5 Ways AI-Powered Search is Different Than Traditional Filtering

AI is making a huge impact in the ecommerce space, but it goes beyond generating product descriptions and chatbots. Product search and discovery are two areas where AI actually transforms the shopping experience. The promise of applying this new technology is simple: showing customers more relevant products, faster than ever. 

Key Takeaways

  • AI-powered search is more robust than search with filters, as it builds results based on matching keywords.
  • AI utilizes semantic search, making the process more intuitive and easier for consumers.
  • AI has the ability to account for individual preference, buying history, and previous search text, which can enable more personalized and unique product recommendations.

The Difference Between AI and Filters

Many people still wonder: Can’t you do that with existing features like filtering? 

The short answer is “No.” 

When you see AI-driven search in practice and watch as products appear according to shopper input, it may not look or feel that vastly different than the results you get after checking a few filter boxes. 

But it’s important to keep in mind this key difference:

  • Search starts with the entire universe of available products a brand offers and adds results based on matching criteria.
  • Filtering begins with a set list of products and removes items that don't match the selected criteria.
It’s building results according to personal input and preferences, versus reducing selection based on matching keywords. 

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Here are 5 essential differences between AI-powered product discovery and traditional filters. 

AI Has a "Brain"

With semantic interpretation, AI search understands the meaning and intent behind user queries, going beyond simple keyword matching. It naturally tracks synonyms, context, and colloquial language, providing more relevant results.

This means that users don't have to think like a computer. They can enter what they need or know of a product and get more accurate results.

AI Can Get Deep

AI understands complex queries and can process and understand complex, natural language statements, while filters typically rely on predefined categories or attributes.

Rather than entering a few words and having to keep filtering down, users can ask a question as they would ask it to a salesperson. The results are more accurate, creating a replica in-store experience as if the user has a personal shopper. 

AI Knows Where You're Headed

AI’s predictive capabilities process user needs and suggest products or content before the user completes their query, which is not possible with traditional filters.

This saves time for the user, especially if they're searching based on a concept rather than a specific product. For instance, "I need shoes for a wedding in October" yields results as they're typing, enabling them to skip things that would be required by filters, such as shoe size.

You Don't Need a Perfect Match

With AI you don’t have to have a perfect match. Using “fuzzy matching,” AI search interprets misspellings, partial matches, and variations in product names or descriptions, while filters typically require exact matches.

This not only mimics natural language use, it offers accurate results to those for whom English may be a second language, users who are rushed for time and thus use abbreviations, and is more disability-friendly.

AI Gets to Know You

AI search is personalized and adaptable, tailoring results based on individual user preferences and behavior, and offering a more personalized experience compared to standard filters.

This enables not only more accurate results, but better upselling opportunities, for a larger cart total overall. Returning customers can see items that complement their past purchases, increasing trust in the brand and likelihood of conversion.

Conclusion

As you can see, there is much more to AI discovery than meets the eye, including a more thoughtful and relevant browsing experience for shoppers.

Talk to us about visual discovery AI to learn more. 

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