Artificial Intelligence


AI-Powered Search Turns E-Commerce Queries Into Conversions

It’s a common refrain from both technologists and laypeople alike, but the past two years have reshaped the digital landscape. While many people are probably a bit tired of hearing this phrase — and other similar phrases — it is particularly important for companies with e-commerce platforms.

There are many ways companies can stay relevant as we enter a new era of e-commerce. It is safe to say that all e-commerce platforms should feature trendy product offerings, crawlable and mobile-friendly site architecture, and ensuring round-the-clock customer service. But above all else, having a strong on-site search could be one of the biggest factors in retaining customers and boosting revenue.

A good on-site search function can quickly steer a consumer to their desired destination based on a few simple keywords. More and more retailers are rethinking their current platforms as they strive to increase revenue and brand awareness.

Pleasing Uncompromising Consumers

Online shoppers are not only tech-savvy, but they know what they want. They prefer personalized and relevant results returned the first time they enter a query. Site search is one of the best tools to accommodate a fast-paced consumer, as it helps companies generate millions in additional revenue and makes consumers 1.8 times more likely to convert.

Sadly, as many have come to find, developing and maintaining a strong on-site search feature is much easier said than done.

The average on-site search engine has a difficult time interpreting ambiguous search terms, correcting misspellings and interpreting user errors. A 2021 study shows that 94 percent of consumers globally received irrelevant results while searching on a retailer’s website in the last six months, and 85 percent said they developed a poor impression of the brand after poor search results.

A poor on-site search experience can quickly lead to a customer abandoning a website. Site abandonment is a huge issue, as it collectively costs retailers in the United States more than $300 billion a year, according to research by The Harris Poll.

AI to the Rescue

This is where artificial intelligence (AI) comes into play. More and more companies are beginning to use AI in their search practices. Machine learning can leverage data such as clicks, add-to-cart, signups, conversions, and purchases to improve search result ranking as well as relevance.

For example, if the search term “iPhone” leads to 20 different results but the only ones being viewed are results number six and eight, then AI will know to push those two products to the top of the search results.

Even as consumer trends change over time, AI will continually adjust search results based on previous sales, as well as a consumer’s profile. This is similar to how Google improves search results over time — more relevant results get pushed up to the top.

Over the past 20 years, companies like Google and Amazon have built teams of thousands of data scientists and search engineers to design incredible AI capabilities. Both companies designed their AI capabilities against huge datasets with millions of users.

Most companies don’t have the resources to build their own in-house expertise, nor do they have the same traffic on which to hone their AI algorithms. Fortunately, emerging site search solution providers can offer very powerful on-site search for more typical e-commerce use cases.

While ranking and organizing search results can be done manually with traditional search engines, AI is far more accurate and requires much less effort. AI models can interpret the context of the website and consumer, which will provide accurate results almost instantly. Even if a user misspells a keyword or queries an irrelevant search term, an AI-powered search engine will be able to still be able to deliver relevant results.

Personalization Powered by AI

When search relevance and ranking are operating at a high standard, a high level of personalization can be achieved.

Personalization is one of the additional benefits some AI-powered search engines are able to offer. Eighty-three percent of consumers expect some level of personalization in their shopping experience, which means they expect a digital journey that is catered to their needs and past shopping behavior.

AI-powered search can provide personalized results and recommendations, which can increase average order size and provide greater user satisfaction. For example, if you know a customer has purchased an iPhone in the past or is browsing your site on an iOS device, you can personalize results on a search for “headphones” or “phone case” with Apple-related products.

The more data the better for AI-powered search to give smart product recommendations. It can include past purchase behavior, recent searches, profile attributes (such as gender), or browser-based IP attributes such as location.

Vector-Based Results

Another exciting component of AI-powered search is vector-based search results.

Vectors have been around for a while, but they are slower than keyword-based search and never took off. That’s changing, however, as new technologies come online. Vectors eliminate the need for companies to create and manage synonyms and can assist with longtail searches, symptom-based searches, and more.

Take a simple example like a jacket, which is sometimes called a coat, parka, or pullover. Traditionally, online retailers have had to create synonyms or add tags or other metadata so that visitors can find what they want regardless of the keywords they’re using. With vector-based technology, that becomes a thing of the past.


Without AI, companies must do an extraordinary amount of work to ensure their search engines are performing to a high standard. Most search engines operate based on manually written search rules and algorithms. Rules need to be constantly updated to make a search engine run to its fullest potential. Not to mention this approach often leads to inaccurate results.

These days, Google and Amazon dominate the online shopping market — this is because they are able to hire tens of thousands of data scientists and search engineers that can sell and distribute industry-leading products in an unprecedented rate.

AI-powered search gives retailers a stronger platform to compete with global marketplaces as they bolster their search practices.

Joe Ayyoub

Joe Ayyoub is chief revenue officer at Prior to, Joe served as chief customer officer at ZineOne. Before that, he was senior vice president of customer experience and partnerships at Unbxd and head of global support operations at Magento Commerce (acquired by Adobe).

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