The eCommerce industry was already on par to be worth just shy of $5 trillion by 2021 and a staggering 96% of Americans have bought an item via online commerce. The industry is well on its way to becoming an ever-increasing part of how we all shop and that shopping is cutting across more and more categories. A recent survey by consumer intelligence firm Resonate, revealed 55% and 41% increases in consumer intent to purchase products and groceries online in the next 90 days, signaling that there is no slowing the growth of eCommerce even in a post-pandemic retail landscape.
As a result, the pace at which we see predictive and automated shopping take hold will be far more significant than where it’s been to date. Brands and retailers will move to an even greater degree past their reliance on a customers’ past purchase history or self-provided preferences to make cross-sell and upsell recommendations and instead will capitalize on automation, data, and an understanding of human behavior via machine learning to help people find products in their precise moment of need—and at times, even before they know they need it at all.
This is not the stuff of a far off future. It’s happening today. In fact, the online grocer Farmstead has already rolled out their smart shopping lists feature and is capitalizing on not only their owned data related to customers’ purchasing patterns but also contextual indicators such as what day of the week the list is being created and what season the interaction is happening in. Combining those owned and contextual data points allows them to make relevant recommendations and suggest new products that their customers may not have otherwise discovered and to proactively build those lists to make shopping even more seamless and tailored to each customers’ preferences.