Have you noticed that the current keyword-based search engine does not provide relevant search results? Or at least could it work much better?
Semantic search technology appears to be a promising solution that can solve many website search problems and completely replace the default keyword-based search.
So what is semantic search, why should you use it in your business, and can it become the future of ecommerce?
Why is keyword-based search not enough?
43% of all website visitors head directly to the search bar. These people expect your website to provide a smooth shopping experience, so they can find what they need fast.
But, sometimes, these users encounter challenges.
Keyword-based search relies on exact matches between the user’s search query and the keywords in the website content. It typically considers each word in the site search individually and searches for its equivalent on the website.
Therefore, when a user types in “snacks,” a keyword-based search will not deliver olives, bruschettas, or Parmigiano cheese. Instead, it will look for products that contain the word “snacks” in the title.
This way, the site search might return a few sets of snacks or, in case you don’t have them, a blank page. Eventually, it leads to inaccurate and irrelevant search results.
And that is costly and lost sales potential.
What is semantic search in ecommerce?
Unlike traditional keyword-based search, semantic search understands the meaning behind the user’s query and delivers highly accurate search results.
An effective search engine that supports semantic search also evaluates the context of the search term.
For instance, if a person recently searched for olives, cheese, and wine, the next time this person searches for “snacks,” the search engine will mainly suggest Italian appetizers.
Therefore, shifting to semantic search drastically improves user experience, boosts the site’s conversion rates, and increases your revenue.
Keyword-based search vs. Semantic search
In contrast, semantic search engines use Natural Language Processing (NLP) and Machine Learning (ML) algorithms to understand the meaning behind the user’s query and the context in which it is being used.
It allows the search engine to deliver more accurate and relevant search results that match the user’s intent, even if the search query does not contain the exact keywords being searched for.
In other words, if a person is looking for snacks, the site search should deliver products that are considered - but not named per se - as snacks.
The difference between the two types of search becomes evident.
The keyword-based search is limited compared to semantic search because it cannot grasp the intent behind the user’s search and can only deliver results based on exact keyword matches.
Is semantic search the future of site search?
Semantic search has the great potential to revolutionize ecommerce site search by enabling more accurate and personalized search results for each user.
However, although semantic search is a promising technology, it is not a silver bullet that can solve all ecommerce site search challenges.
Ecommerce businesses must also invest in continuous data analysis, frequent algorithm updates, and site search improvements to ensure their semantic search capabilities deliver the best possible results.
How can you include converting semantic site search into your ecommerce search strategy?
To take the most out of semantic search and enjoy the spike in ecommerce conversions, follow our tried and tested strategy.
1. Choose a reputable site search partner that supports semantic search. For example, with LupaSearch, you don’t even need any coding knowledge to take the maximum out of a converting site search solution.
2. Optimize product data. Semantic search relies on structured and enriched product data, so it’s essential to ensure that your product data is accurate, complete, and up-to-date. Of course, you can always fix this on the go.
3. Test and refine. Implementing semantic search is an iterative process, and it’s important to continuously test and refine your search algorithms to ensure they deliver the most accurate and relevant results for your customers. Usually, the ecommerce search partner’s team does this task with (or for) you.
4. Monitor and measure success. Implementing a converting site search is only half of the success. Get used to tracking the search metrics like conversion rates, search trends and engagement, and zero-results pages.
Successful ecommerce implementation, followed by continuous data analysis and updates, destines any ecommerce business to success.
If a semantic search will become a future, be one of the first ecommerce players to empower it and gain a competitive advantage. You now have the know-how.