How we score
Abora shows two kinds of score, and they are built in genuinely different ways. Rather than describe them together and imply a method they do not share, each has its own page. Start with whichever number you are looking at.
Discover
“Why is this property ranked above that one?”
Eight dimensions, weighted by the priorities you set, combined into a match score out of 100. The weighting is rebuilt for every search, so the same property scores differently for different people.
Suburb profiles
“What does ‘Families 75, confidence high’ actually claim?”
Two figures on every suburb profile that work in completely different ways — one is a language model’s reading of Census data, the other is a calculated measure of how complete that data was. Neither means what people assume.
A score is a match, not a verdict
Nothing we publish says a property or a suburb is good. A Discover score says how closely something matches the brief you set; a buyer-fit score says how a suburb’s Census profile lines up with a type of household. Both are descriptions. Whether that is what you want is your call, and we do not make it.
Compare within a set, not across time
Discover’s weights are rebuilt for every search, and suburb insights are regenerated as data lands. A number is meaningful against the other numbers shown beside it, in the same view, on the same day. Tracking a single score over weeks measures our pipeline as much as the market.
The notes matter more than the number
Every score comes with the reasons behind it — which dimension gave up points, which Census figure drove a rating, what was missing. The number exists to sort a list. The notes are the actual finding, and they are what you should be reading.
A third system scores individual properties in Property X-Ray, on six fixed dimensions. That page is not written yet. If a number anywhere on Abora is not explained to your satisfaction, tell us — that is a gap worth closing. For where the underlying data comes from, see methodology.