AI-Enhanced Product Discovery and Recommendations in Ecommerce

By Gabrio Linari, Last Updated on 24 February 2025

AI-Enhanced Product Discovery and Recommendations in Ecommerce

Over the past few years, the ecommerce landscape has gotten a little wild. We’ve seen it all: from figuring out how to best apply Product-Led SEO (shoutout to Eli for seemingly having it all sorted) to dealing with the C19 madness that had everyone holed up at home, spending like there’s no tomorrow. But perhaps the biggest shakeup has come from the rapid rise of AI, which has turbocharged pretty much everything happening online.

Search for “2024 ecommerce case study,” and you’ll stumble upon all sorts of success stories, like Glossier’s rise to a $1.2 billion company or how Lunya pulled off $25M in revenue. What’s the common thread? Personalization. That’s the magic word. Today’s customers aren’t just looking for a product; they want an experience tailored to their tastes, needs, and whims. And who’s helping drive that personalization? AI, of course.

AI has had a transformative effect on ecommerce, especially when it comes to customer service. Take Riley Watson Jewellery, for example. They were dealing with a flood of traffic, but a frustrating number of visitors were just window-shopping and not buying. Enter Manifest AI. By integrating a conversational AI assistant that aligned perfectly with their brand, Riley Watson not only personalized the shopping experience but also saw conversion rates nearly triple (6.21% vs. 2.02%). The AI even managed to bump add-to-cart rates by 143% while autonomously handling 97.57% of customer interactions. But wait a second, what is conversational search?

But what’s really transformative here? Well, let’s break it down.

The Magic of AI in Product Discovery

Let’s talk about why AI is such a game-changer for product discovery. Imagine AI as a super-powered refinery for data. In the world of ecommerce, AI doesn’t just sift through data; it processes, refines, and turns it into actionable insights faster than any human ever could. We’re talking about analyzing mountains of data in seconds, not hours or days.

This kind of speed and accuracy means businesses can get a crystal-clear view of market trends and consumer behavior in no time. And when you understand your audience that well, you’re in a prime position to create products that hit the mark. So, AI isn’t just transforming how we research; it’s revolutionizing how we plan, develop, and deliver products to market.

From Planning to Personalization

Now, let’s take it a step further. AI doesn’t just stop at helping you understand what your customers might want. It follows through to the final stages, where it tailors product recommendations to individual user preferences. It’s like having a super-smart personal shopper for every visitor to your site.

Picture this: you’re shopping online and mention that you like the color blue. The AI behind the scenes isn’t just noting that; it’s connecting the dots between that preference and other data it has on you (like previous purchases, browsing habits, etc.). Then, it starts presenting you with the best blue items in your size, style, and price range. Over time, this AI learns from each interaction, continuously refining its recommendations and making them more accurate and personalized.

And it’s not just about offering products you might like, it’s about offering them at the right time and in the right way. This is where AI’s real-time adaptability comes into play. As it interacts with more users, it picks up on patterns and trends, adjusting its approach to meet ever-changing customer demands.

2 Case Studies That Highlight AI’s Impact

Take Gucci, for example. Their ecommerce platform leverages AI to enhance the user experience through personalized recommendations and chatbots that engage customers in meaningful conversations. This isn’t just about pushing products; it’s about building a luxury shopping experience that feels bespoke.

Then there’s Frank Body, a brand that used AI to power its content marketing strategy, leading to $20M in annual sales. The AI didn’t just recommend products; it created a cohesive brand experience that resonated with customers on a personal level.

User Retention and the AI Edge

Let’s talk user retention for a moment. Imagine you’re selling a product, and suddenly you notice a drop in user engagement, maybe because the pricing is too high or the value proposition isn’t clear enough. With AI-enhanced systems, you don’t have to just accept that drop-off. Instead, AI can identify those at-risk users and nurture them back into the fold.

For instance, it might recognize that certain customers are price-sensitive and offer them tailored discounts or bundle deals that provide better value. Over time, AI can track how these interventions affect user behavior, fine-tuning its approach to maximize retention.

The Tech Behind the Magic

Let’s dive into the tech that’s making all of this possible: Natural Language Processing (NLP) and Machine Learning (ML). These aren’t just buzzwords; they’re the backbone of AI-enhanced ecommerce.

NLP (buzzword) is essentially how machines understand and process human language. Imagine a customer typing “red shoes with a low heel” into a search bar. In the old days, search engines might have just focused on matching keywords, but NLP allows AI to grasp the context and intent behind the search. It doesn’t just look for items labeled “red” and “shoes”, it understands that “low heel” is a crucial part of the request and prioritizes results accordingly. This means customers are more likely to find exactly what they’re looking for on the first try, which is a win for both shoppers and sellers.

Machine Learning, on the other hand, is what allows AI to get smarter over time. It’s like having a personal shopper that remembers your style, size, and preferences, and continually refines its suggestions the more you shop. For example, if you often buy eco-friendly products, ML will learn this and start recommending similar items, even if you’ve never explicitly stated that preference. Over time, this leads to a shopping experience that feels tailor-made for each user, which is exactly what today’s customers expect.

