Lead scoring in practice: how to sort your call list with an A–D grade
How BaseOS's lead scoring model works: points for behaviour, profile-fit signals, decay and caps — and how the A–D grade sorts your call list without inventing priorities.
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Every sales team has its own way of deciding who to call first. It is almost always a mix of memory, intuition and order of arrival: whoever shouted loudest this morning gets called first. Lead scoring exists so that this decision is made with visible, debatable data — not by eye.
In BaseOS, scoring combines two different questions — who this contact is and what they have done lately — and turns them into an A–D grade that sorts your list for the day. This guide explains how the model works, with its real default values, and how to tune it to your sales cycle.
Two halves: fit and behaviour
Fit answers "is this the kind of customer we are looking for?": static data about the contact and their company. Behaviour (interest) answers "what has this contact done lately?": web visits, email opens and clicks, messages, replies, product signups.
A contact can have great fit and zero behaviour — the ideal manager who never opens an email — or lots of behaviour and poor fit — the enthusiastic reader who will never buy. The score joins both halves so you can tell them apart before you waste an afternoon on the wrong one.
How much each action is worth
Every interaction adds points according to a rule table. These are the model's default values:
- Convert or pay on the web: 30–40 points.
- Reply to an email or message: 25.
- Sign up or activate in the product: 20.
- Click an email or message: 10.
- Visit a page: 1–5.
- Open an email: 3.
The logic behind the scale: replying is worth far more than opening, and a commercial action — converting, paying — is worth more than any content signal. If your team thinks a click should count more than a reply, change the rule: it is a row in a table, not code.