When people talk about Artificial Intelligence, the first thought that may cross your mind may be robots taking over our everyday tasks, or possibly the early 2000’s movie starring Haley Joel Osment. Artificial Intelligence (AI), however, is around us every second of the day. Whether AI is running ads on our Facebook feeds or sending us confirmation purchase emails, it has become a norm in our culture.
What is AI?
AI mimics our human thought and decision-making processes. When we feel emotions or react to people, places and things (aka stimuli) in a certain way, we think these feelings or responses came out of the blue. Instead, our brains formulated a reaction to a situation based on processing thousands of data points from years of memories stored in our heads. Basically, it generated the best guess on how you should respond.
Today, AI is doing the same thing to make the customer experience more seamless and connected from browsing, to suggestion selling, to enhancing the point of sale, to post-sale interactions.
Brick and Mortar AI
It’s important for us to remember that AI isn’t just for online sales. There are plenty of great examples of AI in retail stores across the United States.
Here are our top five:
- Amazon Go Amazon Go stores give customers a grocery shopping experience without the checkout line by using a network of sensors and cameras that tracks the customers’ movement through the store and places the items they take in a virtual cart. Best of all, there is no line to contend with when you are done. You just leave and Amazon bills your account.
- Starbucks Starbucks logs a mind-boggling 90 million transactions a week at its 25,000 stores; 17 million of those sales come from their active mobile app users, of which 13 million are rewards program users. As a result, Starbucks probably grinds through just as many data points as it does coffee beans every day! This allows them to create a highly personalized customer experience that leverages predictive marketing, a virtual barista, and a rewards program that is nearly as addictive as the coffee.
- Walmart Big box retail giant is not conceding the AI fight. Just like Walmart built its retail empire by saturating the market just outside of large metropolitan areas before it moved into large cities, it is also moving into highly intelligent retail after a dominant player (Amazon) had been established. Walmart recently launched an Intelligent Retail Lab (IRL, which is a play on the gamer acronym meaning “in real life”) to compete with the innovative experience of Amazon Go stores.
- H&M H&M is investing heavily in AI by offering a robust customer rewards program which in turn is providing the budget fashion retailer with more data than you can fit into a Kardashian closet. Knowing more about what H&M’s repeat customers want has allowed the company to increase sales, lower costs and reduce the need to mark down prices on unsold inventory in order to move it.
- Stitch Fix AI isn’t just for optimizing the customer experience through basic automation like eliminating checkout lines and pre-ordering your latte; It can also do the work of personal shoppers whose main value prop is matching what clothes will look best on your and pairing it with accessories, and telling you how good you look in it all.
Can Small Companies Benefit from AI?
Mega-retailers don’t have a monopoly on the market or AI. Big data is for small businesses, too! Predictive modeling and other AI strategies can help small businesses reduce the cost of new customer acquisition and increase customer retention rates.
AI for Customer Service
Examples of AI in retail are not limited to customer attraction. “Chatbots” are being used by a rapidly growing number of companies to manage post-sale interactions. This technology gives customers an online chat alternative to addressing their concerns instead of having to make a phone call. Chatbots are also beneficial in reducing costs by utilizing AI to resolve basic customer service inquiries which decrease payroll costs.
AI-powered searches help fill the role of window shopping and flipping through catalogs. Often customers have an idea of what they want, but don’t know the exact product they want or where to get it. Retailers are able to increase sales and customer retention by tracking customer buying habits, including what they are searching for, when during the month or time of day they are making their purchases, how often they come back, along with many other factors.
For instance, AI-powered searches help customers find the product they are looking for even if they don’t know the brand or how to spell it. Autocorrect and autocomplete are well-established technologies that are constantly improving by leveraging user data. By assisting the customer in navigating an online search or finding a product in a store with the use of location-enabled app.
We use the same concepts to help businesses increase listing visibility and conversion rates of Amazon listings.
Automated Ad Purchasing
Segmenting your audience is critical across your marketing strategy. Fortunately, AI has revolutionized how we purchase online ads to target market segments. The massive amounts of data consumers are providing paired with enhanced algorithms have turned online advertising into something of an advanced online stock exchange, where dynamic prices are driven up or down based on consumer demand which is predicated on views, click-throughs, and other factors. Due to the amount of demographic and consumer data businesses have access to, they are able to target an audience when they are ready to make a purchase.
Sales Forecasting and Predictions
Every aspect of AI relies on some level of predictive modeling, but one of the most powerful ways it can be applied is to sales forecasting. In a pre-AI world, businesses developed forecasts through a capitally intensive process of developing a product based on much rougher market analyses and guessing what sales might be.
In a post-AI world, there is much less reliance on a high-stakes game of trial and error. Examples of AI in retail forecasting are literally in every case study you can get your hands on. Leveraging sales forecasting allows businesses to manage their inventory better by understanding consumer behavior. It also helps businesses reduce costs. By understanding when and how customers shop, retailers can right-size staffing and operational costs, and utilize AI to manage low-complexity customer interactions.
The Bottom Line on AI in E-Commerce
E-Commerce is a tool for every business to leverage from a single man or woman startup to a small retailer to giants like Amazon, Starbucks, and Apple. AI is growing in its importance in post-sale customer service and allows companies to build lasting relationships with consumers through conflict resolution applications and customer loyalty programs.
Small businesses don’t have to take extreme risks with AI by jumping in as the innovators who carry the burden of advancing this technology, but they can be a part of the early majority of retailers who understand riding this wave of the future will grow their sales and their business.