer them, the identity behind each, and the answer to send back. This page lists every role page with the desk it is written for and the first question on it, so a reader can find their own questions in one click.
16 Sept 20264 min readThe four-level tree that every sales measure is summed through, the difference between a level and a dimension, the identity that must hold at each level, and the mapping decisions that make one hierarchy serve finance, sales operations and the salesperson at once.
16 Sept 20263 min readThe six lines a validation report on an uploaded sales file should carry before any measure is computed: the period it detected, the row and value totals against what the source showed, the columns it mapped and the ones it dropped, the roll-up identity at every level, the identifiers it did not recognise from last time, and the exceptions it will exclude. What each line catches, what a pass looks like, and why a report that says only 'upload successful' has told you nothing.
16 Sept 20263 min readABC analysis ranks customers by revenue or margin, accumulates their share, and cuts the list into tiers: A for the few that make most of the revenue, B for the middle, C for the long tail. This page gives the Excel formulas for the ranked table, the cumulative share and the tier, shows how to check whether the 80/20 rule holds for a given base, explains why the ranking should use contribution and potential as well as current revenue, and sets out what each tier should be owed in coverage so that the analysis changes what the sales team does.
17 Sept 20264 min readA step-by-step guide to building a customer cohort retention table in Excel: assigning each customer to the period of their first purchase with MINIFS, computing periods since first purchase for every invoice, counting active customers and summing revenue per cohort per period with COUNTIFS and SUMIFS, turning counts into retention percentages, reading the triangle, and the checks that prove no customer was lost on the way. Includes the exact formulas, the pivot-table route, and the point at which the spreadsheet stops being enough.
17 Sept 20264 min readA step-by-step guide to building a cross-sell or whitespace matrix in Excel from an invoice export: a customers-by-categories grid with SUMIFS or a pivot table, a bought or not-bought flag, category penetration within each customer segment, the expected categories for each segment, the gap cells where a customer does not buy what most similar customers do, a value for each gap from the segment median, and the ranked opportunity list. Includes the exact formulas, the check, and the point at which the spreadsheet stops being enough.
17 Sept 20264 min readA step-by-step guide to computing a monthly seasonality index in Excel from two or three years of sales: monthly totals with SUMIFS, each month as a ratio to its year's average, the index as the average of those ratios, the check that the twelve indices sum to twelve, and three uses: seasonally adjusting this month's figure, building a run rate that does not mislead, and spreading an annual target across months. Includes the exact formulas, what to do with one-off spikes, and the point at which the spreadsheet stops being enough.
17 Sept 20264 min readA step-by-step guide to computing sales account coverage in Excel from a CRM activity export and an account list: filtering activities to real touches, last touch per account with MAXIFS, days since last touch, the cadence owed by tier with a lookup, covered at cadence, coverage by count and by revenue per rep, the uncovered list ranked by value, and the check that every assigned account is in exactly one state. Includes the exact formulas and the point at which the spreadsheet stops being enough.
17 Sept 20262 min readA step-by-step guide to computing cost to serve per customer in Excel: choosing the cost pools and their drivers, counting drops, order lines, visits and return lines per customer with COUNTIFS, computing a rate per driver from the ledger, allocating cost with SUMPRODUCT, contribution after cost to serve, the ratio of cost to serve to gross margin, the largest driver per loss-making customer, and the check that allocated cost equals the pools. Includes the exact formulas and the point at which the spreadsheet stops being enough.
17 Sept 20263 min readA step-by-step guide to computing customer concentration in Excel from an invoice export: revenue per customer with SUMIFS, the top-ten share with LARGE, the largest single customer share, the same figures for the prior year, the pivot-table route for older versions, and the one check that proves the customer totals still add up to the ledger. Includes the exact formulas for Microsoft 365 and for older Excel, and the point at which the spreadsheet stops being enough.
17 Sept 20263 min readA step-by-step guide to computing net revenue retention in Excel from a billing export: revenue per customer in two periods with SUMIFS, NRR over the customers who were active a year ago, gross revenue retention with MIN, expansion, contraction and churn per customer, NRR by start-year cohort, and the identity that proves the movements add up. Includes the exact formulas and the point at which the spreadsheet stops being enough.
17 Sept 20262 min readA step-by-step guide to computing on-time-in-full in Excel from an order and delivery export: the on-time test with early and late tolerances, the in-full test with a fill threshold, OTIF at line level and at order level, the rate per customer with COUNTIFS, the four-state identity of OTIF, late only, short only and both, and the customer's rule beside your own. Includes the exact formulas and the point at which the spreadsheet stops being enough.
17 Sept 20263 min readA step-by-step guide to computing quote-to-order conversion in Excel: joining quotes to orders on the quote reference with COUNTIFS, a fallback match on customer, item and a date window, conversion by count and by value, conversion per customer with a minimum count, conversion by turnaround band, orders with no quote, and the check that every quote is in exactly one state. Includes the exact formulas and the point at which the spreadsheet stops being enough.
