To many people, search is the little box at the top of a webpage, but it’s so much more. Today, businesses are dedicating greater focus on search capabilities and seeking more innovative ways to further improve the search experience. The last six to twelve months has produced a wealth of new technologies such as generative AI, vector search, and conversational AI, all poised to bring exciting enhancements to retail. But, what does all this mean and how can retailers engage and apply modern search strategies into their tech stack to increase revenue? The answer: retailers must take a data-first approach and leverage AI in order to truly understand the intent behind search queries. From there, search can help retailers provide fast, relevant, and personalized results that dazzle consumers and improve their bottom line.
The Importance of Data-Led Advanced Search
Did you know that 71% of retailers leveraging sophisticated search say it boosted their revenue? Despite this compelling statistic, many retailers manually approach site search, as keyword search engines power most search bars. As the name suggests, keyword search is based on matching the search query with keywords in the search index. The problem? Any term variations can cause the engine to fail, and you can’t write enough synonyms, rules and keywords to avoid this conundrum. Term variations have another name: the long tail. These long tail searches can confuse keyword search engines. Therefore, ecommerce site managers must spend considerable time writing rules, synonyms, or keywords to optimize the search experience for buyers.
Enter: End-to-End AI Search
Luckily, AI search adds more capabilities and functionality by leveraging customer engagement data. AI search acts more like a person by understanding what information the customer is searching for and what they need to complete the sale.
In 2023, many different AI technologies are in play, but the one that empowers this human-like comprehension of queries is called vector embeddings. Vector search works by analyzing the relationships between words and concepts, generating vector representations of words and phrases that capture their meaning in a more nuanced and contextual manner. Vectors understand how terms and ideas are related. For example, searching for “Adidas” via an AI search engine will return with results for Adidas as well as “Nike” and “Puma.” The search engine understands the overall concept of Adidas instead of only offering results that are a literal match to the search. With a hybrid search engine, retailers can combine both options and give customers a way to search by brand name, product type, symptoms, or descriptive words in order to get the best, most relevant results.
Gone are the days of the dreaded “no results found” page. Instead, customers searching for a “lovely bubbly for Sunday brunch” will be delighted with results for proseccos, champagnes, and sparkling rosé. Merchandisers rejoice: there’s no need to build a synonym library, write rules, or stuff your pages with keywords while hoping to get a keyword match. With AI, it works out of the box while saving you time and money.
A Revolution: Search As You Think
It’s exciting to think about the impact that AI-powered search will have on B2B and B2C sellers as they push for digital transformation, cost reductions, and faster, automated decision-making, and ultimately increased revenue.
With the ability to optimize search algorithms and improve the accuracy of search results, AI search presents endless opportunities for retailers to personalize the end user experience and drive growth in their businesses. Translation? It’s an indispensable tool for retailers looking to stay competitive in an increasingly crowded marketplace.
As the Chief Revenue Officer of Algolia, Michelle Adams is responsible for driving revenue at scale through worldwide alignment across sales, marketing, revenue management, and business development. She most recently served as SVP of Sales for the Americas at Dropbox, where she led direct sales, marketing, channel and customer success to grow its business by 10X in under four years. Prior to Dropbox, Adams was Global Head of Sales for IBM Watson, taking it from inception to nearly half a billion dollars in sales.
