Gear Up Your AI: Fine-Tuning LLMs
February 8, 2019

How AI is Improving Retail Merchandising Efficiencies

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Every area of a retail store can directly affect your bottom line. Elements from the products that are stocked, to where they’re placed, what signage is used, and price can impact sales. For consumer packaged goods (CPG) companies like Coca-Cola and retailers like Target, it’s vital to ensure a return on the cost of that physical retail space - whether you’re paying for shelf space or paying to keep the lights on.

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For many, much of what goes into decisions around what to stock, how much to order or supply, what to promote, and how to price is done traditionally and manually. This work is not only labor intensive but also often contains human biases. In fact, according to Nielsen:

  • Consumer product companies spend extensively on trade promotions—to the tune of $1 trillion each year.
  • The disappointing part is that about 40% of that spend doesn’t drive the desired results.

However, machine learning is enabling retailers to look at planogram planning in a new, innovative way. By applying AI to historical data gathered from your store or even stores around the world, you can determine which products should be placed where, at what price, and which promotions should be applied to optimize sales. This is one of the many reasons why analysts predict that retail spending on AI will reach $7.3 billion by 2022. These trends are also leading retailers to AI:

  • While 74% of retailers want to be data-driven, only 29% successfully implement data analytics. (source)
  • First-quarter retail sales in 2018 fell for three straight months for the first time since 2012 despite the economy growing around the world, including economies that of Australia, the U.S., and Europe. (source)
  • 54% of US and Canada-based consumers said that they would end their relationship with a retailer that fails to make relevant, personalised offers. (source)

We all know how important analyzing and reacting to data is, but few retailers are actually leveraging it yet, and this is affecting revenues and driving profits way down.

Given the right information, AI can optimize every aspect of retail planning. For example, by using computer vision and the security cameras already throughout your store, you can better understand foot traffic, the impact of displays, and even keep count of the number of items in stock.

Want to see how AI is being used in retail today? Check out this post next! You can also check out our list of the top AI and retail stats here. 

How to Drive Revenue with Computer Vision AI