AI for insights and analytics
A building materials distributor sells to trades that each buy a known basket. AI analytics compares every account with the trades like it, finds the categories a general contractor buys elsewhere, watches credit headroom and quote conversion, and answers in figures that tie to the ledger.
These are the questions building materials distributors ask. Each one maps to a measure our tools compute from your files. The AI model chooses the measure and explains the result; the arithmetic is done by our code, and every total is checked.
| The question | The measure behind it | What comes back |
|---|---|---|
| Which trade accounts buy a category from someone else? | Category share by trade | Each account's category mix against the norm for its trade, with the gap valued at the account's own spend. |
| Which trade accounts have gone quiet? | Dormant trade accounts, by prior value | Accounts past their own order gap, by prior-year value, branch and rep. |
| Who is about to hit their credit limit? | Credit limit headroom | Headroom by account against its run rate, with the ones that will stop being able to buy this month. |
| How much quote value are we losing, and to whom? | Quote conversion, count and value | Conversion by count and value per customer and branch, with the lost value listed. |
| Are we invoicing at the agreed terms? | Price realization against terms | Invoiced against agreed prices by line, with leakage by branch and account. |
| Which projects in the pipeline match accounts we hold? | Project pipeline matched to accounts | Building permit and project leads matched to existing accounts, with the estimated spend and the current share. |
Every figure below was computed by a tool from the rows and checked before it was shown. The lines sum; the percentages match; each line opens to the rows that make it.
Where are our trade accounts buying elsewhere?
The category gap against trade norms is worth $2.7m a year across 3 trades, valued at each account's own spend. General contractors accounts hold $1.4m, 52% of the gap.
| General contractors | $1.4m | 52% of the total |
| Excavation and site work contractors | $800k | 30% of the total |
| Roofers | $500k | 19% of the total |
| The 3 lines sum to | $2.7m | 0 unexplained |
Which general contractors have the biggest gaps?
3 accounts hold $221k of the $1.4m gap among General contractors, 16% of it. All three buy lumber and panels from us and little or no aggregates, where full-supply general contractors spend a fifth of their basket.
| Redmayne Construction | $96k | aggregates 0% against 18% norm |
| Hollis & Sons | $74k | lumber 12% against 32% norm |
| Parkside Builders | $51k | aggregates 3% against 18% norm |
| These 3 are | $221k | 16% of General contractors |
How do we turn that into orders?
Each account gets a category conversation, not a discount. The rep takes the basket comparison, the delivery slot and the credit headroom, and the branch tracks whether the category appears on the next invoices.
| Branch managers | Visit the three accounts with the basket comparison | Within two weeks |
| Credit control | Confirm headroom on each before the visit | This week |
| Regional sales manager | Track category share by trade monthly | Monthly |
Each measure has one formula, one source and one meaning. They are computed per branch and rep and in total, and every one carries an identity that must hold before it is shown.
| Measure | Formula | From | What it tells you |
|---|---|---|---|
| Category share by trade | Account spend in category ÷ account total, against the median for full-supply accounts of the same trade, for categories most of that trade buys | Ledger with category; account master with trade | The general contractor buying no aggregates; the plumber buying no fittings |
| Account activation | Accounts opened with a second purchase within 90 days ÷ accounts opened, by branch | Account master; ledger | Accounts opened and never used |
| Dormant trade accounts, by prior value | Prior-year revenue of accounts past k × own order gap ÷ prior-year revenue | Ledger | Trade customers who moved to another distributor |
| Credit limit headroom | (Limit − balance) ÷ limit, with payment record; accounts over 85% used and paying to terms | Credit file; ledger | Good customers who stopped because they hit the limit |
| Project pipeline matched to accounts | Value of building permits and project starts matched to trade accounts, by branch market area | Building permit or project data; account master | Which customers have work coming, and where |
| Quote conversion, count and value | Quotes matched to orders ÷ quotes decided; by value | Quote log; order file | Project quotes that went elsewhere |
| Branch coverage of key accounts | Revenue of key accounts touched within cadence ÷ key account revenue | CRM or call log; ledger | Whether the top trade accounts hear from the branch |
| Price realization against terms | Invoiced price ÷ agreed terms price | Ledger; terms file | Terms not applied; counter overrides |
| Delivered and pickup mix | Delivered revenue ÷ total; average delivered drop value | Ledger; delivery file | Cost to serve; small drops to job sites |
| Contribution per account | Gross margin − rebates − cost to serve | Ledger; delivery and order files | Accounts that earn after what they cost |
Each measure is worked through, with the export it comes from and what to drop, in Sales KPIs for building materials distributors and construction suppliers.
From your question and the measures declared for construction and building materials, the model picks the one that answers it, and the period and comparison the question implies.
Deterministic code reads the rows, computes the measure, and checks the identities below. The same question on the same data gives the same answer, every time.
The AI model writes the sentence around the result, naming the branch or account behind it. It states no figure that is not in the result, and every figure links to its rows.
| Category share | Category spend sums to the account's ledger total; every account has one trade or is counted as untyped |
| Activation | Accounts opened = activated + not yet activated within window + window still open |
| Credit headroom | Balance ties to the receivables ledger |
| Quote conversion | Quotes = converted + lost + open |
The exports building materials distributors already produce. Column names are mapped once and the mapping is reused. A file is the way in; scheduled delivery and connections to your systems come with the plan, and every source is listed here.
An answer is a list with an owner and a cadence, or it is a chart nobody works.
| Measures | Owner | Cadence |
|---|---|---|
| Dormancy; key account coverage; credit headroom list | Branch manager; regional sales manager; credit control | Weekly |
| Activation; quote conversion | Branch manager | Monthly |
| Project pipeline | Outside sales; branch manager | Monthly |
| Category share by trade; price realization; contribution | Commercial director | Quarterly |
The median category mix of accounts in the same trade at your own branches, computed from your ledger. A general contractor is compared with general contractors, an electrician with electricians. That is why an electrician buying no aggregates is no gap at all, while a general contractor buying none is a large one.
Yes. With the credit limit and balance file, headroom is compared with each account's run rate, and the accounts that will reach their limit inside the month are listed with the amount. The conversation happens before the counter refuses the order, not after.
Every measure is computed per branch and in total, and the totals reconcile. An account that buys from two branches is one account with two locations, rolled up for share and concentration and split for coverage and quote conversion.
The invoice ledger with a trade code on the account. It gives category share, dormancy, price realization and concentration on its own. The quote log, the credit file and any project lead data each add a question they alone can answer.
Trade norm · Expected basket · Credit headroom · Quote conversion · Dormant account · Price realization
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Bring a few thousand rows. The data map opens next, every column mapped once, and the first question is answered in minutes. Free, in your browser, no account.