Machine Learning for a Less Taxing Checkout

Tax complexity is quietly undermining the checkout experience

Retailers are working hard to create frictionless shopping experiences, but tax calculation is one barrier that often gets overlooked. When customers can buy anything, anywhere, across mobile apps, brick-and-mortar stores, and third-party marketplaces, tax calculation becomes far more complex than applying a simple percentage rate. Product type, shipping destination, parties in the transaction, and jurisdiction all factor in.

Wayfair and new legislation raised the stakes

The 2018 South Dakota v. Wayfair ruling changed everything for remote sellers. States can now require out-of-state businesses to collect and remit sales tax without a physical presence. By June 2021, all 45 states with a statewide sales tax had adopted these requirements. Four years after the ruling, 58% of business leaders said marketplace facilitator laws had directly impacted how their company operates. California's e-commerce tax expansion added even more businesses to state income tax rolls, and other states are expected to follow.

Manual processes can't keep up with this pace of change. New taxing jurisdictions emerge regularly, and local governments facing economic pressure have introduced their own sales taxes on top of state rules. The risk of non-compliance and the cost of fixing errors grows alongside that complexity.

Why retailers are turning to microservices and automation

Sixty-one percent of business leaders have used microservices for a year or more, and adoption continues to grow. It's easy to see why. Automated tax engines deliver consistent, real-time calculations across every channel: point of sale, e-commerce, and mobile. All are tied to the same engine. That consistency matters in an omnichannel retail environment.

But before an automated tax engine can work, every product must be mapped to the correct tax category. For large retailers, that can mean thousands or even millions of SKUs. Done manually, it's slow and error-prone.

How Vertex Tax Categorization Service helps

Vertex Tax Categorization Service uses machine learning combined with the expertise of Vertex subject matter experts to predict the correct tax category based on past mappings. What used to be a lengthy manual process becomes a fast, data-driven one. Retailers go live faster, scale more easily as inventory grows, and reduce the risk of audit exposure. Consistent, accurate categorization across your full product catalog means fewer surprises and a smoother experience for your customers at checkout.

Tax compliance doesn't have to be a distraction. With the right automation in place, your team can focus on what matters most: growing the business and elevating the customer experience.