In an ideal environment, shoppers would behave – and, more importantly, make purchases – in predictable patterns and cycles. However, in reality, the cycles of supply and demand can seem borderline chaotic and nearly impossible to plan for, leaving unprepared retailers scrambling to offload surplus and dig up in-demand items in a strained marketplace.
This is the point where artificial intelligence, or AI, can act as a dependable bridge, ensuring that relevant data is efficiently analyzed and converted to uncover opportunities for growth and profit. In fact, AI and automation can drastically improve supplier and retailer relations in a number of ways by leveraging data to improve routine processes and operations, like forecasting demand and improving inventory management.
AI in Retail: More Than a Trend
Artificial intelligence (AI) is not just a “buzzword” or the latest trend in retail. It’s being applied throughout the retail process, including in areas that can improve supplier-retailer relations, and thus, meet shopper expectations. When used in retail, for example, AI can learn from shoppers’ habits and use that information to better predict and target what they want. As a result, retailers can work closely with suppliers to effectively market and manage inventory.
More retailers are tapping into the power of AI to save costs, increase productivity and increase revenue. Business Insider predicts that retailers will spend $5 billion on AI by 2022, while it’s projected to boost profitability in retail and wholesale by nearly 60% by 2035. Furthermore, AI shows the greatest potential in three key areas – personalization, search and chatbots – which can be used collectively to optimize the buying process on both ends of the spectrum.
Using this technology, suppliers and retailers can effectively gauge shifting demands and trends among shoppers, and act accordingly. Done right, this can increase transparency and both teams can use the resulting data to optimize their operations and improve their profitability.
4 Ways AI Can Improve Supplier-Retailer Relations
1. Forecast Demand
This is important for suppliers and retailers, allowing for advanced forecasting to accurately predict shopper behavior. According to a recent survey, 34% of retail supply chain leaders indicated that one of their top supply chain challenges is lack of forecast accuracy. This is due in part to earlier technologies that didn’t take a number of factors into account – like consumer attributes – to precisely predict demand.
AI can provide support in this area through machine learning, which is a branch of AI that crunches large data sets to identify patterns that can be used in predicting shopper trends and behaviors. In fact, it allows for ongoing forecasting, and continuously adjusts the forecast based on factors like real-time sales and weather. In this way, retailers are able to analyze historical and real-time data to build an accurate and informed forecasting strategy that sufficiently anticipates and meets demands.
2. Optimize Inventory Management
Once retailers and suppliers gain a better understanding of shopper demand, they must ensure products remain in stock – especially the right products – to generate sales and satisfy shoppers. AI can help by driving real-time inventory management. This advancement not only boosts the productivity of the supply chain, but it can maximize the stock efficiency and reduce depletion of
the stock. With improved inventory management, suppliers can better support retail initiatives, which will lead to better relations between the two parties.
Coca-Cola integrated AI into its supply chain management by automating cooler display restocks. The technology can recognize the number of Coca-Cola bottles on display, differentiate between sizes and varieties, count each type and more in real-time. According to the company’s chief information officer, with 16 million cooler displays worldwide, AI will help optimize inventory management and sales and support global scale growth.
3. Improve Omnichannel Fulfillment
Shoppers use a variety of channels to purchase products, including websites, online marketplaces, stores and more. Factor in the different inventory locations – like warehouses, fulfillment partners and retail locations – and it can be difficult to fulfill orders when and how shoppers expect.
The challenge is that shoppers are unaware of the massive omni-channel fulfillment operation that takes place when they make a purchase. Whether they shop online or in-store, they expect immediate availability, fast shipping and a seamless buying experience. Failing to meet their expectations can lead to lost sales and decreased loyalty for, which could have a damaging effect of supplier-retailer relationships.
To streamline this process, both groups must implement strategies that can deliver on their promises while overcoming the challenges and complexities of fulfillment. According to IBM, AI can be supportive in the following ways:
- Minimize the cost to serve while meeting expectations
- Simulate sourcing and fulfillment streams to support decision making
- Maximize omnichannel fulfillment capacity
- Utilize inventory at its most profitable price point
- Make dynamic adjustments to your fulfillment network without IT
Walmart is piloting an AI-powered robot called Alphabot that will retrieve items from shoppers’ grocery orders. The automated technology, which has already been installed in a Salem, New Hampshire supercenter, will help determine how similar systems can speed up the fulfillment of these orders. Ultimately, the goal is to satisfy the end user – shoppers – and integrating AI can help by making the fulfillment process more efficient for both partners.
4. Support Product Discovery
With e-commerce, particularly large online marketplaces, product discovery can be a challenge for shoppers. A simple search may not produce the desired results, causing them to move on to the next website. This is mainly because retailers typically have dedicated staff that manually sort, filter and standardize product information for a variety of images in a catalog. This can lead to errors and misclassification, impacting the way shoppers find items and affecting sales for both suppliers and retailers. But done right, you can increase personalization and improve the shopper experience, which will help to increase conversion rates.
AI can support product discovery in a number of ways. One of the most notable uses is through Natural Language Processing (NLP), a type of AI that improves on-site search results by mapping items to conversational words and phrases. Integrating NLP into your e-commerce site can improve search results for shoppers, provide access to more shopper data and deliver personalized recommendations based on site behaviors or past search history. This level of visibility is beneficial for both ends of the retail journey, which is likely to have a positive effect on the relationship.
AI is transforming the retail industry in ways that can significantly improve supplier and retailer relations. No longer a buzzword, AI is emerging as a viable solution for optimizing the purchasing journey and producing measurable results for both parties. To find success, consider integrating AI throughout your retail process to better meet shopper demand and expectations while increasing your bottom line.