The Future of E-Merchandising: AI and Personalization

e-merchandising rack of shoes feature

E-merchandising is getting a significant boost from generative AI (credit: Martin Adams on Unsplash)

The world of e-merchandising, i.e., the art of presenting products and services in an enticing and captivating way online, has evolved significantly over time. It traditionally relied heavily on the expertise of merchandising teams, supported by software tools like ecommerce websites, Digital Asset Management (DAM) and Product Information Management (PIM) systems.

However, with significant AI advancements and extensive research, the profound impact of AI on the future of e-merchandising is becoming increasingly evident. In fact, 60% of brands and retailers are planning to invest in AI in the future to automate product visual content on online channels. Yet, to truly harness this potential, careful consideration and specific measures must be undertaken.

Following the dictum “garbage in, garbage out,” data inputs need to be sufficient to realize meaningful insights in order to harness the power of AI. For example, if a retailer only has one image per product, there is not much AI can do. But with a greater number and diversity of photos, AI can display more relevant photos based on a shopper’s unique aesthetic. To truly take advantage of AI, retailers need to scale image creation at a rate that was previously impossible.

This principle applies to all potential AI use cases in retail, including generative AI. Let’s explore a few areas where this technology can improve the customer experience and affect real change.

Personalized Experiences for Enhanced Customer Engagement

Data, when plentiful, offers crucial customer behavior insights, why they make decisions and even helps predict future behavior. But the key to making this data effective is twofold — how you analyze it and how you leverage it to deliver personalized experiences at the right time. AI algorithms can perform this analysis and make it easier for you to offer personalized product recommendations, pricing and promotions based on individual preferences and historical actions and purchases.

We know this is important for e-merchandising. In fact, in our recent Shopper Sentiment Report, 60% of consumers said they’re more likely to purchase when the images show products in a context that matches their personal aesthetic or interests. Tailored imagery is one way to make sure customers feel understood and actually stick around to engage with your collection and product description pages (PDPs).

These effects are magnified when using generative AI. On top of tailored imagery in a PDP, generative AI can create unique product descriptions tailored to each shopper. Instead of generic blurbs written in a universal tone that call attention to the same features, these customized descriptions can be completely unique, each one based on the shopper’s geography, demographics, preferences and behaviors. For a baby boomer based in Montana during winter, a couch’s warm, cozy material might be featured. But for a millennial parent, the couch’s stain resistance may be the headline.

Endless Possibilities with Dynamic Imagery

Making personalization come to life is where dynamic imagery comes into play. I envision a world where a consumer who has purchased a sleek lamp and minimalist desk is shown an ad depicting the same aesthetic: a simple, understated rug showcased in a modern home. And a consumer who keeps browsing farmhouse-style items clicks on a couch PDP and sees the couch featured in a living room complete with farmhouse decor.

AI-powered engines, in partnership with CGI technology, can fuel this, dynamically adjusting images and product promotions in real time. This functionality is helpful beyond personalization in e-merchandising.

As AI continues to evolve, these types of innovations will only become more powerful. Featuring a couch, but the pillows you typically display with it are no longer available? AI will be able to automatically accessorize the couch with different pillows or a throw blanket that’s in stock. The possibilities are endless.

Data-Driven Product Recommendations

Retailers have tried to offer relevant product recommendations for years to shoppers, often using information like previously-browsed products or products that have been added to cart to surface ideas for accompanying products. With the rapid advances in AI, these recommendations can become even more data driven and precise.

Retailers are beginning to offer AI-powered shopping assistants that help consumers find items based on their unique needs and preferences. In some cases, these offers could be for products that a shopper didn’t know existed or has never seen before.

I see this as just the tip of the iceberg for AI recommendations in e-merchandising. Instead of just offering a product catalog, retailers will be able to solve shoppers’ problems and satisfy their queries with an exact product. Need a pair of shoes to match the shade of an old suit you’d like to wear? Wondering what texture couch pairs best with your current rug? Generative AI will be there to save the day — and improve your style.

Making Visual Search Fast and Simple

Finally, AI has incredible implications for visual search. Ever see a photo of an item, perhaps when scrolling Instagram or browsing the web, and wonder what it is and where it’s from? If it’s a product you’re interested in, this can be frustrating. Perhaps you think of a few words to describe them and plug them into Google, to no avail. Maybe something similar shows up, but it isn’t exactly what you were looking for.

Visual search powered by AI can solve this in an instant, simplifying and expediting the process. In a world where products can be instantly found, customers will be delighted, and their shopping experience online will improve.

Here’s to the Future

When considering AI, various possibilities come to mind. But when it comes to AI for retail,  the focus is on the potential to transform the shopping experience, whether through personalized visuals or tailored product recommendations.

By accessing curated content and offers, consumers can confidently make purchases in less time, without having to sift through irrelevant products. As a result, they become satisfied customers eager to return for future purchases.

Sam Parnell is CTO of Nfinite