Just two years ago, our conversations with retail executives centered on a digital-powered future, and the exciting possibilities ahead with machine learning. That future quickly became reality, illustrated by this example of Kiran’s recent shopping trip:

My wife and I have 2 kids. We were at the park recently when my toddler daughter needed to be changed, and we realized we did not bring diapers. As I held my daughter with one arm, I picked up my phone with the other and said, “Ok Google, can you please find diapers?” My phone announces my daughter’s brand and size are in stock at my nearest preferred big box store, about 1000 ft away.

This experience was impossible two years ago. Machine learning and automation have made this experience not only possible, but expected, in seconds. Through voice and situational recognition, knowledge of Kiran’s preferences and a retailer whose experience delivers instantly, retail is suddenly changed forever.

Today’s digital shoppers expect more than answers, they expect assistance. Machine learning delivers on those expectations, bringing step-change improvements for faster, more personalized, and more intuitive experiences. Savvy executives are making investment decisions that give them a competitive advantage in this age of assistance: through a clear vision, robust technical infrastructure and relentless execution.

Today’s digital shoppers expect more than answers, they expect assistance. Machine learning delivers on those expectations, bringing step-change improvements for faster, more personalized, and more intuitive experiences

Accelerate data-driven decision making

e-commerce is rapidly transforming from an opex based to a capex based business. 90% of the worlds’ data was created in the last 24 months, but less than 1% of it is analyzed. Executives must align their resources and investments to harness data to deliver on these experiences.

This doesn’t mean that companies need to change internal structure and priorities overnight, but retailers who are taking meaningful steps focused on knowing their shopper better are seeing immediate benefits to their omni-channel business - better recommendations, cleaner check out flows, and simpler integrations between online and in-store purchases.

Home Depot is doing just this - last year their internal teams worked together to pull all their data - online and store - to Google Cloud just in time for the holidays. With the help of machine learning, they were able to predict inventory needs at individual store level. They were also able to optimize delivery times and demand between stores in a timely and cost effective way, leading to online and offline sales growth during a critical holiday season.

Connect with data & insights

We recently conducted consumer research at Google with Qualtrics, learning that that for retail purchases, shoppers are aware of on average 10 brands in a category, but consider only 3. What’s more, 89% of shopper spend in that category goes to those three brands. Consideration & choice are powered at every sale, so how do retailers compete? They leverage data and insights to create experiences so that every interaction stands out.

Purple, a direct to consumer Mattress Company, knew that people buy mattresses at key life moments, like moving or getting married. Purple partnered with Google to leverage audience signals to find shoppers on YouTube who were more likely to have just moved, get married or were about to move or get married. After running the campaign, Purple saw a 20%+ lift in purchase intent among movers and among engaged or recently married viewers.

Drive action in a I-W-W-I-W-W-W-I-W-I world

Finally, those companies that reduce friction to serve shoppers in a “I-want-what-I-want-when and -where-I-want-it” (IWWIWWIWI) world, deliver results. A slow website is a major gatekeeper to traffic and conversions. According to Google & Ipsos, 53% of visits are abandoned if a mobile site takes longer than three seconds to load - yet, the average U.S. mobile retail site takes over ten seconds to load.

J Crew took on the effort to reduce shopper friction on their mobile web pages, leading to 90% reduced load times. They carried this fast and frictionless experience all the way to the point of purchase, helping auto fill a user’s saved payment credentials when they are ready to checkout. Through this effort, they decreased checkout times by 75%.

Digital is infused in every part of the retail value chain. Companies that win at e-commerce do three things. They accelerate their business by turning data from a challenge into the foundation of everything they do, from powering personalized experiences to making better business decisions. They embrace that people are shopping anywhere and everywhere and connect with them in all of these places - in a way that keeps them in control of the experience and helps them stand out amongst the competition. And finally, they drive action by removing friction from the entire experience, so the big effort of getting attention isn’t wasted on customers expecting a different experience.

The fundamentals of e-commerce businesses - and what makes them successful - haven’t changed; machine learning is just there to help unlock transformation in more ways than ever before.