How AI and Generative Design Are Transforming Store Layouts for Enhanced CX

Mar 12, 2024

How AI and Generative Design Are Transforming Store Layouts for Enhanced CX

By Alyx Kaczuwka | Total Retail

For retailers designing curated and experiential spaces for customers to elevate their in-store experience vs. competitors’ stores or e-commerce alternatives, the challenge remains: How do you design a store layout that maximizes both the customer experience and overall sales?


Artificial intelligence (AI), including generative AI, can provide deeper insights, faster iterations and more intuitive store designs to drive the redesign process. Most retailers are already using space planning software, but far fewer are utilizing AI-driven insights or generative AI at any phase of design.


Before moving on to aesthetics, it’s important to start with a data-driven approach to your store design. AI tools are ideal for the extraction and analysis of store data, such as:



  • Highlighting Customer Traffic Patterns: AI tools can spotlight high and low traffic zones within a store, enabling retailers to reengineer their store layouts, direct customer movement, and utilize space efficiently and effectively.
  • Deep Diving Into Customer Behavior: AI can extrapolate customer behavior from time spent in particular store sections to specific product interests and customer interactions. AI algorithms might spot payment trends, such as a growing number of mobile vs. fixed point-of-sale transactions, or nuances like customers who buy certain products being more likely to linger in-store or have companions with them, suggesting a need for seating in that department.
  • Elevating Product Placement: Intelligent product placement dramatically impacts sales. AI analyzes sales trends, product relationships and consumer demands, placing products strategically to boost sales based on which products benefit from in-store visibility or sell best when grouped together.
  • Analyzing Competitor Layouts: AI can power competitor analysis when retailers add competitors’ store layouts to their training data, making it easier to capture learnings about their store designs and merchandising.


Generative AI takes store design a notch higher by facilitating the creation of 2D or 3D store models. An exploration of all available generative AI tools available today goes beyond the scope of this article, but a broad array of options exists, ranging from text-to-image tools to completely create an image based on a prompt,  generative fill tools to add or delete sections from an existing store layout, or models to train from scratch on your current store layouts.


Using parameters based on your learnings, such as product placements, store dimensions, architectural features, accessibility needs and customer traffic patterns, generative AI can create detailed virtual models making use of your retail space. Here’s an example of a luxury retailer layout generated using Midjourney AI:

Once several layouts are created, a retailer can utilize them for virtual focus groups, letting consumers engage with the store digitally and offer feedback for refining the layout before the commercial architecture and design teams take over.


Rapid AI design tools for store models can be of value for commercial real estate process as well. Here’s what’s basically the same space above, but rendered for a retailer of luxury menswear. A broker can now easily create renderings for multiple potential clients.

AI can also emulate customer behaviors in these virtual setups. Behavior simulations, combined with review by stakeholders and focus group participants, can preemptively identify challenges the AI might have missed, ranging from security to accessibility, ensuring a seamless store operations experience as well as customer experience when the layout is physically implemented.


Overall, AI has the potential to revolutionize the retail industry, including store layouts and customer experience.  By providing insights, speed and flexibility, AI can help retailers to create more intuitive, efficient and customer-centric stores, using intricate consumer insights, rapid prototyping, and fast modifications.

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