Most Common Reason Your Data is Different in Amazon Vs. Ad Badger
A common question users have when using Ad Badger is, “Why are my ad spend, clicks, or revenue different in Ad Badger than in Amazon for the same time frame?”
This has a lot more to do with Amazon than it does Ad Badger– or any Amazon tool you might use.
Amazon’s Advertising API, which Ad Badger and other tools use, calculates data differently than Amazon’s Advertising Console or Seller Central does.
Is this bad? Not exactly. Ad Badger has access to additional data metrics not found inside Seller Central. For example, Ad Badger is able to pull in extra data points like 30d conversions that illustrate 30-day conversions with a single click.
Another point of difference is data delay. As you know, if you look at January’s revenue on February 1st, the numbers will be different than if you review it on February 15th. This happens in both the Advertising API and Seller Central. Amazon reports different data points and processes data differently in both.
In short, the data difference is usually so small that there is no need for concern.
48 Hour Data Delay
Amazon Advertising has a notorious 48 hour (sometimes 72 hour) data delay. This makes data from today, yesterday, and a bit of the day before unreliable. You will often see just a quarter of your orders for ""today"".
To account for this data delay, Ad Badger works this data delay into our app. So if you are looking at data that includes the past 48 hours, it might look different than Amazon.
We do incorporate this delay into all of our optimizations, to ensure we're making changes based on the best data.
What happens when a customer clicks on your ad on Monday, but doesn't buy until next Sunday? This is known as an 'attribution window' in which an order can happen and it would be attributed to the initial click.
While this 'attribution window' is open, there may be a slight different between Ad Badger & Amazon. The attribution difference is typically only 1-2%.
Ad Badger re-downloads your data to pull in the fresh attribution data on a regular basis, which eliminates the attribution difference.
Attribution Windows on Sponsored Products Placement (Top of Search, Rest of Search, Product Pages)
Fun fact about Amazon's data: the placement data we receive is set to a 14-day attribution window, where the 'normal campaign summary' is on a 30-day attribution window. It's our philosophy to use the longest attribution window wherever possible, so you never make decisions that potentially miss out on sales!
You will notice slight differences between your placement summary (top of search + rest of search + product pages) due to this attribution window, but it is typically the same, or within 1% of each other.
Amazon's Own Data Differences in their API, Search Term Reports, and Interface
The information in Ad Badger (and every app) is slightly different than Amazon Ad Console. It’s because of Amazon, not The Badger. We get our data directly from Amazon’s Advertising API. The data itself is different. Fun Fact: the data you see in Amazon’s Ad Console is different than Amazon’s own API, as well as their downloadable search term reports, etc.. They simply have different data processing for different sources. It’s close, and if you ever notice it being significant, let us know.
For sponsored products, Ad Badger uses a 30-day window, compared to the Amazon Ad Console attribution window of 14-days. We believe this gives you the most accurate data and reduces the risk of negating a keyword or downbidding on something that wasn’t reported on Amazon, but you indeed have sales for. This means that Ad Badger will have more conversion data available than Amazon’s Ad Console. Do note: we get this data directly from Amazon. We don’t know why they chose to display a shorter attribution window, but we assure you our data is accurate, and directly from Amazon’s API. For the product performance dashboard, Ad Badger uses same-sku attribution, to show you the purchases made on the product that received the sale.
If you have questions, please contact us at email@example.com.