Artificial intelligence (AI) continues to retain its position as the technology perceived to be the most disruptive since Q3 2021.
The retail sector is no exception, as software company RELEX Solutions points out that retailers’ investments are increasingly driven towards AI. This is done with the aim of growing sales, stabilising supply chains, adjusting planning processes, and improving customer relations.
Supply chain forecasting
Retailers have begun using machine learning to capture the impact of hundreds of demand drivers for highly accurate demand forecasting, improving planning processes across merchandising, supply chains, and operations with visibility into future demand.
These solutions combine advanced machine learning capabilities that can forecast demand for every product, in every store and channel, for both the short- and long-term.
Convenience business One Stop adopted such solutions in 2022, reporting significant improvements after four months of using an AI forecasting solution. This included a 5% point increase in-store availability across One Stop’s entire range, which contributed to a significant sales increase, according to RELEX.
Cutting operational costs with chatbots
Cashier-free stores are already in play for a while and have been shown to reduce lines and significantly cut operational expenses. Amazon Go is one of the first examples, using ‘just walk out shopping’ technology that reacts to products taken from the shelf and invoicing products taken in-store to their Amazon account.
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By GlobalDataLeading retailers, such as the fashion brand Burberry, have adopted AI chatbots to enhance customer service, improve searching, to send notifications on new ranges, and to suggest similar products.
A consumer survey conducted by GlobalData finds that consumers are fairly ambivalent about the introduction of ChatGPT to retailer customer service bots, but that is down to their underestimation of how much of an improvement they will add to their interactions.
Smarter markdowns and clearances
Further AI use cases across the retail sector include pricing and clearance optimisation software. These new solutions automate markdowns and clearance processes. This allows retailers to eliminate manual clearance and markdown tasks such as product identification and allocation.
Retail staff can proactively identify products for clearance and markdown, setting timely, optimised discounts based on desired outcomes. This also reduces the risk of excess stock, whether at season end or lifecycle end, and cutting spoilage.
These AI solutions can drastically improve margins, which is urgently required in an already challenging sector. AI software that identifies optimal markdowns means retailers can use AI to target the right products at the right time and price, which expedites inventory turnover and improves margins.
There are ample examples within the retail sector where AI is being used in novel ways, and AI adoption at companies will play a crucial role in determining the winners and losers of tomorrow.