Effective ecommerce search is one of the most underrated revenue growth strategies. Conversion rates can rise by up to 50% when businesses exploit the site search.

Moreover, recent research suggests that on-site search powered by artificial intelligence can increase the conversion rate by about 216%​ [1]​.

A converting site search has to understand the search queries, decipher the user’s intent, and deliver query-matching products.

But what if the user types in a super long query like a blue woolen winter midi dress for women size XL?

The search engine has to deliver precisely that. Here’s how AI site search can process even the long tail keywords.

Long tail keywords are search queries that are more specific and detailed than general terms, making them more challenging to match with relevant products.

A user can strictly define a product he needs by naming all expected features like size, pattern, function, model, color, and other relevant criteria. Alternatively, he can also type a generic search term, like a Christmas gift for a toddler boy.

Current users expect ecommerce websites to satisfy their requests and personalize their shopping experience.

Every second shopper admits they are more willing to buy from e-shops that adapt product browsing experience based on their preferences.

That means a site search engine has to process and understand even longer search terms. Moreover, studies have shown that personalized product recommendations, a feature greatly enhanced by AI, contribute to approximately 31% of online sales​ [1]​.

Traditionally, ecommerce sites have used a manual approach to process search queries. It involves creating an extensive list of keywords and mapping them to the relevant products.

However, this approach is limited as it relies on pre-existing knowledge of what users might search for, which is not always accurate.

AI-based site search, on the other hand, uses natural language processing (NLP) algorithms to understand the context of the user’s search query and match it to the most relevant products.

It doesn’t rely on pre-existing knowledge of what users might search for. Instead, AI algorithms analyze the user’s search query and match it to the most relevant product based on its features, descriptions, and attributes.

Just like you would say what you want to buy to a shop assistant, you can now tell it to an e-shop. And it has to be understood.

AI significantly improves conversion rates across various sectors, demonstrating its versatility and effectiveness in understanding and responding to customer behavior.​ [2]

How can AI site search process long tail keywords?

Keyword expansion

AI can analyze the user’s search query and expand it by adding relevant keywords that may not have been included in the original query.

Similarly, a shop administrator can do it manually by adding product synonyms. It helps to match the user’s query with the most relevant products.

AI can use semantic search algorithms to understand the context of the user’s query and match it to the most relevant products.

It is especially useful for processing long-tail keywords that may be ambiguous or have multiple meanings.

Furthermore, autocomplete in site searches has proven to boost conversion rates significantly, offering a smoother and more intuitive search experience for users​ [3]​.

Besides, it not only improves usability but also contributes to higher customer retention and loyalty, driving more frequent visits and interactions on the site​ [3].

Product tagging

AI can automatically tag products with relevant keywords or assign specific filters based on their features, descriptions, and attributes.

AI systems can then match the user’s search query with the most relevant products quickly and accurately.

Product recommendations

AI can analyze the user’s search query and recommend products that are closely related to the user’s search query.

Besides, AI-powered Product Recommender analyses previous user interactions with the website and the search and suggests highly user-relevant product recommendations.

It allows users to find products they might not have thought of but which still match their search query.

Exploit the power of the AI-driven ecommerce site search to grow your business

AI-driven site search is a powerful tool that can help ecommerce sites process long-tail keywords effectively and drastically boost business sales and grow revenue.

LupaSearch is the site search partner that can help your business exploit the benefits of effective site search.

By using natural language processing algorithms and semantic search, the LupaSearch engine can understand the context of the user’s search query and match it to the most relevant products.

Some of our customers witnessed a 40% growth in their site conversion rates within the first months.

Schedule a demo with LupaSearch and enable your e-store to provide a more personalized and efficient shopping experience, ultimately leading to increased business sales.

References

  1. Using AI to Optimize E-commerce Conversion Rates (With Infographic) - Capturly Blog (2022).

  2. Marcin Hylewski. October 20, 2023. Conversion Rate Optimization with AI in 2023 (+6 Examples) (landingi.com).

  3. Ornaith Killen. November 14th 2013. Four reasons why site search is vital for online retailers (econsultancy.com).