3 Actions for Retailers to Drive Customer-Centric Merchandising with AI Core
The ever-changing economic landscape, propelled by financial constraints, surging costs, and technological advancements, is reshaping consumer behavior. The pandemic intensified retail trends and redefined the meaning of "personal" shopping.
To stay competitive, retailers must transition from product-centric to customer behavior-centric hierarchies for improved assortment strategies. In this evolving retail realm, AI emerges as the essential tool for this shift, enabling customer-centric merchandising.
Here are three key recommendations for retailers to embrace customer-centric merchandising through AI.
Implementing AI Use Cases for Aligning with Customer Expectations and Industry Segment Needs
Retailers can use AI to organize merchandising and merchandise planning around customer behavioral segments. By working more closely with the marketing team, retailers can focus on what is most important to customers at every touchpoint. This will allow retailers to understand and enable the way customers prefer to shop.
This approach can be complex, as it involves creating matrices of behavioral segments, locations, touchpoints, and the products required to support the business. However, this is where AI and algorithmic retailing can be most helpful. AI can be used to collect and analyze customer data, identify patterns, and make predictions about customer behavior. This information can then be used to optimize merchandising and merchandise planning, and to create personalized shopping experiences for customers.
Merchandising and Planning Teams Must Leverage Customer Behavioral Segments
Customer behavior is a key factor for merchandising success. Customers may not always act according to their stated preferences, such as buying cheaper products that are not sustainably sourced. Merchandisers need to understand how customers think, feel and act, and what influences their decisions. By using data from various sources, such as transactions, locations, touchpoints, social and demographic profiles, and external factors, merchandisers can create customer segments that capture the essence of the customer, or the "I AM" as Gartner calls it. However, the "I AM" is not static, but dynamic and evolving, as shown in Figure 2.
Customer behavior is a complex phenomenon that needs scientific methods to model it accurately. To create effective merchandising strategies, customer behaviors should be grouped into segments that can be measured and applied. Customer behavior segments should be based on various data sources, such as transactions, social media, location, and brand loyalty. Customer behavior data should be shared across different functions to support customer-centric approaches. Customer behavior insights and new metrics should be communicated to key stakeholders, and marketing and merchandising teams should work together to understand and use customer behavior analysis.
Merchandising and Planning Teams Require Automation to Avoid Failure
To shift from linear product-centric to circular customer-centric merchandising, merchandising teams need information, tools and automation. Algorithmic retailing can help them use data effectively in their decisions. Merchandising also needs more automation and machine intelligence to support human processes (see Figure 3). RPA workflow tools and intelligent automation services can enable the comprehensive merchandising processes that are essential for customer-centric merchandising.
Develop alternative methods that enable merchandising to reorganize the business functions around customer behavior hierarchies instead of traditional product hierarchies:?
- Enhance AI capabilities within the organization and achieve implementations in redesigned customer-centric merchandising processes within two years. This is essential, because otherwise, your current competitors, as well as new entrants and your customers, will have expectations that exceed your current capabilities, and you will lose relevance.?
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- Implement basic and intelligent automation services now, even for processes that will not last long. This will help to foster the understanding of automation that can benefit the business immediately while also freeing time from existing people to focus on new business process reengineering for the future.
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We hope this edition about AI will emerge as the guiding light steering retail towards customer-centric merchandising. By adopting AI and weaving it into the very fabric of retail strategies, businesses can infuse agility, relevance, and innovation into their operations, ensuring they remain not only competitive but indispensable in the ever-evolving retail landscape.
Stay tuned for more updates and best practices to elevate your retail strategy!
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