Quality Scores
Every flight offer returned by the Norba API carries a quality_score field — a number between 0.0 and 1.0 that says how complete the offer's data is. This page explains what the number means and how to act on it.
Why quality scores?
In the fragmented world of NDC, different airlines return varying levels of detail. Some might omit aircraft types, others might omit fare rules entirely. A quality score gives you an immediate, objective signal about how much usable data an offer contains — without having to inspect every field.
The score weighs the fields an offer carries: the ones a booking cannot proceed without count most, the ones that only make the display richer count least. 1.0 means every field the Norba offer schema defines is present. Anything lower means gaps — and a gap is left as a gap in the offer, never filled with a guess.
What the score reflects
Completeness of the offer as delivered to you: its identifiers, price and itinerary; the passenger breakdown, fare rules and fare family; and the per-segment detail — times, flight number, aircraft, booking class.
It does not reflect price, schedule quality or the airline's reliability, and it is not a ranking Norba applies. Two offers from the same search can score differently only because one came back from the carrier with less detail than the other.
quality_score: 0.0 … 1.0 1.0 = every field in the offer schema is present < 1.0 = some fields are missing; the offer says which
What it is not
- Not a measure of price or value — a cheap, complete offer and an expensive, complete offer both score 1.0.
- Not a booking guarantee — a complete offer can still expire, or be refused when you price it.
- Not stable across releases — when fields are added to the offer schema, scores can shift. Treat any threshold you set as something to revisit, not a constant.
How to use quality scores
The quality_score field lives on every Offer object returned by the Norba API. Here are practical ways to use it:
- Sort search results by score so the most complete offers appear first.
- Surface a visual indicator (e.g. a gauge or badge) next to each offer in your UI.
- Filter out offers below a threshold (e.g. < 0.5) in automated booking pipelines.
- Log score distributions to monitor airline data quality over time.