What is Focused Score and how does it evaluate my traffic?

Bread & Butter's Focused Score does not calculate a generic number from static rules. It uses a continuous machine-learning feedback loop to evaluate the real buying intent of your visitors, processing thousands of overlapping data points including granular, proprietary heatmap engagement, and it adapts to your specific business.

In short: Focused Score builds a scoring model unique to your website rather than applying universal rules, so visitors are ranked relative to one another and scores spread evenly across a 1 to 10 scale. Scoring starts from the first visit and the Focused Tab fills as soon as visitors score 6 or higher. What takes fifteen days is calibration, establishing your Focused Ratio so it can be compared against the Focused Index. From there the model keeps improving every time you mark a profile Won/Closed, which teaches it what your actual buyers look like and recalibrates your Ideal Customer Profile automatically.

Scores are relative and unique to your website

Focused Score does not use a universal truth or a standard set of generic rules, such as five points for visiting a pricing page. Your model is built entirely around your own website, its architecture and its purpose.

The model evaluates your visitors relative to one another, whether your site is an ecommerce storefront, a content-heavy blog or a B2B software site. Because it is relative, scores are distributed evenly across a 1 to 10 scale using decile ranking. You will see roughly the same percentage of visitors scoring a 10 out of 10 as you will see scoring a 5 or a 1. The system is actively ranking your traffic to show you who is engaging the most compared to your own average visitor.

What relative scoring means in practice

A 10 on your website is not the same as a 10 on someone else's, because the score answers "who among my visitors is showing the most intent", not "how does this person compare to the internet".

Scores can shift as your traffic mix changes, for example when a campaign brings in a wave of low-intent visitors. That is deliberate. A universal grade would be easier to explain and far less useful, because the behaviour that signals a serious buyer on a B2B software site looks nothing like the behaviour that signals one on an ecommerce storefront. If you want to know how your traffic compares to everyone else's, that is what the Focused Index is for.

Scoring starts on day one

Focused Score is live from the first visit after installation. There is no waiting period before scores appear on profiles. Every visitor is evaluated against the others on your site as they arrive, and the ranking sharpens as traffic accumulates and the model sees more of what engagement looks like on your pages.

The Focused Tab also works from day one. It filters out the noise and the bots and shows you the visitors who have reached a Focused Score of 6 out of 10 or higher, so it starts filling as soon as your first serious visitors score.

What the fifteen days is for

What takes fifteen days is calibration, not scoring.

Your Focused Ratio is the share of your traffic that scores as high intent. On its own that number tells you little. It becomes useful when it is compared against the Focused Index, the benchmark across the whole Bread & Butter network, and establishing a stable ratio for your site needs a representative sample of traffic.

That is why the Focused Index Benchmark shows a fifteen day calibration period after installation. During that window scores are live and the Focused Tab is populating. The comparison against the network unlocks once calibration completes.

How it improves over time, the Success Factor

The model gets sharper over time, and the single most effective way to speed that up is to mark profiles as Won/Closed in Lead Stages.

Marking a lead Won/Closed is how you label the training data. Without labels, a model can only tell you who behaved unusually. With them, it can tell you who behaved like someone who bought. By marking Won/Closed you are setting the Success Factor for the machine. The model immediately looks back across the entire journey of that winning user, analysing thousands of data points, behaviours and firmographics, and recalibrates your Ideal Customer Profile. That removes the guesswork and lets it constantly adjust its scoring weights to find more visitors who act like your actual buyers.

The Won/Closed tab appears in your dashboard once you have marked at least one profile at that stage. The first profile you mark is what turns the tab on.