The Science of Winning Customers' Hearts: How to Build an Effective Retail AI Strategy

IN — 31 October, 2017

Most of the buying decisions that customers make are emotional, even if they back-rationalize their purchases with logic. This is one reason that understanding consumer buying habits, and creating an engagement strategy that works on a personal level, is so challenging for retailers.

 

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However, the art of winning customers’ hearts can be greatly improved with science – something Blue Yonder’s founder and Chief Scientific Officer, former CERN scientist, Professor Michael Feindt, truly believes.

Recently, Michael sat down with Chris Field, Head of Innovation at Retail Connections, to look at how data science investment can help retailers to build stronger customer relationships in the grocery and fashion industries. He also discussed why Artificial Intelligence (AI) is the most powerful way to leverage that data science for strategic improvement.

Here are some of our key takeaways from Michael’s interview – you can also watch the full grocery insights video here and the full fashion insights video here.

1. Narrow AI use cases deliver the most immediate value

While media headlines have been dominated by stories about robotics redefining the retail landscape, in truth, AI delivers the greatest immediate value when it is deployed to solve a specific problem.

“The real progress is not in the broad sense of AI, but in narrow intelligence, solving specific problems in a better way than humans,” comments Michael. “AI enables millions of automated operational decisions every day, aligned with a strategic goal.”

2. Decisions should be based on current customer influences

One of the most common pitfalls retailers find is basing customer acquisition and retention activity on historic data, which doesn’t always account for the changing influences on buying behavior.

“Usually what happens at the marketing planning stage is that retailers look at what they did last year to determine their strategy,” says Michael. “But, this year, there are hundreds of different influencing factors to last year.”

AI enables retailers to combine more data sources than ever before, and to look at historic data in the context of current influences. From this, businesses can create campaigns that resonate much more closely with consumers in the current climate.

3. AI should empower, not replace, the human workforce

“The application of AI does not kill jobs,” Michael urges. “It actually enables store personnel to work smarter than before, as it reduces a lot of their daily task load. Without having to do these jobs, staff have more time to focus on the customer.”

Just as the growth of ecommerce has redefined bricks-and-mortar’s place in the retail mix, AI is giving the retail workforce a renewed sense of purpose – one that is focused on offering customers the human warmth and skill that machines will never be able to replicate.

4. AI can work with existing technology to deliver greater customer value

Today’s shoppers are demanding and impatient; they want a retail service tailored to their needs, and they aren’t prepared to wait for it. For retailers to respond to this challenge, they need access to technology and processes that can be implemented quickly and seamlessly, to deliver rapid results.

AI is already helping leading retailers to make huge differences to their customer experience in a short space of time, from pricing optimization through to improving replenishment models. And Michael believes this pace of change will only increase.

“AI development cycles are getting shorter and shorter, and there’s more innovation to come” he concludes. “Companies like Blue Yonder help to increase this pace because we can simply put an intelligence layer on top of existing ERP systems, deployed in the cloud as a service model.”

For a round-up of retail AI innovation visit our AI in Leadership page – where you can read the latest articles from The Daily AI.

 

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enables retailers to take a transformative approach to their core processes, automating complex decisions that deliver higher profits and customer value using artificial intelligence (AI).