3 AI Prompts to Inspire In-Store Retail Strategies and Boost Sales

For those who develop in-store product placement strategies, creating a “love at first sight” moment is the ultimate goal. Whether arranging items by color, optimizing category visibility, or using eye-catching stoppers and signage, the goal is always to spark an immediate connection between shoppers and products.

Visual presentation plays a big role in purchasing decisions. A well-curated display can position a product as premium, innovative, or more appealing than its competitors.

Retailers have long relied on the Category Decision Tree (CDT) for assortment and placement decisions. But once those decisions are made, brands face the challenge of bringing products to life on the shop floor—a process that can be both time intensive and costly.

This is where AI-generated visuals can come into play. They offer a quick, cost-effective way to prototype merchandising concepts, allowing brands to experiment with multiple creative directions before committing resources.

In this article, we’ll explore how AI supports the ideation phase of retail strategy by:

• Testing promotional messaging
• Brainstorming product placement ideas
• Prototyping packaging and label designs

AI-inspired in-store signage concepts

ChatGPT was asked to: “Create a banner for a fashion T-shirt brand featuring a top model wearing a white shirt in New York streets.” The result can serve as a starting point for creative exploration:

Figure 1: OpenAI. (2025). A high-fashion banner for a trendy T-shirt brand featuring a top model wearing a white shirt in New York City [AI-generated image]. DALL·E.

This visual concept enables marketing teams and brand managers to explore diverse design directions—experimenting with colors, imagery, and messaging—before engaging design teams. This can lead to quicker internal approvals, fewer creative bottlenecks, and reduced production costs.

AI-driven planogram concepts

What about some layout inspiration for a heavy duty tools section? Copilot suggests one possible layout:

Figure 2: Copilot. (2025). Section of heavy-duty tools in a hardware store [Adapted from an AI-generated image].

AI tools like Copilot don’t have access to your specific store layout or hard data, such as sales per square foot or item quantity per bay, to inform the image creation. However, decision makers can combine this visual inspiration with planogram optimization data to develop a more holistic and effective store layout that marries creative ideas with data-driven decisions.

AI for packaging and label design inspiration

And what about a Craft Stout Beer label? Here’s ChatGPT’s proposal:

Figure 3: OpenAI. (2025). A detailed beer label design for an artisanal Stout featuring a Viking raising a mug of dark beer in a toast [AI-generated image]. DALL·E.

Whether for CPG or in-house printed private labels, AI supports rapid testing of typography, color schemes, and imagery for packaging and label concepts. This can be combined with market research and performance data to finalize designs while lowering the total investment—useful when refreshing an existing product line or launching a new category.

Ready to take advantage of AI?

All the images above were created in seconds using various AI models without any payment plans. With just a well-structured prompt, AI concept art for retail contexts can inspire ideas that lead to success on the shelf.

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