How Generative AI can make search results on websites more functional and error-free

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While shopping for a hat online, you add cowboy hats in the site search query, but search results show children's T-shirts with a cowboy on them. We’ve often come across search bars, where no matter how much we try to specify what we want, it shows some other result entirely. For most sites, search is still in the stone age of web browsing. Despite the advancements the world has experienced in today’s web age, they fail to deliver accurate and personalised results.

Why can’t conventional site search bars keep up?

Inaccurate results primarily occur since conventional site search bars heavily rely on keyword matching to generate responses, which historically hasn’t been the most effective. Due to limited sophistication in search algorithms, search bars struggle to understand context and nuances.

Think of how OTT searches function—when searching for what to watch on an OTT platform, searching for a particular movie, and by entering even a few alphabets, it knows the movie you’re looking for. Similarly, when looking for a movie that has a sequel, it could make this suggestion right in the search section or the home screen. Such search experiences eliminate the dread of interacting with an app and continue to make movie-watching fun. Unevolved site search bars are bad for business. Further, inaccurate search isn’t just an inconvenience that many are trying to ignore, it has the potential to create actual damage that can go far deeper than one can imagine.

A report highlights that around 69 percent of consumers go directly to the search bar when visiting an online retailer, but 80 percent of those surveyed admitted to leaving because they were dissatisfied with the on-site search experience. It also highlights a traffic bounce rate of 39 percent caused due to poorly performing search offerings and shoppers being unable to find relevant products.  

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To make matters worse, these search technologies rarely offer personalisation—most of their responses are generic without any consideration of user preferences or past behaviors. This rather one-size-fits-all approach results in a search experience that doesn’t wow its users, forcing them to sift through a ton of irrelevant results, wasting their time and eventually offering a disappointing customer experience.

This only makes customer retention more difficult, struggling to keep them engaged with the platform and hampering the smooth exchange of data, which affects the platform’s long-term potential.

Generative AI’s potential to revolutionise site search

The world has been riding the AI wave and this groundbreaking technology has been boosting efficiency across domains and sectors. Now, it also has the potential to improve conventional site searches. Leveraging Natural Language Processing (NLP) and machine learning (ML), the platform learns from information that the users are entering in the search bar to generate the most appropriate search results.

The learning happens in real-time and tunes the results in the background, unique to every individual. This tuning can be refined based on the individual’s past activity, common spelling errors, and understanding the intent behind a search query based on the language.

Here are some ways it stands out compared to traditional site search:

Better understanding of user intent: With every search query a user enters, they’re also communicating their specific need or desire. While traditional search might just look for keywords, AI site search uses semantic search—essentially it is smart enough to understand the context and intent behind the search, beyond mere keywords—ensuring the most relevant results at all times. For example, if you’re searching for baby diapers, the site could also suggest baby clothes and other paraphernalia, assuming you’re shopping for a newborn child.

Personalised search results: Since the AI learns about user behaviour and keeps a record of their search queries in real-time, it can predict and proactively offer suggestions. For instance, if an e-commerce site knows about your fandom for a football team, it can suggest similarly themed merchandise.

Agile adaptability: By actively tweaking the algorithms, AI-based site search can adapt to changing trends and market shifts. The idea is to ensure that the tool stays closely aligned with the goals set by the users and find whatever they’re looking for, even if it didn’t exist moments ago. For instance, a buyer looking to buy a phone gets the newly released smartphone as a search result, moments after it’s launched.

Improved customer experience: With more accurate and personalised search results, users will enjoy a smoother and more satisfying experience. This improvement in user experience can lead to higher engagement, increased loyalty, and a stronger connection with the brand or platform.

Also Read: What business leaders really think about Generative AI

By offering a superior search experience, businesses can differentiate themselves from competitors and drive more value from their online presence. Enhanced search capabilities can lead to better customer insights, more effective targeting, and ultimately, increased conversion rates. With AI-powered search, we can move beyond mediocre results, providing users with accurate, personalised experiences that drive significant business value.

The writer is the co-founder and chief product officer at CleverTap.

The thoughts and opinions shared here are of the author.