How We Turned NameBio’s Keyword Dataset Into a Domain Scoring System

Most domain tools give you lists. We wanted to give you clarity. That’s why we built a scoring system using the data provided by NameBio. The goal was simple. Instead of just showing data, we wanted to answer a single question: How strong is this domain, based on real market behaviour? Not opinions. Not guesswork. Just measurable signals combined into one clear score.

Why scoring actually matters

When you’re looking at available domains, the challenge isn’t finding names. It’s knowing which ones actually matter. Without structure, most decisions end up being made using gut feel, isolated comps, or surface level keyword appeal. That works to a point, but it’s inconsistent and hard to scale. The reality is that good domains aren’t random. They follow patterns, but those patterns have always been difficult to quantify in a consistent way. That’s what we set out to solve.

How we break down a domain

Every domain is broken down into a set of core signals, each based on how keywords behave in real sales data. At the centre of everything is the keyword itself. We look at how often it appears in sales and how consistently it performs over time. This helps prioritise repeatable demand instead of one off results that can be misleading.

We then look at pricing. Some keywords sell frequently but only at low values, while others sell less often but command strong prices. The scoring system accounts for both sides so that the final score reflects quality, not just activity.

Positioning is another key factor. Where a keyword appears in a domain can significantly impact how it performs. Some keywords are stronger at the start, others at the end. By analysing historical sales across different positions, we can adjust scores based on what actually works in the market.

Finally, we look at consistency. One high value sale doesn’t define a keyword. What matters is whether it shows up repeatedly across multiple transactions. This helps filter out noise and focus on signals that are more reliable.

Turning signals into a score

All of these inputs feed into a unified scoring system. Instead of exposing raw data, we combine these signals into a single number that reflects how closely a domain aligns with proven market behaviour. The goal isn’t to overwhelm you with metrics, but to give you something you can act on quickly. This creates a consistent way to compare domains, filter large lists, and focus on names that have real backing behind them.

Why this changes how you evaluate domains

Most tools stop at giving you access to data. What you do with it is still up to you. We wanted to go one step further and turn that data into something practical. A scoring system makes it possible to evaluate domains in a more structured way. Instead of asking whether something feels good, you can compare it directly against patterns that already exist in the market. That doesn’t replace judgement, but it gives you a much stronger starting point.

How we’re using it

We apply this scoring system directly to a curated list of available domains. That means every name has already been evaluated against real sales data, keyword performance, and structural patterns. Instead of starting from scratch, you’re starting with a filtered set of opportunities that align with what’s already working.

Explore the scoring system

Want to see exactly how the scoring works and the formula behind every score?