Rohan Thambrahalli |
To accurately process the immense volume of data points on Amazon.com, B2B companies should use such advanced technologies as artificial intelligence, robotic process automation, and machine learning, writes Rohan Thambrahalli, president of DimeTyd.
The B2B ecommerce world is expanding at an exponential pace. COVID-19 and its aftereffects changed online commerce in countless ways—consumers flocked to ecommerce for necessities, and business buyers expediated their migration to ecommerce to continue business operations.
The B2B ecommerce market has ridden a wave of unparalleled growth. A recent Insider Intelligence study reported that U.S. B2B ecommerce sales will cross the $1 trillion mark for the first time in 2022. When it comes to the B2B e-commerce world, Amazon stands front-and-center as the leader of online purchasing. By 2023, RBC Capital Markets expects Amazon Business, an Amazon B2B marketplace, will take over the $67 trillion B2B industry and generate sales of $52 billion.
While Amazon serves as a conduit for billions in B2B ecommerce, countless inefficiencies lurk within the accounting processes of ecommerce. Amazon’s Marketplace is a layered mosaic of complex data streams, opaque vendor rules and agreements, and a maze of shifting regulatory policies, often unseen by Amazon Vendors. It can easily result in lost profits and a damaged bottom line.
To maximize profitability, B2B product companies are grappling with how to solve undetected accounting errors, profit leakage, and overbilling amid thousands of complex transactions that are nearly impossible to dispute manually. In fact, the needed time to track and reconcile Amazon accounting errors could take years. Even the largest vendors are unlikely to have the necessary capacity to manually process the equivalent of millions of data points on the Amazon platform.
New Tools for Online Success
To address these challenges, B2B product companies are turning to advanced technologies such as artificial intelligence (AI), robotic process automation (RPA), and machine learning (ML). These innovative tools help B2B product companies streamline ecommerce workflows and safeguard against a myriad of potential hazards while identifying, generating, and optimizing revenue.
Amazon invoicing is laden with its own unique set of formidable demands. RPA and ML models allow product companies to simplify complex rivers of data, automatically reconcile accounting errors, and identify return discrepancies. These tools eliminate duplicate financial reports, resolve billing disputes, and automatically match invoices with the correct purchase order.
Furthermore, RPA aligns a vendor’s system to Amazon’s accounting matrices with precision and accuracy. It helps find and eliminate incorrect duplicates and missed invoices. RPA provides needed transparency, correcting overbilling and missed deductions that result in lost profits and revenue leakage. Automation also eliminates potential human errors—creating far more accurate reconciliations while decreasing workforce hours needed to manually audit data. By incorporating automation into the accounting process, product companies gain back time and resources to concentrate on other mission-critical business areas.