The Challenge of Algorithmic Bias

But, of course, AI isn’t perfect. One of the major challenges we face is algorithmic bias. Since AI systems learn from data, they can inadvertently pick up on biases present in that data. This can lead to skewed recommendations that don’t serve all users equally. For example, if an AI system is trained predominantly on data from a particular demographic, it might underrepresent products or preferences from other groups.

Addressing algorithmic bias isn’t just about fairness; it’s also about business sense. If your AI is unintentionally alienating a segment of your customer base, you’re leaving money on the table. To combat this, companies need to ensure their AI models are trained on diverse data sets and are regularly audited to identify and correct any biases that emerge. It’s about creating an AI that’s not just smart, but also fair and inclusive.

Wait a Sec, How Do We Scale Up Then?

Deploying AI at scale is no small feat. It’s one thing to test AI on a small section of your business, but rolling it out across an entire ecommerce platform requires a robust strategy and significant resources.

Take eBay, for instance. They developed a “Magical Listing Tool” that leverages AI to streamline the process of listing items for sale. This tool uses computer vision and machine learning to automatically categorize items, suggest prices, and even generate descriptions. What’s impressive here is not just the tech itself, but how seamlessly it integrates into eBay’s existing infrastructure. Sellers can list items faster, with less effort, and with more accuracy, which, in turn, drives more sales.

But the real magic lies in the tool’s scalability. eBay didn’t just deploy this on a small scale; they integrated it into their entire platform, where millions of sellers can benefit from it. This required eBay to ensure that their AI could handle a massive and diverse array of products without sacrificing performance or accuracy. It’s a perfect example of how to successfully scale AI in ecommerce, demonstrating that with the right approach, AI can enhance every aspect of the user experience.

Balancing Personalization with Privacy

Of course, all this personalization comes with a caveat: user privacy. Not every customer is comfortable with their data being used to personalize their shopping experience. With privacy-focused browsers like Brave and Mullvad gaining traction, marketers need to be aware that they won’t be able to reach 100% of users with AI-powered personalization.

So, what’s the solution? It’s a mix of embracing AI where it’s welcome and falling back on tried-and-true tactics where it’s not. For those customers who prefer not to share their data, businesses can still offer great experiences by focusing on content, customer service, and general best practices in UX design.

The EU’s Latest Guidelines

Lastly, let’s not forget the ethical considerations. With AI becoming more ingrained in our daily lives, there’s a growing need for guidelines to ensure it’s used responsibly. The EU recently introduced their Ethics Guidelines for Trustworthy AI, which outlines principles like transparency, fairness, and accountability. For ecommerce businesses, adhering to these guidelines isn’t just about compliance, it’s about building trust with customers in an increasingly AI-driven world. Did you guys know about this?

Think Creatively 🧠 First, Use Data Later

Let’s get real for a second: brand owners, CMOs, and directors of marketing, you know your brands better than anyone else. While it’s tempting to let data drive every decision, remember this: you’re appealing to real customers, not just algorithms. You’re not selling to a robot (at least not just yet).

Here’s a free tip: after enabling those AI-enhanced product discoveries, have you actually asked your customers if they’re happy with the new setup? This could be a game changer, especially when it comes to reconnecting with your former, possibly bored users. Why not engage them directly? Offer a prize or a subscription to your service in exchange for an honest video feedback. Not only could this feedback be featured on your site, but it also opens up a dialogue with your customers, showing them that their opinions matter.

Leverage this user input to feed back into your data and create a feedback loop that continuously improves your strategy. Sure, this approach won’t work for every brand. If you’re offering a SaaS product for accounting, it might not be the most exciting, but for beauty brands, influencer-led businesses, and other consumer-facing industries, this is an avenue you shouldn’t discount.

Yes, it might seem obvious, but in the frenzy of data-driven decision-making, we sometimes forget where marketing originally started: with creativity and human connection. By blending creativity with data, you can refine your strategy and ensure that you’re not just meeting expectations but exceeding them. AI is here to help with the execution and the heavy lifting, but it’s creativity that will keep your brand feeling fresh and connected to your audience.

And who knows? Maybe you’ll get those inspiring ideas while on the 🚽. Sometimes, that’s where the best ideas come from. 😉

Final Thoughts

AI is clearly transforming ecommerce from top to bottom. With NLP and machine learning, we’re seeing more personalized and effective shopping experiences. However, companies must be mindful of algorithmic bias and the challenges of integrating and scaling AI systems. Case studies like eBay’s “Magical Listing Tool” show us that with the right approach, AI can be both scalable and incredibly impactful.

Looking ahead, the future of AI in ecommerce is bright, but it will require continuous innovation and careful consideration of ethical implications. Those who get it right will be the ones leading the charge into the next era of digital commerce.

If you wish to discuss further how AI product discovery applies to your brand, don’t hesitate to get in touch.

About The Author

I have over 15 years of professional experience spanning SEO, strategic digital transformations, and business growth initiatives. My expertise lies in aligning SEO efforts with business goals to drive meaningful results. I regularly post on LinkedIn about Growth Marketing, remote work, and inspirational topics. Check out my latest posts on Gabrio’s Thoughts and subscribe to my YouTube Channel ROCK SEO (Rocky is the boss!). You can discover more about me here.