Search Engine Evolution

In the age of Google and now ChatGPT, we take quality search for granted. We’re used to having information at our fingertips, but this ecosystem of instant gratification hides complex processes that enable us to find what we’re looking for.

Moving Beyond Keywords

Search and discovery has traditionally been driven by keywords, returning products that are the closest match to a user’s chosen search words. The problems with this approach are obvious: firstly, it requires both accurate classification of products. It also requires your customers to know pretty much exactly what they want to buy! While keyword search remains at the heart of most algorithms, including Google and Amazon, in e-commerce it has contributed to a failure rate in first searches of up to 17% and over two-thirds of consumers seeing irrelevant results.

AI and the Future of Search and Discovery

In September 2024, after months of testing, we fully integrated AI with our search. This enabled it to continuously critique and improve its own results. By training AI models to think like buyers, we were able to identify irrelevant results across thousands of keywords, helping us eliminate results that didn’t align with buyer expectations. Since this implementation, we’ve already had some clear improvements: 17.4% better engagement and 14.6% increase in conversions. Here’s how AI has enabled an optimized search and discovery process.

Deep Classification

AI enables a deeper and more complex keyword classification than could ever be afforded by a manual process. Our buyers typically start by searching broad industry themes, such as fashion or beauty, as they work on building brands within these categories. With tens of thousands of domain names in these categories, reliably recommending the most relevant names is impossible, even with a huge base of root keywords.

Connection With The Buyer Journey

Deep classification – and the accurate categorization it requires – is just one side of the coin of better discovery. The other side is your customers, those doing the searching. You must pair deep classification with data on buyer types and behavior. In other words, how buyers are browsing your marketplace. This will allow you to create meaningful associations based on real end-user search terms.

Search Is About Data And People

Effective search and discovery requires a two-pronged approach. Firstly, a deeper, more sophisticated product classification. Second, understanding your customers and their search intent.

Conclusion

Once you’ve perfected both, search is no longer a coin toss for your customers but an accurate and effective tool for bringing the right products to the right buyers. Search should be able to handle customers at all stages of the buyer journey, and provide relevant and desirable results for those with different degrees of knowledge and information about your inventory. It can be the final step to finding and buying a product, or a mid-funnel test of just what you have to offer, so it truly is a core part of your business as an e-commerce provider!

FAQs

Q: What are the limitations of traditional keyword-based search?

A: Traditional keyword-based search requires accurate classification of products and customers to know exactly what they want to buy, which can lead to a failure rate in first searches of up to 17% and over two-thirds of consumers seeing irrelevant results.

Q: How does AI improve search and discovery?

A: AI enables a deeper and more complex keyword classification, and by training AI models to think like buyers, we were able to identify irrelevant results across thousands of keywords, helping us eliminate results that didn’t align with buyer expectations.

Q: What is the importance of understanding customer behavior in search and discovery?

A: Understanding customer behavior is crucial in search and discovery, as it allows you to create meaningful associations based on real end-user search terms and provide personalized suggestions that are based upon how similar users interacted with those names in the past.