Machine Learning for a Less Taxing Checkout

How tax categorization services remove friction from retail experiences

Two women in work aprons standing in front of their checkout computer in their flower shop. The woman in the foreground is showing her business partner information on a tablet. Light illuminates them from a window in the right side of the image, highlighting greenery and a string of purple flowers.

Today, there are a lot of possibilities for friction in tax calculation because you can buy anything, anywhere—via mobile app, brick-and-mortar, third-party marketplace, etc. as well as through a combination of these channels within the same transaction.

To calculate tax, retailers can’t simply just multiply a percentage rate on the price. Tax rates depend on various factors such as what type of product it is, where the product is being bought, where it’s getting shipped, who are all the parties involved in the transaction, and more. Adding to this complexity are the waves of recently passed laws that have a significant impact on the way retailers operate. 

This eBook walks retailers through how tax calculation can significantly contribute to online friction and how machine learning-powered tax services can help retailers navigate tax calculation for an assortment of ecommerce products.

Fill out the form below to download the Machine Learning for a Less Taxing Checkout eBook.