AI applied

A lead scoring system that explains itself

Client
B2B sales team running high inbound and outbound volume (under NDA)
Industry
B2B sales
Size
SMB

Results

  • What changed A score nobody trusted → a score with a stated reason, tested against past deals
  • Trained on The client's own closed-won and closed-lost history, not a generic model
  • Design choice Low-confidence leads are labelled low-confidence rather than given false precision

Described rather than measured. We publish numbers only where we have them.

The problem

More leads than the team could work, and no reliable way to decide which twenty to call today. The existing approach was a mix of gut feel and whoever shouted loudest. Off-the-shelf scoring tools gave a number with no reasoning behind it, which sales reps quite reasonably ignored.

What we did

We built an AI-enabled scoring system on their own closed-won and closed-lost history rather than a generic model. Each lead gets a score and, more importantly, a short written reason for it — the firmographic fit, the behavioural signals, the things that historically preceded a win in this specific business. Low-confidence leads are flagged as low-confidence rather than given a false precision. Accuracy was measured against a held-out sample of past deals before anyone was asked to trust it.

Start small

Three doors. The first one is free.

You should be able to find out whether we are any good without signing anything.

Free

A 20-minute call

Tell us what is not working. No deck, no discovery phase, no invoice.

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Fixed price

One first engagement

A published band, a fixed scope and a date.

See the price bands
Monthly

We run it for you

Outbound, a care plan, or an ongoing build team.

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