A wholesaler's sales team stopped calling cold lists and started calling scored intent

Representative examplesEvery case study in this library is an illustrative composite of the kind of engagement we deliver — written to show our method and standards, not to name clients.

Where they started

Across three regional warehouses, a trade-only wholesale distributor supplies components to installers and small contractors — no retail, no walk-ins, every account opened by an inside sales rep. The buying history of a decade sits in an aging sales database the office still uses for invoicing, while the newer CRM holds conversations and little else. The inside sales team turns over quickly, and each rep inherits a contact list from the last one, ordered alphabetically because nobody had a better ordering to offer.

What it was costing

The sales team worked a purchased list alphabetically. Rep turnover was high, conversion was flat, and the CRM — bought for exactly this — tracked activities but influenced nobody's day. Marketing sent the same nurture to everyone including existing customers.

What they could see

• Reps work the call list top to bottom — A for Accurate Supplies, B for Bespoke Fittings — regardless of who last bought, who quoted, or who lapsed.
• Existing customers receive prospect-nurture emails offering first-order discounts on products they already buy.
• New reps take months to learn which accounts are actually valuable because that knowledge lives in the sales director's head.
• Quote requests from the website sit untriaged because nothing tells anyone which request matters.
• When a rep leaves, their account knowledge leaves with them; the replacement starts from the same flat list everybody else ignores.

The constraints we worked inside

• Historic purchase data lived in an aging sales database — scoring had to use it or ignore the best signal available.
• The sales director defined 'good lead' as repeat buyers in two categories; the model had to encode his judgment, not a template's.
• Existing customers were being nurtured as prospects — the embarrassment had to end without a risky mass-delete.

What had been tried before

The team subscribed to an intent-data service that scored accounts by firmographics and web activity.

The scores never matched the accounts the sales director rated highest, and he was right — the model had never seen a decade of purchase history.

An analyst built a manual monthly scoring sheet, joining the sales database export against the CRM list.

It was accurate the week it was built and stale the week after; by month end the ordering no longer described reality.

HubSpot's built-in scoring was switched on with its template weights as a quick experiment.

Template weights reward opens and page views; repeat buying in the director's two categories — his whole definition of a good account — appears nowhere in them.

What we proposed

The plan was to turn the sales director's judgment into a model the CRM applies daily: score accounts on repeat-purchase behaviour in his two categories, quote requests, and recent web activity, weighted until the ranking reproduced the buyers he rated by hand. The lifecycle splits honestly into customer, prospect, and former customer, so nurture never again addresses account holders as strangers. The aging sales database stays the system of record for purchases — we import its signals into scoring properties on a schedule rather than migrating a decade of transactions. The team's daily call list becomes a saved, score-ordered view, so the CRM decides who gets called first.

Just as important is what we ruled out, and why:

• A third-party predictive scoring platform — Its models needed data volume the business does not have, and the director would be taking scores he can neither inspect nor adjust on faith.
• Migrating the sales database into the CRM — A decade of transactions in an aging schema is a project of its own; moving it risks the invoicing office for a benefit the scheduled import already delivers.
• Buying a fresher contact list — A better list still gets called alphabetically; the failure was ordering and relevance, not merely the contacts themselves.

How the work ran

Delivered by the systems pod — automation specialist over 7 weeks, with working increments reviewed with the client every week.

The stack, and the reasoning

HubSpot CRM

The team already worked in it; scoring had to change Monday-morning behaviour, and a new tool would have delayed that by a quarter.

Lead scoring

Transparent weights encode the director's judgment and stay adjustable when his definition of a good account changes; a black box would have been taken on faith.

Lifecycle stages

Customer, prospect, and former customer need genuinely different treatment; stage logic makes the distinction enforceable rather than remembered.

List segmentation

The daily call list and the nurture exclusions are the same segmentation viewed two ways — one for the phone, one for the inbox.

Import from sales DB

A decade of purchase history is the strongest signal the business owns; starting fresh would have discarded more knowledge than any new model adds.

What went wrong

How we worked together

Cadence

A 45-minute Tuesday score review with the sales director for the first month, then fortnightly; the weekly sales meeting got a standing five minutes on the ranking itself.

Client side

The sales director owned the model and its weights; one senior rep close to retirement acted as design partner for the call-list view.

Decisions

Weight disputes were settled by walking through ten real accounts together — if the ranking disagreed with the director's gut, the weights moved.

They provided

Export access to the aging sales database, one week of the director's annotated account ratings as the training bar, and rep time for the comparison fortnight.

What changed

The headline: calls-to-quote conversion over the first full quarter versus the prior one — +34%, read from CRM conversion reports. A second check: nurture emails sent to active customers since the lifecycle split at 0.

Monday meetings run on a ranking the director recognises as his own judgment, and new reps stop needing a mentor to tell them which accounts matter — the list says so. The nurture embarrassment ended: account holders get account-holder mail. Reps describe the working day differently — the question is no longer who to call but why the model put an account third, and that question has an answer they can read.

The result was read from CRM conversion reports against the pre-engagement baseline over the stated window, with a guardrail check on nurture emails sent to active customers since the lifecycle split. Where platform-reported numbers and business outcomes differ, this record says which layer it is quoting.

What they own now

• A written scoring model — every weight, its source signal, and the director's rationale for it.
• The lifecycle map and the list logic that keeps customer nurture away from prospects.
• The domain exclusion list and the procedure for adding to it.
• A scheduled import routine from the sales database with a documented failure alert.
• A score-ordered call-list view per rep, owned by the sales director's admin login.