Artificial intelligences and artificial neural networks are seeing increasing use in all spheres of web design, from graphic design to generating code. While all these implementations are interesting in their own rights, ecommerce platforms are poised to take unique advantages of the power of AI to significantly grow revenue. We’ll take a closer look at three of the emerging applications of AI in ecommerce—two customer-facing and one internal.
The most accepted and adopted use of artificial intelligence in online commerce is the chatbot. They’re becoming so ubiquitous that in 2020, more than half of all ecommerce platforms use chatbots to reinforce existing customer service representatives. And it’s far more than a cost-saving measure. Chatbots significantly increase response time to customer inquiries, which equals quicker turnover of merchandise. Additionally, a growing number of shoppers prefer interacting with chatbots, which helps to drive engagement and grow cart sizes. Most interestingly, chatbots can make timely, relevant upsells by analyzing customers’ questions, shopping history (for returning customers), and other data points. The power of recommending the right products at the right moment cannot be overstated.
That leads nicely into the next growing function of AI in ecommerce—personalized product recommendations. When customers create accounts for ecommerce platforms, AI-driven processes begin compiling demographic information, shopping history, traffic on the site, etc. to make shockingly personalized product recommendations. While some consumers express concern about the high degree of accuracy of the recommendations, anecdotal evidence suggests they grow revenue by 10% or more. Personalized recommendations also benefit shoppers; instead of combing through dozens (or more) of products with slight variations, shoppers are presented immediately with the handful that would have comprised their shortlist. That reduced effort means less frustration for consumers.
That covers two customer-facing implementations of AIs, but they’re also seeing growing use in internal ecommerce functions—especially inventory and ordering. The inventory functions are obvious; AI can count and compile complex inventories significantly faster than humans, and they do it with many fewer errors. With less lost or miscounted product, retailers will need to allocate a smaller portion of their budget to losses. But AIs can also significantly reduce the amount of wasted money and space incurred by unsold inventory by improving ordering. Much like they can be used to make personalized shopping recommendations to consumers, they can also make intelligent recommendations to retailers about which products (and in what quantities) to stock based on what their store sells. AI-driven inventory management can increase revenue and decrease expenditures.
Taken together, these three implementations make the benefits of AI in ecommerce clear. In the coming year, you shouldn’t be asking yourself why you’d want artificial intelligence assisting your store and your shoppers. You should be asking yourself how you can implement AI-driven solutions as quickly as possible.