Every lead carries a score from 0 to 100, shown as a small bar on the leads list. It is worth understanding what it measures, because it is easy to assume it means something it does not.
What the score is
It is a rules-based signal built from how much you know about the lead and where it came from. Broadly, a lead scores higher when it has more usable contact detail, arrived with ad tracking attached, and filled in more of what you asked for.
A lead with a name, phone, email, company and a captured click ID scores well. A lead with a name and nothing else scores poorly — not because that person is uninterested, but because you cannot do much with the record.
The part that is about the visit, not the form
Completeness alone has an obvious flaw: a bot fills every field perfectly, and a serious buyer who typed only a phone number looks weak. So for leads that arrive through a landing page carrying the tracking script, the score also reflects how the visit actually went — the one thing that cannot be faked by typing more:
- Read before enquiring — thirty seconds on the page and at least half of it scrolled. Both together, because a tab left open racks up time without attention and a short page scrolls to the bottom in one flick.
- Took their time on the form — eight seconds or more between the first keystroke and submit. Under two seconds counts against the lead: that is not typing.
- Came back — a second visit before enquiring usually means they were comparing.
- Came in on a real consumer connection — a datacenter or VPN address counts against it, which is the strongest negative available without accusing anyone.
These are small on purpose. The largest single move is fifteen points, so no behavioural signal can outweigh having a real phone number, and the figure stays explainable to a rep who asks why one lead is 70 and another 45. A lead typed in by hand, or pushed in through the API, has no visit behind it and is scored purely on completeness exactly as before.
What it is not
It is not a prediction of who will buy, and it is not machine learning. It has never seen your historical outcomes, so it cannot know that customers from one campaign close at three times the rate of another.
That comparison does exist, and it is a different screen: Audience Intelligence measures your own won deals against your own lost ones and tells you which cities, devices and hours actually convert. The score is what you sort today's list by; that is where you find out what to change.
Plenty of CRMs describe this kind of score as AI-powered. Being straight about it matters here, because a team told "the AI ranks your leads" will start ignoring low scores — and a low score usually means an incomplete form, not an uninterested person. Some of the best leads any business gets arrive with a phone number and three words.
Use it to sort, never to filter. Working highest-first on a long list is a reasonable use. Ignoring everything under 40 is not — you would be discarding people whose only failing was not filling in the optional fields.
The score is set once, at creation
It is calculated when the lead is created and does not update as your team works the record. A lead that arrives sparse and turns out to be your biggest deal of the year keeps its low score forever.
This is a deliberate simplification rather than an oversight: a score that drifted as people edited records would be impossible to reason about, and nobody would trust a number that changed without explanation.
How it differs from the traffic quality score
These are two different numbers and are easy to confuse:
- Lead score (0–100, higher is better) — how complete and well-attributed this lead is.
- Traffic quality / fraud score (0–100, higher is worse) — how likely this submission was automated rather than human. Only shown when it flags something; a clean lead displays no badge at all.
A lead can score well on one and badly on the other. A bot filling in every field produces a high lead score and a high fraud score simultaneously, which is exactly why the fraud badge exists as a separate signal. See Traffic Quality.
Improving your scores
If most of your leads score low, the cause is almost always upstream rather than in the CRM:
- Your form asks for too little. Adding one qualifying question — budget, timeline, city — raises scores and, more importantly, gives your team something to open the call with. See custom fields.
- Ad tracking is not reaching the CRM. Leads arriving without a click ID score lower and cannot be reported back as conversions. See what a gclid is.
Both are worth fixing for their own sake. The score improving is a side effect, not the reason.