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02/24/2020

Why Retailers Should Bet on AI

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Competition in the retail industry is stiff. As technology advances and consumer expectations skyrocket, retailers can no longer solely rely on products as their main competitive differentiator. They are now pressured to also deliver exceptional customer experiences, with little margin for error, even as executives search for tangible solutions to help improve processes and increase overall revenue. 

The upside is that retail businesses have been given an unprecedented view into consumer habits. Every action and inaction, from what pages customers clicked on to how much time they spent viewing select products, have been saved and compiled. 

The world’s largest retailers, including Walmart and Amazon, are using AI solutions to inform their decision making. Yet most have not yet figured out how to effectively leverage data to draw connections between past trends and future demand. 

In fact, most are limited by siloed data that cannot provide a holistic view of their customers, and still others have yet to invest in technology that can assist with the time-consuming analysis required for predicting behavior. As a result, shoppers are given cookie-cutter personas that do not evolve along with their shopping behaviors.

The truth is that we have moved beyond mass-market strategies straight into an era of instant gratification, real-time engagement and the above-all desire for a frictionless customer experience. The retail industry is facing a tipping point. To achieve these goals, it is time that more retailers embraced AI and the countless advantages it enables.

AI Can Unleash Better Decision Making

Executives in the retail industry are looking to solve real, tangible and significant business problems like how to grow their loyalty base, reduce store-level stockouts and overstocks, increase revenue and reduce manual processes. Using AI and data science to automate everything from inventory to promotional marketing is undoubtedly how they can find the biggest impact. 

For example, one of the more common strategies that retailers employ to make decisions is to group customers into broad segments and study their past decisions. The problem is these calculations are retroactive in nature, often suffer from limited visibility into overall buying behavior, and may not contain any information about who is most likely to change their behavior. And more importantly, what incentive or activity will get them to change behavior in order to achieve the business objective.

With the help of AI, retailers can combine a retroactive view (i.e. segments based on past data) with machine learning-driven future predictions and opportunities, down to the customer level. Through this lens, retailers will be able to actually understand what people want; what they want to buy, why they want to buy it and which channel they prefer to engage with, empowering them to cater to their customers in very specific ways. 

Soon Every Retailer Will Rely on AI 

Retailers have integral data at the ready empowering them to cater to their customers in very specific ways. AI can transform and optimize this data to enable retailers to tune into customers’ needs and shopping habits, whether it’s through promotional planning, loyalty management or product selection.

Targeting a consumer based on age or purchase history certainly makes sense in theory. However, consumers are much more complicated and make purchase decisions based on a complex set of factors that are constantly changing and evolving. Retailers are missing out on a significant opportunity to drive revenue and loyalty by failing to truly understand their customers with more advanced analytics that pull data from all of their POS and ERP systems. 

For that reason, it’s no surprise that a majority of retailers are now planning to utilize artificial intelligence and machine learning technology by next year. It’s a smart bet. And in the end, the retailers that implement AI technologies the soonest will have the largest advantage.

Kerry Liu is the co-founder and CEO of Rubikloud, a leading AI and machine learning platform for enterprise retailers.