True e-commerce sales tracking vs estimates

Why our competitors are selling unreliable sales data

Do not index
Do not index
A customer recently pointed my attention towards yet another competitor of ours, called SaleSource (for a full list of our competitors, check this article).
This customer asked me how SaleSource compares to Cart.
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As you can see from the screenshot above, Salesource guys self-report the software as "The best all-in-one eCommerce software", which in my opinion is highly dishonest and not backed by any data. Are they really the best? Who says that?
The first difference was very easy to spot: SaleSource publicly claims to have a database of 10k Shopify merchants and more than 1M products, while we track 1.5M merchants to date and 42M products.
Aside from this, what really caught my attention was the way they handle sales data. They give their customers estimates. This is not something they do exclusively. In fact, it's not uncommon that other competitors do it using the same strategies.
One strategy they use to get to a sales number involves the number of monthly visitors a store has. Usually, they get this number from popular sources like Alexa or Similarweb, and usually, that number is also an estimate.
Here is what they do: they take the number of monthly visitors to a store and multiply that number by the industry conversion rate to get an estimated amount of sales. This way is completely unreliable.
Some other times competitors use another strategy to get an estimate of sales: they get the number of sales from Aliexpress. While this strategy is more reliable than the other one I just described, this strategy is also an unreliable way to get an idea of sales, because even if a product may sell well on Aliexpress does not mean that it will sell well on your store.
We use what we call "true sales tracking" instead, which involves directly taking sales data from stores.

True sales tracking

 
What we do instead: we take anonymous and non-anonymous sales data directly from stores using our own technology.
While we cannot do this for every store on the planet, we can do it for a large and increasing number of stores, and the sales data we get is very detailed. We know exactly who buys, from where, when, how much he/she paid, and more.

Why our competitors' predictions are so far off

 
For example, here is what our competitors say about a Shopify store I respect and a brand I like, Gymshark:
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According to our competitor Intelligynce, Gymshark makes $5k - $22k/day, whereas Salesource says they do $6M - $12M per month in revenue. A big difference in ranges here.
This is so far off from reality. They could have easily done a Google search to learn that Gymshark reached $50 million in revenue in 2017 and hit $100+ million in 2018. By the way, Gymshark' statements of income are public.
Our competitors missed the reality of only about $90M in revenue =)
Now, it's one thing to say that a store probably does $X amount of revenue in a year and another thing to tell you exactly how much a product is selling in that store. That's what we do!
Here are Gymshark.com sales for a particular product, as we display them on Cart:
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And here is a rundown of that product's sales by variants!
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So, as it turns out, Gymshark made $20k of sales on this product only, in less than 20 days (the time we were tracking this product), just on the US store.
We also know that the "small" size is selling far better than any other size and they had very few returns on this product.
That's why Cart is on another level when it comes to sales tracking.
Gymshark has hundreds of products in different online stores that target different regions and countries. That's why our competitors' estimates of sales are so far off!

Your choice

 
Gymshark is a big brand. It's easy to just pull revenue data with just a Google search but I've shown you how competitors are shooting in the dark. Imagine what kind of unreliable data they can give you in a small store.
I'd like to leave you with a question: would you rather base your research on estimates or real data?
 
Thanks for reading,

Written by

Mike Rubini
Mike Rubini

Founder at usecart.com