The Modern E-Commerce Marketplace: How Advanced Technologies Are Changing the Online Retail Game for Industrial Brands

Business-to-business (B-to-B) online retail sales were projected to reach $1.2 trillion last year, up from $889 billion in 2017 — and show no signs of slowing down. With e-commerce marketplaces evolving and becoming more complex, each with its own set of issues and obstacles, success in these markets is critical to a company’s growth and survival. However, navigating the complexities of e-commerce isn't easy. As a result, many online retailers incorporate advanced technological tools into their daily operations to cement their brand’s success and gain positive customer engagement.

Industrial brands are just discovering the vast potential Amazon.com and other e-commerce platforms hold. Artificial intelligence (AI) and machine learning (ML) tools are platforms that take them from later adopters to the head of the pack. New automated platforms can help brands become more competitive by rapidly gathering relevant product information, content, performance data, and pricing to maximize discoverability and strategic transparency.

Automation leveraging AI and ML help retailers streamline operations and solidify themselves as viable competitors in the race to get a piece of today’s $4.2 trillion e-retail sales pie. One way to reach this goal is to leverage automation that supplies sellers on critical platforms like Amazon with features such as automated seller responses, which allows readers to read and respond to more than 20 million reviews over the course of 60 days.

Every online business knows data is king. However, up to 73 percent of company data providing insight on operations, customers and strategy implementation go unused for analytics — which can put companies at risk for cost deficits in the form of lost revenue opportunities, lower efficiency and productivity, and quality issues. Automation platforms streamline the otherwise time-consuming process of extrapolating overwhelming amounts of data about time website users spend on the retailer’s page and what material they’re viewing. In today’s world of supply chain disruptions and labor shortages, brands must have a system in place that doesn’t require time-intensive human interaction. A robotic process automation (RPA) operates based on the brand’s internal algorithms set up with industry-specific best practices, such as processing a transaction or triggering responses, to perform optimally in each situation.

Effectively implemented, AI and ML technologies can help industrial brands navigate complex online marketplaces. Some examples include:

• AI gives businesses the ability to strategically mine product information while simultaneously creating content and utilizing performance data.
• ML tools equip industrial product brands with forecasting capabilities to make inventory control more manageable.
• AI helps predict ebb and flow demands based on geographic and historical customer data to improve ad spending on the most in-demand products.
• ML systems provide enhanced data protection and cybersecurity, reducing disruptions caused by digital breaches.

Leveraging advanced technology solutions and adding them to a brand’s toolbox can help future-proof the brand’s success and reputation while making the most of the market opportunity. By becoming more adept, quicker and more innovative in extracting specific product or customer data while handling daily queries, industrial brands can dominate the ever-evolving e-commerce marketplace.

Rohan Thambrahalli is the founder and president of UpstartWorks, a company providing technology and service solutions for manufacturers and brands to scale their B-to-B e-commerce revenue.