Sentient AI – Ecommerce Personalization

It is clear that the convenience of ecommerce is rapidly displacing the need for brick-and-mortar stores. Just as digital media delivery platforms killed the video-rental store, so too are clothing, electronics, and other retailers transitioning the bulk of their customer experience online.

This is easier said than done, as one-stop-shops like Amazon have made it difficult for retailers dedicated to a single brand or category of product to establish themselves. To gain a competitive edge, there has been a move among ecommerce shops to create more interactive and curated shopping experiences. To do this, many stores have integrated artificial intelligence software into their websites to help provide more ecommerce personalization.

Similar types of technology have long been in use by online ad providers to create a sort of footprint or profile of users in order to deliver to them more relevant or appealing advertisements. It is a model that works, catering content to customer interests and ultimately optimizing conversion rates. In other words, ecommerce experiences customized through artificial intelligence turn more clicks into repeat customers.

How exactly artificial intelligence has shaped and enhanced ecommerce personalization is fairly varied. One of its most important features is the software’s ability to observe customer viewing and shopping patterns and in turn offer recommendations of other products based on this data. Upselling used to be the domain of salesmen in face-to-face interactions, but the increased sophistication of artificial intelligence has enabled web stores to not only replicate this, but to also provide more useful suggestions to customers than simply recommending more expensive purchases or tangential add-ons.

As an example, online clothing stores can recommend complementary products, leading a customer from buying just a shirt into purchase an entire outfit. Artificial intelligence also has the ability to better retain or produce repeat customers. By tracking a user’s browsing habits, how long they view a specific item’s page, and other data, the customer can be automatically contacted via email should an item relevant to their interests go on sale? Given that, on average, a little over 30 percent of these leads aren’t followed up on by sales staff, AI automates this whole process and reaches out to the customer in a format that feels unobtrusive.

The success of personalized shopping experiences online is clearly supported by the data. Retailers who use this strategy on average show a 6 to 10 percent increase in sales, while the industry as a whole expects to see sales increase by as much as 59 percent by 2035 in both the retail and wholesale industries. Given these projections it’s clear that AI’s role in retail and ecommerce personalization is not only secure, but will likely expand in the future.

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