We’re pumped to announce that industry benchmarks are back in Triple Whale!
Yep, that’s right. You can now (right now!) see how your metrics measure up to your direct competitors. But before you dive in, let’s talk about the data. We’re peeling back the curtain on how we collect and aggregate benchmark data, the inclusion criteria, and the rigorous standards our data team has in place to ensure it’s all squeaky clean.
Our benchmarking data is collected by Triple Whale with consent from our customer base. We store and use data from the following sources:
Triple Whale formulated data would include blended metrics like Return on Ad Spend. That includes ad spend data that customers may have provided us individually, rather than just spend data collected from the Facebook and Google API’s, providing your store with a more accurate benchmark.
To answer your burning question; YES, your store’s data and privacy is protected.
No other store or competitor can tie back benchmark data to your store alone. We use a mix of anomaly detection and machine learning techniques to ensure that no single shop can skews the data set.
Again, yes! Our team took rigorous steps (read: all nighters and manual checks) to ensure that all anomalistic data points were accounted for or removed from the data set.
For example, Facebook spend and ROAS can be up to three standard deviations from the mean during popular sale periods such as Cyber Monday. Now, as all ecom marketers know, this is to be expected, and we decided to keep those special holiday datasets. However, some stores place large test orders on their site, or process wholesale orders through the same Shopify backend as their ecommerce orders. This can cause massive fluctuations in metrics such as MER, ROAS and New Customer CPA; so we cleaned all that up for you.
Because of the proactive steps we’ve taken, a new store can plug directly into Triple Whale and become eligible to review benchmark data by providing the store industry.
The criteria we chose allows you to filter our entire data set by the Industry, AOV range, and monthly ad spend range. We recommend using the filters closest to your own data points for an accurate read on your performance.
First, customers have the ability to filter by the industry of their choice. If a specific industry does not have at least 5 stores, you will be shown benchmarks that make up an “Other” category.
We’ve defined “Other” as all shops that belong to industries without enough stores to be statistically significant on their own.
Note: The following two filter segments are made up of a rolling 90-day average. This helps to ensure outliers don’t drastically skew the outcome of the metrics being displayed.
AOV (Average Order Value)
We know that these calculations can be executed a little differently depending on your business. So here’s how we do the math for the available benchmarked metrics today:
Go forth and conquer your industry! You got this.
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