Every price point kwery delivers carries a confidence score (0–1) derived from source agreement, parsing certainty, freshness, and historical stability of the listing. Scores below the publish threshold are held back or flagged so your repricing logic can decide how to treat them. Data quality details.
kwery only emits a change event when a normalized field actually moved relative to the last validated value. Re-observations of unchanged prices are suppressed, which keeps downstream repricing logic from reacting to noise. How delta detection fits the pipeline.
Data is always real-time. kwery fetches from the marketplace at the moment of request — not from a cached or aggregated feed. Every record carries an observed_at timestamp so you know exactly when it was collected. Typical end-to-end latency is under a second.
Each record passes through identifier resolution (matching the correct product/SKU), completeness checks (no missing offers or dropped fields), and sanity checks (outlier and anomaly detection on price, currency, and availability). Anything questionable is flagged rather than silently delivered as fact.
Failures surface as explicit health signals rather than silent gaps. Records that fail validation are quarantined, the affected listing keeps its last validated value, and the full event chain is available for audit. Reliability and traceability.
Yes. Every result can carry a provenance trail showing when each step happened (fetch, match, validate, deliver), the source URL, and the outcome of each check. If a number ever looks surprising, you can trace exactly where and when it came from.
Seller display variants are collapsed into one canonical identity, first-party retail and third-party offers are tagged explicitly, and price, shipping, currency, condition, and availability return the same shape on every marketplace — so you can compare like with like without per-site logic.
No data provider can honestly claim 100% accuracy from public marketplace surfaces — they change constantly. What we guarantee is transparency: every record carries a confidence score, every result is timestamped and traceable, and questionable values are flagged rather than passed off as fact.
Request API access and the team will walk through sources, volumes, and integration in detail.