Data Trust
How We Validate the Numbers You See
And why they may differ slightly from Amazon Ads Console.
Sellers often ask why a number in our platform looks slightly different from what they see in Amazon Ads Console. The short answer is that the two are designed for different purposes.
Our platform is built for decision making. Amazon Ads Console is built for campaign reporting. Both use Amazon data, but they may calculate or display metrics differently.
Small differences are normal. Large differences are investigated.
How we validate
Before we trust a reporting metric, we compare three independent sources:
- 1The raw data stored in our own database
- 2The values our platform displays to sellers
- 3Amazon Ads Console
Only after all three agree within an acceptable tolerance do we consider that metric trusted.
Two worked examples
When these differences show up in real campaigns, this is what they look like:
Why small differences happen
1. Attribution continues after data is pulled
Amazon keeps attributing orders for several days after a customer clicks an ad. A snapshot taken yesterday might show $16,259 in ad sales; a day later, Amazon may report $16,800 for that same date range. Neither number is wrong — Amazon simply received additional attribution after our data refresh. This is why recent dates change more than older ones.
2. Reporting refresh timing
Amazon updates its reports throughout the day. We deliberately use scheduled refreshes instead, so that everyone sees the same numbers, automation works from a consistent snapshot, and approvals are based on stable data rather than values that shift while you are reading them.
3. Different metric definitions
Not every metric inside Amazon uses the same definition. Ads Console may combine Sponsored Products, Sponsored Brands, and Sponsored Display, while certain operational metrics draw specifically from Sponsored Products because those reports carry the detail required for accurate optimization. Two values can differ slightly and each still be correct by its own definition.
4. Different business purpose
Amazon Ads Console answers "What happened?" We are building toward answering "What should I do next?" That difference changes how information is presented: rather than asking you to navigate dozens of reports, we combine multiple Amazon data sources into a single operational view covering bid and budget decisions, coupons, inventory, and profitability. The objective is a better business decision — not a copy of Amazon's interface.
Why we don't force an exact match
Forcing an exact match sounds appealing, but it would create more confusion, not less.
Amazon's own reports change over time because of attribution delays, invalid traffic adjustments, refunds, conversion updates, and reporting corrections. If a third-party platform recalculated history every few minutes, you would watch your numbers move all day.
We prioritize consistency and reproducibility instead: recommendations are generated from scheduled, settled data snapshots rather than continuously recalculated history.
Our validation standard
Our engineering team follows a simple rule:
- Our platform ↔ our database
- These should match exactly. If they don't, we treat it as a defect.
- Our surfaces ↔ each other
- Every interface we ship reads from one shared set of metric definitions — not a separate calculation per screen. If two surfaces ever disagree, we treat it as a defect.
- Our platform ↔ Amazon Ads Console
- Small differences are expected, because of reporting timing and attribution. Anything larger than those effects would explain gets investigated before we rely on the data.
What you can expect
- The values we show you are consistent across everything we ship.
- Metric definitions are shared and version-controlled, so the numbers behind a recommendation are the same numbers you see.
- Small differences from Amazon Ads Console — especially on the most recent days — are expected, and usually come from attribution timing or metric definitions.
- Our pipeline is monitored daily for failures and stale data, so problems surface to us quickly rather than sitting unnoticed.
Our philosophy
Our goal is not to build another reporting dashboard. It is to build an AI-powered business decision platform that sellers can trust.
Trust comes from transparency. When numbers differ, we explain why. Data is timestamped so you can always see how current it is. When something looks wrong, we investigate it.
Because a good decision starts with data you can trust.
Ready to make better Amazon decisions?
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