The summer of 2023 proved that feminine energy sells. The impact was significant enough that Federal Reserve Chair Jerome Powell fielded questions about the Barbie movie and Taylor Swift’s Eras Tour impact on the economy. The retailers I serve felt the pain and joy of this boom as shoppers immediately wiped them out of head-to-toe Barbie pink outfits, Beyonce-style silver crops and skirts, and Taylor Swift Eras dresses. How could we have anticipated this demand or responded in a way that served shoppers better? This has gotten me thinking a lot about how best to leverage GenAI for retail.
If the last few years of rapid retail industry changes have taught us anything, it’s that shopper preferences and patterns move faster than assortment planning, merchandising, and product discovery approaches of the average retailer. Here are three new retail business realities about the expectations of modern consumers and how retailers and brands can address them with generative AI (GenAI) technology.
Retail industry reality #1: Consumers are no longer just observing trends, they are creating them.
One thing we know for sure is that consumers, especially Gen Z and Alpha, are frequently pushing trends to retailers rather than the other way around. When did you first become aware of the absolute run on pink and sparkling tops, pants, dresses, and skirts? Did your business systems adjust automatically or were you forced into an ad-hoc reactive mode?
Customer engagement is key
Speeding up the consumer feedback loop and listening in more places is becoming a necessity for retail businesses. Retailers need to focus more on online customer engagement by enhancing their social listening and doubling down on surveys and panels. This means more data collection than ever before. GenAI’s ability to efficiently analyze vast amounts of shopper and social data, summarize it, and classify it makes it ideal for processing all of that input in a way that can be efficiently fed into assortment and merchandise planning processes.
Holding back a portion of your budget to address these unexpected assortment changes and being ready to fast-track your supply chain process is also important. Automating these processes with generative AI and other scalable cloud-based technologies will lead to being a step ahead of your retail industry competitors to capitalizing on the fastest-moving merchandise and achieving more than your fair share of revenue lift.
Retail industry reality #2: Customers no longer want the endless aisle, they want the perfect aisle.
For a time, the endless aisle concept solved a portion of the assortment prediction problem by offering customers a vast selection of products that could lead each shopper to find what they needed. The approach still has its merits, but with increasing frequency customers are more interested in retailers that can provide easy and efficient discoverability and a curated virtual aisle of products tailored to their specific preferences and needs.
Take an AI-first approach to product discovery
Generating the perfect aisle in real time can be aided by an AI-first approach to product discovery. Efficient discoverability starts with clean descriptions of the products in your assortment. Automate refinement of your product catalog data using GenAI for retail to create consistent and accurate SKU descriptions that are properly tagged and error-free.
Then use an AI-driven solution for retail search and recommendations to automatically learn as users shop, detecting changing user preferences and utilizing the semantic understanding built into the AI model to produce the most relevant set of products personalized to your shoppers’ preferences.
The perfect aisle really starts to take shape when you add real-time data pipelines that can account for behavioral cues, such as what the shopper is clicking on, what products they’re adding to the cart, the pages they’re looking at, and the pages they’re bouncing off. AI can learn from all of these cues and automatically respond with even more personalized product recommendations.
How can generative AI help retailers and brands improve the customer experience by making the perfect aisle even more perfect? Add in conversational commerce technology, which interacts with retail shoppers in a chat-based format with a series of natural language questions, follow-ups, and replies to guide the shopper through product selection.
This consultative approach starts to mirror the in-store experience that a retail associate might provide in guiding personalized recommendations. Building the perfect aisle in a way that’s personalized for consumers benefits your top line by driving larger basket sizes and increased conversion rates.
Retail industry reality #3: Customers expect more. Satisfying them starts with an improved associate experience.
This reality is trending louder and louder; taking care of retail associates is more important than ever. The sales associate’s well-being plays a crucial role in shaping a shopper’s in-store experience, and retailers are increasingly prioritizing it. Here are two big ideas about where generative AI technology can help improve the retail associate experience:
Harnessing data
The first idea is rooted in the fact that retail employees are constantly turning over, so it’s essential to train them quickly and efficiently. You already have a wealth of product, process, and customer data. Generative AI technology can harness all that data and allow your associates to use natural language queries as part of training, enabling them to help customers immediately and in a smart, consultative selling mode.
Tapping into retail associates’ knowledge
The second idea is focused on the fact that your in-store associates have first-hand knowledge of the best and worst about your retail processes, deep knowledge about customer preferences, and other insights you may only see if you are there in the store day to day. Handheld devices are increasingly common and can be used by retailers to capture insights from associates in the moment either by voice or text.
Previously, this amount of data collected by retailers would be pure noise and too voluminous to distill. Today, GenAI technology is capable of summarizing and categorizing that data to rapidly feed insights into the organization. Creating a faster feedback loop can reveal valuable information that impacts your top and bottom lines. Taking care of associates will result in more loyal customers, higher repeat customers, and greater longevity for your associates.
The overall reality about the retail industry is that the only thing that is constant is change. Retailer decision-makers need to grasp that the heightened demands of shoppers—especially generations Z and Alpha—mean that change will continue to move at an exponential pace. Leveraging GenAI for retail is key to predicting and automating your retail operational systems response to what’s next.
Getting the most from generative AI with SADA
Wherever you are in your generative AI journey, SADA’s artificial intelligence experts can help align this powerful new technology to your boldest business objectives. SADA starts every generative AI engagement by understanding your unique business, industry, and vision. Prepare to be on first-name basis with AI experts, engineers, and Change Management specialists who’ll work closely with you to design a custom AI practice that’s fully aligned with your desired business outcomes. In the meantime, check out our handy reference, Create the ultimate digital shopping experience: 10 tips for getting started with AI.
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