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Podcast EP.43: How to optimize your retail AI

Understanding the reasons why retailers invest in AI, the common assumptions usually made and how to mitigate risk in order to see value.

As reported by Juniper Research, global retail spending on AI is expected to reach $7.3 billion annually by 2022. However, a survey by Sloan Management Review and the Boston Consulting Group found fewer than 40% of companies who have invested in AI had seen business gains from it in the previous three years. So how can retailers make the most of their AI investment?

With the acceleration of digitalization and adoption towards digitization, retailers are learning quickly that their future depends on how they can leverage technology. But for an industry that’s been slower to adopt, retailers have entered uncharted territories on exactly how to get the most out of its retail AI. 

Based on his co-authored article in the Harvard Business Review called “Why you aren’t getting more from your marketing AI”, Michael R, EDITED’s SVP of Retail Sciences, joins the podcast to share his knowledge of how companies need to use AI to see true value. With an extensive background in retail and technology, Michael is a leader in the industry as the former Co-Founder of both figleaves.com and DynamicAction, a leading retail analytics and AI company recently acquired by EDITED, as well as a non-executive Director of Sainsbury’s Bank and N.Brown. With today’s uncertainty in the retail landscape, Michael shares insight into the business opportunities retailers can get from their AI by simply asking the right questions. 

Key takeaways:

  • While AI adoption is necessary to scale a business, humans are still very important in retail to understand what a machine cannot define, including what’s driving fundamental growth via customer retention and acquisition. Ultimately, a machine makes a prediction and that needs to be combined with human judgment. Michael says, “Think of AI and algorithms as your new colleagues. It’s not that they’re going to replace humans, but they’re going to amplify humans and take cognitive burdens, both in terms of solving the problems and then executing at scale.” 

  • The typical failures seen when using AI incorrectly are defined by three A’s. Alignment is the failure to ask the right question; Asymmetry is the failure to recognize the difference between the value of being right and costs of being wrong; and Aggravation is the failure to leverage granular predictions.

  • Retailers have historically made decisions based purely on gut instinct, but nowadays ideas can be quantified. With data transparency, retailers are able to see the different channels of where business payback can come from and provide hard facts to streamline efficiency. Michael says, “Creating a culture of data transparency is incredibly powerful.” 

  • For any retailer looking to dive into retail AI, Michael advises, “Think big, but start small. You don’t start with a big grand vision and you don’t start with data. You start with looking at a decision and decisions that have a big revenue attached to them and how we can make decisions differently and better.”

 

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