Tips for Upgrading Retail Merchandising With AI

When an order from CalExotics arrived at one of our stores in Livermore, I wanted to help build the wall. After reorganizing it, I took a picture and asked ChatGPT what it thought of the wall. First, it noticed a gap in the top row and recommended adding a toy there or changing the spacing. Then it said, “I noticed there are some toys on the right that aren’t in boxes. You should take those down or put them in boxes.”

I told it, “Those are testers.”

“AI trained on millions of retail images can spot gaps, identify visual balance issues, suggest product groupings and catch mistakes that your eyes might miss after seeing the same wall every day.”

It immediately responded, “Oh, that makes sense. You should add a hand sanitizing station and make a sign that says, ‘Tester Station: Try me.’ It would help if you had all the selling points of each tester, so people know what they are seeing.”

This wasn’t just luck. AI trained on millions of retail images can spot gaps, identify visual balance issues, suggest product groupings and catch mistakes that your eyes might miss after seeing the same wall every day.

That moment shows how AI is fundamentally changing retail merchandising by recognizing patterns, suggesting improvements and learning from every interaction. Let’s explore how AI can help transform the way your store displays and sells products.

The Four Pillars of AI Merchandising

AI merchandising rests on four fundamental capabilities that work together to transform retail operations:

Predictive intelligence. AI can anticipate your customers’ needs, by analyzing purchasing habits, market trends and external factors like weather and local events to forecast demand with unmatched accuracy. This isn’t just about stocking more umbrellas when rain is in the forecast — it’s about understanding the complex factors that influence purchasing decisions. Target has already achieved 87% accuracy in predicting the stages of the customer life cycle. Walmart has used similar capabilities to decrease stockouts by 30% and reduce excess inventory by 20-25%.

Dynamic adaptation. Traditional merchandising relies on fixed planograms, seasonal resets and the intuition of experienced merchandisers. These methods work, but they are slow to adapt and impossible to personalize at scale. AI transforms this entire approach. Imagine an AI system that monitors customer behavior in your store all week, then tells you, “Move the premium products to eye level on the left side. That’s where 73% of your high-value customers look first.” Or receiving an alert that says, “The endcap display hasn’t been touched in three hours during peak time. Here are three alternatives that historically perform 40% better.” Modern AI systems use computer vision — the same technology that analyzed my wall in Livermore — to constantly monitor and improve product displays. Unlike fixed planograms that follow strict templates, AI-powered systems develop location-specific plans that adapt in real time based on local demand, inventory levels and customer preferences. They enable dynamic assortment planning, which identifies product combinations that appeal to specific customer segments. By analyzing sales data alongside customer preferences and local market conditions, AI can recommend assortments tailored to each store’s unique demographics.

Automated execution. Traditional planogram creation is a labor-intensive manual task that can take weeks to roll out across a chain. AI can automatically generate optimized planograms for retailers, taking into account factors like product popularity, profit margins and spatial limitations. Smart Merchandiser AI, recently launched by Zobrist Software Group, exemplifies this trend by providing plug-and-play intelligence that enhances product discovery while safeguarding revenue. These systems don’t just suggest changes — they seamlessly turn insight into action by automatically providing implementation guides, task lists for staff and even augmented reality (AR) overlays showing precisely how to arrange products.

Continuous learning. Perhaps the most powerful aspect of AI merchandising is its ability to learn and improve continuously. Every customer interaction, every sale, every browsing pattern becomes data that refines the system’s understanding. The AI that helps you today will be even smarter tomorrow.
The Revolution Will Not Be Supersized

Unlike past retail revolutions that favored the largest players, AI merchandising tools are making advanced capabilities accessible to all, giving every retailer — from global chains to individual stores — access to insights and capabilities that were unimaginable just a few years ago. Even single-location retailers can leverage AI merchandising tools, some of which you likely already have access to.

Choose your tools wisely. Select solutions that integrate smoothly with your existing systems while providing clear ROI metrics. Don’t be swayed by features you won’t use — focus on tools that address your specific challenges.

Here are some options, grouped by price bracket:

●      Free and low-cost. For as little as $20 per month, ChatGPT Plus and Claude Pro can provide merchandising feedback on uploaded photos of your displays. Photograph your worst-performing display and ask AI what’s wrong in this picture. Take photos of your top three product categories and ask for optimization suggestions. Compare your checkout counter to AI recommendations for impulse items. Get AI feedback on window displays before you build them. With Roboflow, you can train basic AI models to identify out-of-stock items with a phone camera. Spending just a few minutes can yield immediate, actionable insights without any learning curve. You can also get an assist on visual merchandising with Canva Pro’s AI-powered design tools for creating signage, displays and promotional materials, or Adobe Express’s smart templates and AI design suggestions for retail graphics.

