Artificial Intelligence in Retail
In this blog, we will explore how AI is changing the retail space, learn new ways to engage with customers and how to take your customer experience (CX) to the next level.
AI and the Customer
Artificial Intelligence (AI) is enabling game-changing capabilities within the Retail industry, helping to optimise their operations.
Retailers are faced with digitally savvy shoppers, with constantly changing preferences who expect shopping experiences that are tailored, instant, and effortless. AI makes it easier than ever to meet these expectations with its ability to intuitively understand customer desires and craft personalised services at a level far greater than ever before.
A strategic partner amid challenging economic times
For retailers, staying profitable is not just about creating customer experiences to grow loyalty, and ultimately sell more stock. Retailers face multiple challenges outside of just sales — increasing cost of materials, wider economic volatility, and the climate crisis, to name a few. While traditional tactics might be less effective than previously, AI offers cutting-edge analytics and forecasting to help retailers adapt swiftly to market changes.
Gartner predicts that by 2025, 80% of Retail executives expect their companies to use intelligent automation technologies and 40% already use some form of it.
Yet, retailers can’t just plug-in AI and expect it to solve all their problems overnight. They need to take a practical approach that focuses on areas of their business where AI can have the greatest impact.
6 AI use cases for retailers to thrive
There are many areas of business where retailers can use AI to improve efficiency, drive down costs, and improve customer experience. However, achieving these results requires a combination of the right investments in both technology and people.
Here are 6 use cases that all types of Retailers can focus on to deliver game-changing value from AI:
Inventory optimisation: Maintaining sufficient stock is a constant challenge, with most retailers approaching safety stock levels by having a standard target across all SKUs. AI allows retailers to approach this in a much more granular fashion, with them ultimately applying the correct safety stock policy at a SKU-level. By combining customer purchase data with product analytics, AI can predict future buying trends, ensuring that the right amount of each stock is in the right place, ensuring capital is not tied up in excess stock. This reduces waste, optimises space, improves customer satisfaction, and bolsters profitability.
AI-powered demand forecasting: Forecasting is incredibly complex with multiple variables, and retailers can suffer in this regard when skilled, experienced staff leave the organisation. AI systems examine past sales data, current market conditions, and emerging trends to generate accurate demand predictions. These more accurate forecasts then drive initiatives that reduce overproduction, minimise wastage, boost sustainability efforts, and future-proof the business from changes in staff.
Route planning: Using a combination of algorithms and real-time data, AI can optimise delivery routes to limit delivery times, reduce fuel consumption, and improve customer satisfaction. AI-based route planning helps retailers manage changing conditions and avoid service disruption.
Price optimisation: Retailers have to constantly adapt their pricing strategies to succeed but can struggle to do this at a granular level. AI systems analyse wider market trends, buyer behaviour, competitor pricing, demand flows, and internal costs to quickly adapt prices, manage promotions, and maintain profitability. All of this ensures that products are sold at the best price possible at the right time, maximising profit for the retailer.
Product range planning: Traditional retail product planning methods struggle to accommodate dynamic customer behaviours. AI analyses customer data, identifying patterns and relevant variables that are impossible for a human to identify. This allows retailers to create a more personalised, regional, or individual-centric product mix. According to Gartner, all global multichannel fashion retailers will use AI and automation by 2025 for targeted assortments.
Personalisation: Providing a memorable shopping experience comes from a deep understanding of customer behaviours and preferences. AI analyses data points such as buyer browsing habits and purchase history to help retailers craft personalised shopping experiences. This ultimately helps to drive loyalty and repeat business from customers.
Using artificial intelligence in Retail
For retailers aiming to truly embrace the competitive advantages that AI will allow Investing in the correct infrastructure and fostering a unified data ecosystem are more important than ever. However, AI is only as effective as the data it is trained on, so getting the foundations right is critical.
By using AI to refine their operations and engagement models, retailers can position themselves to better thrive in the age of AI.
For more information on how Hitachi Solutions can help you solve your retail business challenges, with AI, contact us.
