Top 5 Generative AI Use Cases for Product (CPG) Merchandising & Marketing

Revolutionizing product marketing with Generative AI

Generative AI, a frontier technology capable of learning from data and autonomously producing unique outputs, is poised to usher in a new era for product marketers and merchandisers. This revolution is not merely about automating repetitive tasks or digitizing traditional practices. It is about reimagining the very fabric of marketing, infusing creativity with intelligence, and personalizing the customer experience in unprecedented ways. The following five compelling use cases of generative AI showcase how it can redefine product marketing with enhanced efficiency, creativity, and customer engagement to drive mass personalization at scale.

1. Product Descriptions for E-Commerce

Crafting product descriptions for a vast catalog of items can be a tedious process. It demands a delicate balance between engaging prose that resonates with humans and SEO-friendly (search engine optimized) content that ensures search priority.

According to Shopify, there are millions of products without descriptions on their platform. And products without descriptive content reduce consumer confidence and typically don't sell.

Tools like their recently announced Shopify Magic or ChatGPT can be used to automate the creation of product descriptions using keywords and suggested tones.

Though this has been an early example of efficiency and time savings for product merchandisers, I can foresee advancements in the near future. Imagine copywriters capable of creating multiple descriptions for products and then testing them across different channels to synthesize the results for optimal and dynamic output based upon consumer profiles.

For a more personalized approach, AI could recognize the consumer and adapt its content to connect on an emotional level. Instead of writing cookie-cutter content, product pages and their descriptive content could be tailored to each individual visitor.

2. QR Codes as Digital Art

Recently, I've been intrigued by the potential of AI-generated artwork to reshape how brands connect with consumers. The innovative use of Generative AI to blend product identifier data with corporate branding can result in visually stunning images.

You already know that QR codes are used for marketing, product traceability, advertising & more. But they're boring black and white squares that are real estate hogs in print and product packaging.

Welcome to the future of retail marketing, where we can infuse branding seamlessly with product identifiers.

Blending techniques are capable with tools like ControlNet for StableDiffusion, or from new AI startups, which I beta tested. With specially trained models, new images can be morphed from an existing code along with text-based prompts. The blending takes advantage of the inherent error correction built into QR codes, which allows the reference data to be restored even if it's partially damaged or obscured.

One example I conjured showcased a mouthwatering stack of pancakes to sell the experience of melted butter for a dairy brand. Another shows a bubbly glass of soda on a beach, with seaweed on the shore cleverly morphed into the QR code.

Though I am not an expert digital artist, it is important to note that these were developed as a test while drinking a cup of coffee. Imagine the possibilities with more time and technological advancements. With additional enhancements to image blending, we may even soon see hidden QR codes in print or streaming media.

3. Experiential Omnichannel Engagement

Now let's take the previous example of QR codes and generative AI artwork and add a splash of augmented reality. The mashup of GenAI and AR can revolutionize experiential retail engagement across multiple channels: in-store, online, and even after purchase.

In the example video below, the artist (@XRArchitect) showcases using a webAR experience on a mobile device. This required no third-party apps - simply point, click, and then accept permissions in the mobile browser for an immersive experience in seconds.

Brand marketers and advertisers can now think about surprising and delighting consumers wherever they are - directly from the product, in print, in-store, online, and from streaming media. Imagine new engagement possibilities directly from product packaging or from digital shelf labels. This will allow brands to truly reimagine the future of retail.

4. Generative AI for Visual Merchandising

Retail planograms, the visual merchandising tools that dictate how products should be placed on retail shelves and fixtures, are more than just simple blueprints. They are strategic layouts designed to optimize product visibility, increase customer purchases, and enhance overall sales. These schematics are developed through a meticulous process that considers factors such as product size, category, and popularity, as well as store layout and demographic information.

In large stores, the challenge of creating and managing planograms is exponentially amplified. The vast assortment of products, along with frequent changes in consumer behavior and preferences, often make the process of keeping planograms updated a herculean task. This often leads to non-optimized product placement, which can reduce sales and customer satisfaction.

Generative AI has the potential to optimize planogram development by processing and learning from a wealth of data. Imagine a system that tracks the efficiency of each product on the shelves, understands the nuances of customer shopping behaviors, and adjusts the product layout dynamically to ensure maximum product turnover. This intelligent process eliminates the guesswork and human bias, focusing on what truly matters: selling more products efficiently.

But the capabilities of generative AI don't stop at optimization. By using generative AI artistic tools like StableDiffusion and Midjourney, we could automate unique planogram renderings, effectively creating a 'digital twin' of a retail environment. This would not only save countless hours spent on manual planogram creation but also provide a more accurate and efficient plan for product placement.

Now, let's get a little imaginative.

What if we could place the products on shelves in such a way that the arrangement itself forms a QR code when viewed from a certain angle or distance? We could weave subtle, interactive marketing campaigns right into the planogram, creating a hidden layer of customer engagement.

Imagine a customer using their smartphone to scan an aisle, only to be led to an immersive marketing experience, a discount coupon, or a fun game. It's a way to transform the shopping experience, making it more engaging and rewarding for the customer and, in turn, more profitable for the retailer.

This innovative approach to planogram creation is not only exciting, but it's also closer than we might think. Pictured above is what an imaginative developer shared on Reddit in a post titled "How to send a secret message with your fruit stall."

5. Reimagine Product Marketing with Generative AI

Imagine the logo of a brand you recognize instantly - perhaps the iconic swoosh of Nike. This image is deeply ingrained in our minds due to consistent, repetitive, and impactful marketing. However, creating such uniform, brand-focused marketing assets for different campaigns and various regions is not an easy feat. It requires a creative vision that respects the brand's identity while also considering the unique cultural nuances of diverse markets.

This is where generative AI art tools come into play, transforming how marketers create consistent, on-brand, and localized assets.

With the power of generative AI, marketers can merge images together, effectively allowing brands to integrate their recognizable symbols, logos, or other graphical elements into new visuals automatically. Picture the Nike swoosh seamlessly blended into an array of different images - a bustling cityscape for an urban streetwear campaign, a serene mountain range for a hiking gear promotion, or a vibrant carnival for a unique limited-edition release.

These localized yet consistent visuals can be generated automatically using generative AI tools such as StableDiffusion ControlNet or Adobe. By feeding in text and keywords, marketers can instruct the AI to create assets that not only incorporate the brand's logos, colors, and other branding elements but also cater to the specific needs of different demographics.

Now, let's envision global campaigns that require localization of messaging. With generative AI, marketers can automate the creation of campaign visuals tailored to resonate with customers in New York, Tokyo, San Paolo, and beyond. Think about it - a single marketing team creating location-specific, culturally aware, and on-brand visuals, all with a few keystrokes.

But it's not just about localization. Generative AI also opens the door to mass personalization, allowing brands to tailor their graphics dynamically to individual customers while maintaining a consistent brand identity. This could be a game-changer in an era where consumers increasingly expect personalized experiences.

This is not just about saving time and resources, though that's certainly a significant benefit. It's about redefining the creative process, about giving marketers the tools to produce work that is consistent yet dynamic; global yet local; efficient yet impactful.

The future of marketing lies in embracing these intelligent tools. As generative AI continues to evolve, it promises to bring even more exciting possibilities for brand marketing. The days of static, one-size-fits-all marketing assets could soon be behind us. Instead, we're moving towards a future where marketing visuals are as dynamic, diverse, and personalized as the customers they're intended to reach.

Generative AI is not just a tool - it's a catalyst for a marketing revolution, and brands that adapt and embrace it will be at the forefront of this exciting new era.