Revolutionizing E-commerce: How AI is Transforming Search and Discovery

The accessibility of the information now available, with the significant improvements in search engines and the new model, ChatGPT, sometimes even its availability becomes the unnoticed normal. Although these technologies are convenient us and give a lot of help, their work is based on various complex processes which take place in the background. However, the ubiquity of these systems often leads to an overlooked element in e-commerce: search and discovery.

Without a proper search and discovery function it becomes problematic to use and sell products and thus presents a tough challenge for e-commerce. It is a link between the people and the goods, it promotes sales and transformations, and helps to gain the confidence of customers. Thus, a suitable match to the customer’s needs earns the brand an appreciation from the customers. Now, AI is moving in, implemented by giants such as Amazon and Shopify, to enhance and fine-tune search and develop complex categorization replacing keyword-based strategies.

This is how the application of AI is revolutionizing the search and discovery on e-commerce platforms – the marriage of intent and products.

Moving Beyond Keywords

In the past, the FurtherSearch system was based on keywords; the system tried to find the closest class for the entered query. While functional, this approach has significant limitations:

Rigid Classification: It requires great accuracy in product categorisation.

Customer Assumptions: They assume that customers already know what they are looking for when they are out to shop.

Such constraints lead to a generation of unwanted or inadequate search results. It is established that first search sessions have a failure rate of up to 17 percent and 70.3 percent of users receive irrelevant product suggestions.

For example, a fashion or an eating delivering mobile application might benefit from keywords including jeans or Chinese food respectively. Although these terms form a functional foundation, the major customer needs remain unfulfilled, for example, ‘’fast shipping’, ‘’green clothes’’ or ‘’comfortable size.’’

As for naming, at Atom.com we are focused on offering brandable domains and many of them may include peculiar naming strategies aimed at eliciting certain emotions. These elements cannot be associated with particular words and, hence, cannot be located by traditional search means. AI helps us to interpret information in between through related opportunities, which are relevant to the consumer’s preferences and needs.

AI: The Future of Search and Discovery

In April 2008 during the months of in September, 2024 Atom.com advocated for another upgrade in which incorporated AI with its search system. By applying this artificial intelligent technique, the system is able to systematically assess and enhance its outcome in a way similar to a buyer, consolidating recommendations.

The results were transformative:

17.% Increase: Customer Engagement 4

14.6% rise in conversions

These advancements were achieved through key AI-enabled features:

Deep Classification

They include involving AI to provide a better keyword classification than manual processes of the same. In Atom.com’s purchases, in which buyers once enter general categories, such as ‘fashion’ or ‘beauty,’ AI provides specific suggestions from tens of thousands.

Using created keyword groups and linking them with themes, emotion, and name styles, AI determines the most suitable applications of domain name in a particular field. For instance, when using the search term “sustainable clothing brand” brands named “PurityCompass” would appear on top even when the key terms are not used.

This ability to directly associate the user search with the data presentation guarantees a perfect discovery in a proposition which is based more on the end-use rather than keywords.

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Enhanced Personalization

The online search using those algorithms is no only accurate but also personalized depending on the behavior of the customer. Hence in e-commerce firms gaining knowledge of the users’ needs and their behaviors, firms can recommend products and services that are needed again providing a unique shopping experience.

For instance, customers looking at categories such as ‘natural skincare’ may be exposed to other but related options that if clicked engages them deeply and makes them more likely to make a purchase.

Efficient Segmentation

It also helps to create a precise separation of customers based on the analysis of the search and preferences. It also helps brands to provide specific marketing campaigns that address the needs of different segments in the population.

AI is reinventing search and discovery in e-commerce — but instead of continuing to rely on key word searches it is making this process ever more complex, creative, fluid and pertinent to the individual user. Thanks to AI and its subset, deep classification, e-commerce segments, and personalization, brands are likely to benefit from improved customers’ satisfaction and business development.

It is therefore expected that the application of AI in search and discovery will become a permanent feature of growth in e-commerce business especially to make brands relevant in a growing market.