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Blog · Wallet share and penetration

Separate existing-account wallet movement from customer mix

Explain a book's wallet-share movement using a fixed account cohort and separate new and lost customers. Reconcile each step to sales and wallet totals.

The short answerCompare wallet share for accounts present in both periods, then show new and lost accounts separately. Build the aggregate change as explicit steps using summed sales and wallets, not an average of customer percentages. A falling book share can result from low-share new customers even when existing-account share is unchanged; the fixed cohort reveals which effect occurred.

Share-of-wallet fixed-cohort analysis separates changes inside existing accounts from changes in the customers included in the book. A new customer often starts at a small share. Adding many such accounts can reduce the aggregate percentage while expanding revenue. Losing a high-share account can move the percentage in the same direction for a very different reason.

The market-share comparison explains why those measures differ. Here the question is narrower: why did one book's wallet share change between two periods?

Declare the account population first

Choose whether the report covers active customers, all addressable accounts or an agreed portfolio list. Record how inactive, newly acquired, merged and transferred accounts are treated. A customer with no order for one month is not necessarily lost.

Start from stable customer IDs and dated ownership mappings. Use the same category, period length, currency basis and wallet source policy. Account transfers between reps change a rep's mix without changing the company's underlying customer economics; flag them separately.

The customer hierarchy guide explains entity mapping. For this comparison, retain the identity crosswalk used in both periods rather than rebuilding last year with an undocumented current hierarchy.

Divide the union into three groups

An account is continuing when it belongs to both declared populations, new when it belongs only to the second, and lost when it belongs only to the first. The labels describe population membership, not necessarily commercial causation.

Keep accounts whose wallet is unknown in an evidence-exception population. Do not give them a zero wallet or quietly drop their revenue. The wallet-evidence coverage guide shows how to disclose the resulting coverage.

For the complete measured population, check:

Opening sales = continuing opening sales + lost opening sales

Closing sales = continuing closing sales + new closing sales

Apply the same two identities to wallet totals.

A synthetic active-book example

Amounts below are annual USD thousands. The category and reporting periods match; continuing-customer wallets are deliberately unchanged to isolate the mix effect.

Group Opening sales Opening wallet Closing sales Closing wallet
Continuing accounts 400 1,000 350 1,000
Lost accounts 100 200 Excluded Excluded
New accounts Not present Not present 50 500
Active-book total 500 1,200 400 1,500

Opening active-book share is $500,000 / $1,200,000 = 41.67%. Closing share is $400,000 / $1,500,000 = 26.67%. The headline fell 15 percentage points, while the continuing cohort fell from 40% to 35%.

Reconcile an ordered percentage-point bridge

Use this stated order: remove lost accounts, update continuing accounts, then add new accounts.

Step Sales Wallet Share Change from prior step
Opening active book 500 1,200 41.67% Starting point
Remove lost accounts 400 1,000 40.00% −1.67 points
Update continuing cohort 350 1,000 35.00% −5.00 points
Add new accounts 400 1,500 26.67% −8.33 points

The effects sum to −15.00 points before rounding. They describe the selected bridge order, not unique causal contributions. Preserve unrounded calculations and round only the displayed figures.

Distinguish within-account change from cohort mix

Even the continuing group's percentage can move because the relative wallet sizes of its accounts change. Investigate each customer's sales and category-spend changes using the within-account decomposition. Keep that diagnosis separate from entry and exit from the book.

Segment results by consistent business characteristics. Re-segmentation is a reporting change, so show it alongside acquisitions, owner transfers and refreshed wallet estimates. Otherwise a new segment definition can appear to be selling progress.

Reproduce the review from rows

Use a customer-period table and explicit cohort labels. Microsoft's SUMIFS documentation supports conditional group totals; its SUMPRODUCT documentation covers weighted arithmetic. Neither substitutes for a declared population.

Conclude with separate actions for continuing-account deterioration, genuinely lost relationships and new-account development. Discuss the cohort definitions and required exports with Covirage. A reconciled movement report is evidence for a commercial review, not proof that every observed change was caused by account-manager activity.

Questions people ask

Should a lost customer's wallet disappear from the comparison?

It depends on the declared reporting population. An active-customer book excludes a genuinely lost account from its current total but shows the removal in the bridge. A fixed addressable-customer population can retain it with zero sales. Never switch between those definitions without disclosure.

Is the order of a wallet-share bridge important?

Yes. Removing lost customers before adding new ones can allocate percentage-point effects differently from the reverse order. State the order and retain the sales and wallet totals at every step; the final endpoints must still match.