Gartner: What Retail CIOs Need to Know About AI for Merchandising


“Seventy-seven percent of the retailers surveyed have deployed or have plans to deploy AI for retail strategy. Of those, 92% are targeting AI-based primary merchandising processes for implementation by 2021.” – Robert Hetu, Gartner

Gartner’s latest report delves into important key priorities for retail CIOs to consider when transitioning to AI technology.

According to a recent Gartner report, What Retail CIOs Need to Know About AI for Merchandising, retailers are shifting their operational focus towards automation and customer centricity with the adoption of AI. However, as retailers undergo this conversion, major transformations will take way on their merchandising processes, making it vital for CIOs to understand the implications of AI on product development and selection, planning, buying, demand forecasting, and allocation and replenishment.

As many merchandisers are witnessing, AI is a retail game changer, but without a clear understanding of what operational changes are in store with its implementation, the benefits of this technology are difficult to reach. According to Gartner, these are the key findings to consider if you’re looking into AI for merchandising:

  • Retailers overwhelmingly have or plan to implement AI solutions in five merchandising processes: product development and selection, planning, buying, demand forecasting and allocation and replenishment.
  • For most retailers, AI will be accessed as part of advanced applications that enable merchandising processes rather than generic AI platforms.
  • Practicality, transparency and explainability are foundational principles for successful implementations.
  • AI implementations will be unsuccessful without significant organizational change.

In order to reap the full benefits AI has to offer, retailers must be aware of these findings and embrace the challenges that come along with it to enable successful implementations.

The Value Behind AI for Merchandise Planning

As an example of some of the many benefits AI has throughout the merchandise process, merchandise planning has shown tremendous potential for success using this technology. Merchandise planning is an important sector of inventory decision-making that is shying away from the out-of-date Microsoft Excel application, and instead applying AI to better support customer satisfaction and the business goals of retailers.

Traditional merchandising processes are overly manual, leading to missed opportunities and the incapacity to operate with the optimal level of detail and urgency. AI provides a more productive change, while also enhancing merchants skills in collaboration with algorithmic retailing. While facilitating intelligent automation, AI inspires creativity, combining the optimal uses of both man and machine to dynamically tackle inventory challenges.

A Use Case with Celect AI to Optimize Assortments

For example, the fashion retailer Aeropostale, with a significant presence in e-commerce and an operation of 350 stores worldwide, is one of many retailers taking advantage of AI in planning assortment. To make the most of its inventory, Aeropostale leverages AI with Celect’s Plan and Buy Optimization solution. The solution identifies strategic opportunities surrounding preseason planning and assortment and provides intelligent insight to help retailers achieve their specific goals.

Aeropostale aims to reduce the number of products in their assortment, while simultaneously driving increased sales. To follow through with these objectives, the Celect Plan and Buy Optimization solution applies AI-driven predictive forecasting to rank incoming styles and determine the optimal quantity to purchase – putting overwhelming inventory decisions to rest. With this innovative approach, Aeropostale optimizes its planning strategy to improve margins and increase sell-through, achieving its merchandising goals.

For more information, you can access (Gartner subscription required) the full Gartner report here.

Gartner, What Retail CIOs Need to Know About AI for Merchandising, 27 June 2019, Robert Hetu.

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Topics: retail technology, artificial intelligence, inventory optimization, brick-and-mortar retail, machine learning, advanced analytics, innovation

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