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How to Know When Amazon's Advertising Data Isn't Right

Why no data provider can independently verify Amazon Advertising API accuracy - and what to look for when reported data may be compromised.

M
Mixshift
May 19, 2023
2 min read

Data accuracy in Amazon PPC tools and reporting dashboards is a critical concern for agencies and brands alike - but it's one that doesn't get enough attention.

The Core Problem

The truth is no data provider or Amazon PPC tool can know if there is an issue in the reported advertising data unless Amazon tells us that's the case.

This isn't a limitation of any specific tool. No data provider can independently verify Amazon Advertising API data accuracy without official notification from Amazon. The data flows through Amazon's systems, and if something is wrong at the source, downstream tools have no independent way to detect it.

Real Consequences: Black Friday and Cyber Monday

This isn't a theoretical concern. During Black Friday and Cyber Monday, there have been incidents where advertisers over-spent due to glitches in Amazon Ads data. Reporting errors during the highest-volume advertising days of the year can have serious financial consequences - budgets exhausted faster than intended, automated bid adjustments made on faulty data, and performance analysis that doesn't reflect reality.

What Responsible Tool Providers Should Do

Tool providers should proactively alert users when Amazon identifies data problems. Without timely notification, agencies and brands continue making budget allocation decisions and running automated optimizations on data that may be fundamentally unreliable.

MixShift's Approach

MixShift commits to acting as the first line of defense when there is an issue our partners should know about. When Amazon notifies us of data complications, we alert users immediately - before those issues can affect decisions.

The value isn't just in having good data when things are working. It's in knowing when data reliability is compromised before you make a significant business decision on bad numbers.