The Quantic Factory

When looking at sales attribution in your Shopify back-office, and then in Quantic Factory, you might notice some data discrepancies. 

There are three reasons that can explain that:

Shopify shows you direct sales that came from post-view. Those sales did not come from previous online interactions of the customer with your ads. In Quantic Factory, we only show attributed sales (sales we were able to link to a marketing source), and not direct sales that happened offline. If you have a lot of direct sales, this might cause a data gap, showing a lot more sales in Shopify than in Quantic Factory.

Shopify computes attribution by taking into account only the last click on an ad before the purchase. In Quantic Factory, we take into account several hits and channels prior to the purchase. Those hits (or interactions) are then weighted following an attribution model. The by-default model we use is the 7 days time decay model (unless you asked us to use another one, which might be relevant if, for instance, more than 20% of your marketing strategy relies on influence). So we don’t use the same calculation method as Shopify.

Shopify does not handle the cross-device as well as we do, by reconstructing the full customer journey. This might explain some of the data discrepancies between our data and the ones you see in the back office of your shop.

- Shopify shows you direct sales that came from post-view. Those sales did not come from previous online interactions of the customer with your ads. In Quantic Factory, we only show attributed sales (sales we were able to link to a marketing source), and not direct sales that happened offline. If you have a lot of direct sales, this might cause a data gap, showing a lot more sales in Shopify than in Quantic Factory.
 
- Shopify computes attribution by taking into account only the last click on an ad before the purchase. In Quantic Factory, we take into account several hits and channels prior to the purchase. Those hits (or interactions) are then weighted following an attribution model. The by-default model we use is the 7 days time decay model (unless you asked us to use another one, which might be relevant if, for instance, more than 20% of your marketing strategy relies on influence). So we don’t use the same calculation method as Shopify.
 
- Shopify does not handle the cross-device as well as we do, by reconstructing the full customer journey. This might explain some of the data discrepancies between our data and the ones you see in the back office of your shop.