17 Sept 20263 min readA step-by-step guide to computing contract renewal rate in Excel from a contract export: contracts due in the period, the outcome per contract with a stated grace window, renewal rate by count and by prior value, contraction on renewal, the rate by renewal number, the upcoming renewal calendar, and the check that every due contract has exactly one outcome. Includes the exact formulas and the point at which the spreadsheet stops being enough.
17 Sept 20263 min readA step-by-step guide to computing win rate and pipeline coverage in Excel from a CRM opportunity export: win rate by count and by value with COUNTIFS and SUMIFS, the coverage a team needs as one over its win rate, in-period pipeline from close dates, coverage per rep against target, aged pipeline removed, and the check that every deal is in exactly one status. Includes the exact formulas and the point at which the spreadsheet stops being enough.
17 Sept 20263 min readA step-by-step guide to building a dormant customer list in Excel from an order export: last order date per customer with MAXIFS, days since last order, each customer's typical gap between orders, a per-customer threshold, the dormant flag, prior-year revenue beside each name, and the check that every customer is in exactly one state. Includes the exact formulas for Microsoft 365 and older Excel, and the point at which the spreadsheet stops being enough.
17 Sept 20263 min readA step-by-step guide to measuring sales forecast accuracy and bias in Excel: keeping a weekly snapshot table, pulling the forecast each rep made at a fixed horizon, signed error and absolute error against actuals, bias per rep across four quarters with AVERAGEIFS, mean absolute error, the team figure against the per-rep spread, and the horizon curve. Includes the exact formulas and the point at which the spreadsheet stops being enough.
17 Sept 20263 min readA hub for the industry KPI pages on this site. For each of thirty-one industries and functions, from wholesale distribution and foodservice to commercial banking, law firms, freight, pharma, SaaS and sports, one page lists the ten measures that matter, each with its formula, the export it comes from and what it tells you, plus the three measures most teams in that industry miss, the figures to drop, the identity behind each table and who should own what. This page lists them all with the measure each industry most often overlooks.
17 Sept 20265 min readRFM scores customers on recency, frequency and monetary value, and was built for consumer mail-order. This page shows how to compute RFM in Excel from an order export, with the exact formulas for the three measures and the 1 to 5 scores, then explains why the consumer version misleads in B2B, where customers order on very different cadences, and gives the three changes that fix it: recency against the customer's own cadence, frequency as a trend against the customer's own history, and monetary value read against a norm for similar customers.
17 Sept 20264 min readA hub for the Excel guides on this site: how to calculate customer concentration, dormant customers, account coverage, win rate and pipeline coverage, forecast accuracy and bias, net revenue retention, renewal rate, quote conversion, OTIF and cost to serve in a spreadsheet, from exports a business already has. Each guide gives the columns needed, the exact formulas for Microsoft 365 and older Excel, the one check that proves the result, the usual spreadsheet mistakes, and the point at which the spreadsheet stops being enough.
17 Sept 20264 min readA hub for the templates on this site: the weekly sales meeting agenda, the pipeline review, the forecast sheet with tested categories, the monthly sales report, the quarterly business review, the one-page account plan, the territory plan, the account handover checklist, the win-loss form and the lost customer review, plus dashboard examples for five readers. Each template is copyable, says which export each figure comes from, and is designed so that the document is mostly filled in before anyone sits down to write it.
17 Sept 20263 min readA hub for the benchmark questions on this site: what is a good share of wallet, customer concentration, pipeline coverage, win rate, forecast accuracy, dormancy rate, account coverage, net revenue retention, renewal rate, seat utilisation, quote conversion, OTIF, cost to serve, spend under management, realisation and hit ratio. Each page gives the ranges people quote, says what those ranges assume, and sets out the three measurable things that decide the right figure for one business. This page lists them with the short answer to each.
17 Sept 20263 min readA hub for the comparison pages on this site: churn and dormancy, win rate and close rate, pipeline coverage and weighted pipeline, OTIF and fill rate, gross margin and contribution, KPI and metric, leading and lagging indicators, concentration ratio and Herfindahl index, share of wallet and market share, renewal and retention, and more. Each page gives both definitions, computes both on the same rows, and says which to use when. This page lists them with the one-line difference for each.
17 Sept 20264 min readA hub for the worked-example pages on this site: each core measure computed in full on a book small enough to check by hand, ten accounts, ten deals, ten invoice lines, five clients, four territories, with every intermediate figure shown and the identity at the end. This page lists them by measure with what each example demonstrates, so a reader can reproduce the arithmetic before running it on their own export.
17 Sept 20268 min readA weekly sales meeting agenda built on computed lists rather than verbal updates: five minutes on the numbers that moved, ten on the accounts that need a call this week, ten on the deals that changed or stalled, and five on commitments made and kept. This page gives the agenda minute by minute, the four lists that feed it and where each comes from, what to cut from the usual meeting, the rules that keep it to thirty minutes, and a copyable template.
17 Sept 20265 min read