Visual merchandisers want to find the right AI solution, they really do. AI was once a smaller topic of conversation, but then rapidly gained momentum over the last few years. At One Door, we talk to visual merchandisers from several retail sectors struggling to understand how to synthesize their needs, especially when it comes to AI (until they meet us, of course).
Without giving away all of our secret sauce, we’re going to break down ways of thinking about AI in visual merchandising.
The Three Buckets of AI in Visual Merchandising
Generative AI
Generative AI in visual merchandising allows retailers to create plans, product images, POP content, and more for each store with a simple prompt. According to McKinsey’s article, it will allow visual merchandisers to expand their marketing efforts more than before. The AI will then create the requested visual or text content based on the data provided. For visual merchandisers, generative AI is primarily a resource saver for both time, effort, and money, giving them the ability to create art or copy at rapid speeds.
Dynamic Planogramming
AI algorithms analyze real-time data, including sales trends and customer behavior, to automatically generate optimized planograms. Using generative AI ensures that products are strategically placed to maximize sales potential, leading to increased revenue and enhanced customer satisfaction.
Personalized Product Recommendations
Combining generative AI and previous demographic and sales data, visual merchandisers can deliver personalized product suggestions based on individual stores. This can include customer behavior, store layout, and other localization items, but taken a step further. The personalization from the AI improves the shopping experience and drives sales.
Analytics
Analytical AI is a way to give visual merchandisers a strategic leg up with their plans. They will be able to move, collect, and consolidate data by having a technology platform to find important information quickly and concisely. Analytics can include everything from sales data, product performance, demographic understanding, localization information, and more. This information is analyzed by AI to point out the trends, possible next steps, and ways to implement the findings.
In-Store Customer Analytics
Through AI-driven customer analytics, visual merchandisers can gain deeper insights into customer behavior, preferences, and demographics. With this better understanding retailers can optimize store layouts, staffing, and product placement strategies to create a more seamless and personalized shopping experience.
Predictive Strategies
AI algorithms can analyze market trends, pricing fluctuations, and customer demand to suggest changes in real time. Visual merchandisers can maximize profitability, optimize inventory and product placement, and remain really competitive in an ever-changing space. This allows visual merchandisers to have more agility in their planning, without needing to change last minute.
Computer Vision
Computer vision in regard to visual merchandising gives countless hours back to retailers that need to monitor how stores execute plans by efficiently analyzing images provided by stores. This is especially useful for monitoring display execution and performance, POP content, and more. Computer vision will learn how to identify the good and bad, so visual merchandisers save countless hours figuring out if their displays are correct in every single store.
Image Recognition
AI-powered image recognition technology enables visual merchandisers to analyze store images and identify areas for improvement in real time. From optimizing product displays to assessing store layout effectiveness, Image recognition helps visual merchandisers gain better insight. They can better understand how their displays look down to an individual product and quickly understand if the display is making an impact.
Issue Remediation
AI showing merchandisers “what’s good is” can be extremely helpful when they don’t have time to backtrack to fix an issue. With computer vision, AI can learn what to do to help the store team fix an in-store issue without needing HQ intervention. This can understand how to fix a display, order more or different print content, or simply know the exact step they went wrong with product placement.
Every day there’s so much more AI is capable of doing. Unfortunately, if you’re not using it to get ahead, you’re falling behind. It’s time to start adopting AI and learning how to drive sales through visual merchandising alongside the right solution.
Still not sure where to start? Talk to a visual merchandising expert today to learn more about how AI can help you create retail success!
The post AI Use Cases for Visual Merchandisers first appeared on One Door.