●      Basic analytics. For about $50 per month and a time commitment of a half hour each week, premium features of Google Analytics with AI enhancement can help you monitor which products customers view online and which pages have the highest conversion rates. Use ChatGPT to analyze your Google Analytics exports, ask AI “What patterns do you see? What should I test?” or use Google Sheets to upload your sales data to ChatGPT and gain insights. Questions to ask include: “Which products are trending up?” “What should I reorder?” “Which categories are seasonal?” Or try pay-as-you-go Google Cloud Vision API for automated image analysis of your displays

●      SMB-focused merchandising tools. In the $50 to $200-per-month range, you can access various tools for ecommerce merchandising. Those include Fast Simon, which provides AI-powered search and product recommendations for Shopify and WooCommerce; Octane AI, offering personalized product recommendations and quizzes; and Rebuy, which features smart product bundling and upsells for online stores.

Thanks to these expanding options, smaller retailers are finding accessible entry points and seeing real results:

●      A boutique clothing store in Portland utilizes Couture.ai to automatically adjust its online product displays based on browsing patterns, resulting in a 23% increase in conversion rates. The owner spends 10 minutes a week reviewing AI suggestions rather than hours manually rearranging product pages.

●      A regional grocery chain implemented BeatRoute’s visual merchandising software and saw compliance with planograms jump from 60% to 92% within three months. They didn’t buy robots — they equipped store managers with tablets that showed AI-generated planogram corrections.

●      A single-location adult retailer (like the Livermore example) now uses photo analysis every time it resets a wall, catching visual issues before customers see them. Cost: $20/month. Time saved: two hours weekly on trial and error. Sales impact: 15% improvement in products-per-transaction on analyzed displays.

Enterprise Solutions

If you’re operating more than five locations, or generating over $50 million in revenue, more advanced tools become cost-effective. Here are some options for retailers working at a somewhat larger scale:

●      Visual merchandising platforms. Flagship provides comprehensive visual merchandising for multi-location retailers. Dragonfly AI offers real-time customer attention pattern analysis supported by over 10 years of university research. LEAFIO AI provides empty shelf recognition, heat mapping and planogram optimization.

●      Intelligent shelf management. Focal Systems has AI-powered cameras for 24/7 shelf monitoring with adaptive planogramming, Simbe Tally 3.0 offers robotic shelf scanning and Retail AI 360 image analysis assists with reliable stock management and precise pricing.

●      Pricing intelligence. Revionics and PROS Smart POM both offer AI-driven retail price optimization, while Clear Demand provides demand modeling and price elasticity analysis.

●      Comprehensive platforms. Vue.ai is a multichannel merchandising platform with automated product tagging, while One Door is a complete visual merchandising solution for planning and execution.

These enterprise solutions are useful when you’re coordinating merchandising across multiple locations, managing thousands of SKUs or operating at scale, where a 1% efficiency boost can generate millions in revenue.

Change Management

AI merchandising marks a major shift, from relying on intuition to making decisions based on data. However, the aim isn’t to replace merchandisers but to enhance their abilities. Successfully adopting this approach therefore involves training teams to collaborate with AI systems while keeping the creative elements of merchandising that depend on human insight. Begin by showcasing the benefits and results to your team. When AI recommends moving a product and it boosts sales, that gains buy-in more quickly than any training session.

You can also start with specific pain points instead of trying a full transformation right away. Choose one area where better data can yield quick results, like inventory accuracy, product placement or demand forecasting. Set a modest initial agenda like the following:

●      Week 1: Photo analysis. Take photos of three to five displays, get AI feedback and implement one suggestion.

●      Week 2: Track results. Did the AI suggestion improve anything?

●      Week 3: Expand. If AI did help, then analyze more displays. If not, try different prompts or approaches.

●      Month 4: Add analytics. Start feeding sales data into AI for pattern recognition.

Establish baseline metrics before implementation. Track not only sales but also operational efficiency, staff time saved and customer satisfaction. The ROI often comes from unexpected sources.

Key metrics for small retailers include:

●      Products per transaction. Are better displays driving multi-item purchases?

●      Display reset time. Are you saving time with AI guidance?

●      Markdown rates. Are you selling through faster with better placement?

●      Customer questions. Are displays more intuitive?

AI merchandising is no longer a futuristic idea but a competitive need. As consumer expectations keep rising and market conditions grow more complex, retailers who adopt AI-driven merchandising will be better prepared to offer personalized, efficient shopping experiences that foster customer loyalty and business growth. The question isn’t whether to adopt AI merchandising, but how quickly you can start learning from it.

Zondre Watson is the general manager of technology and analytics for adult retail chain Ero-Tech. With a background in finance, chocolate and controlled chaos, he blends retail know-how with AI tools to keep 17,000 products moving smoothly.