In recent years, the pandemic, along with economic and consumer shifts, has acted as a catalyst in transforming consumption patterns and consumer behavior in the retail sector.
In general, consumption has shown a year-on-year downward trend in 2023/2024 across most retail sectors. This indicates that consumers are under increasing financial pressure, which in turn affects the retail industry as a whole. As purchasing power declines, the balance between price and value becomes more critical, presenting new challenges for retailers.
In the following sections, we will explore these challenges and how AI can help overcome them.
Enhancing Assortment Strategy with AI
To maintain high sales volumes in a shrinking market, retailers must optimize their product assortment and consider additional data, such as customer income. Start by surveying your customers to understand their income range and then analyze your current assortment. While you may already be excelling in customer segmentation and store clustering, it’s possible that your product offerings do not fully align with customer expectations. AI-driven assortment planning can uncover correlations within customer data, enabling you to better match your offerings with dynamic consumer preferences.
Automating Retail Processes for Efficiency
Automation is becoming increasingly essential in retail, as repetitive tasks previously handled by humans should be minimized to enhance efficiency. By leveraging AI platforms, retail business processes can be streamlined, reducing operational costs while improving speed, efficiency, and reliability. While AI chatbots are commonly used today, the potential of AI extends far beyond this. AI platforms can process supplier contracts in seconds, sending contract data to purchasing systems and setting up business rules for automated ordering processes. Once the right assortment is defined, AI can even automate the entire procurement chain.
Optimizing Stock Management with AI
Maintaining sufficient stock levels is a perennial challenge for retailers. By combining customer purchase data with supply chain analytics, AI can predict future buying trends, align stock levels accordingly, and identify inefficiencies that drain profits. This reduces waste, optimizes space, improves customer satisfaction, and enhances overall profitability.
Leveraging AI for Consumer Insights
AI-powered insights can help retailers understand how customers make purchase decisions and how items interact with each other. By analyzing patterns such as the “halo effect,” AI can reveal which products are frequently bought together and how these interactions influence sales. Furthermore, AI can help determine the true demand for products, providing a clearer picture of the buying process and optimizing product assortment.
The Future of Social Shopping: AI Integration
Integrated social shopping is likely the next frontier where AI can revolutionize the retail experience. For example, Amazon and TikTok have recently partnered to allow users to purchase Amazon products directly through the TikTok app. This integration enables TikTok users to view Amazon recommendations and make purchases without leaving the platform. AI plays a crucial role in personalizing product recommendations, ensuring that customers see the most relevant items. By linking Amazon and TikTok accounts, this collaboration opens up new opportunities for AI and machine learning to drive global e-commerce growth.
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