Retailers are always on the lookout for ways to make themselves more competitive — trends in advertising, social media channels to leverage, new takes on email and online marketing.

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SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learningParticularly for smaller businesses, the focus is often on initiatives that could result in fast ROI, and this tends to mean efforts explicitly aimed at increasing sales volume. For larger chains, it can mean a focus on expanding into new markets or opening new locations. The problem is that these efforts take time and attention away from the simplest way retailers could increase both their short-term success and their long-term ability to compete: implementing AI-powered automation.

This is especially important in the current retail climate, where customers are shopping online more than in person. Forward-thinking executives, marketers and data scientists have been warning retailers that AI is an “adapt or die” prospect for years, but many companies have yet to take up the challenge. Although the huge e-commerce wave brought about by Covid-19 prompted some retailers to take action, too many thought that the retail landscape would “return to normal” within 12 to 24 months. Retailers and distributors who have already leveraged AI are more competitive than those who have not. Now that we know retail has changed forever, it’s time to act.

It all starts with product data, which is often the biggest pain point retailers face. Luckily, there are ways that AI can save virtually any retailer or distributor massive amounts of time and energy and allow them to compete against some of the largest big-box stores and e-commerce giants. 

Handle The Basics: Structure And Taxonomy

It doesn’t matter what industry you serve, how large your company is or how sophisticated your other technologies are; without adequate data structuring, AI can never reach its full potential for your business. Data structuring is the bedrock of every digital transformation and every push forward in innovation. We always suggest data structuring as a starting point when implementing any AI solution. 

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