Semantic Search: AI Game Changer in E-Commerce
October 30, 2024 / Manuel Blümel
Staying ahead of the game requires cutting-edge technology. Semantic search is such an innovation. But what exactly is semantic search and why is it so important for the future?
A semantic search goes beyond the traditional matching of keywords. Unlike traditional search engines that focus solely on the presence of specific words, semantic search understands the context and meaning behind a query. It analyzes the relationships between words, captures the nuances of human language and the intent of the search.
Let's imagine we're in a library looking for a book about marine life. A librarian would understand that we want to learn more about marine life, so the behavior of dolphins and coral reefs for example. Therefore, we would get books that revolve around ocean biology and marine ecosystems, not all titles with the word “life” and “marine”. The semantic search understands the context behind the query and delivers more comprehensive and relevant information.
Combination is Key
A search engine with semantic search functionalities can interpret what is actually meant and deliver more relevant and precise results. This is made possible by combining several key technologies:
Natural Language Processing (NLP) is used to capture the meaning and context of texts. Texts are broken down into smaller units (tokenization) and specific elements such as names, organizations and locations are identified. Transformer models, such as BERT, then transform these terms into vectors.
In a semantic search, a classification algorithm, also referred to as k-nearest-neighbor, determines the distance between the searched terms, based on the previously assigned vectors, and other terms whose vectors are closest to the search terms. If the transformer model is functioning well, these nearly placed vectors represent the most semantically relevant results for the search. For more advanced semantic searches, knowledge graphs are also utilized. They store information about entities and their relationships in order to refine the process even further.
☝️ Simply explained
NLP helps computers to understand and process human language in order to extract meaningful information.
Knowledge graphs store information about entities and their relationships so that machines can recognize correlations.
The context of a search query is taken into account to provide more accurate and relevant results, such as search location or previous queries.
This technique transforms words into numbers to enable machines to recognize their meaning and similarity.
Why does this matter?
An example: A customer searches for “best trek running shoes” in an online store. Instead of showing all the running shoes that the store has available, they receive results that are adapted to the context of the specific search query, i.e. only shoes that are suitable for outdoor use are displayed. Semantic search makes this possible by taking into account the meaning behind the words, not just the words themselves. This approach ensures that users receive information that is truly tailored to their query. This not only improves the search experience, but also increases the conversion rate.
The integration of semantic search in an online store has several advantages:
Benefit #1: Improved user experience
More than anything else, semantic search improves the user experience. More precise and contextual search results reduce frustration and save time. Users find what they need faster, leading to higher satisfaction and engagement. Seamless interaction promotes a more intuitive and enjoyable digital journey, encouraging users to return and continue searching.
Benefit #2: Boosting business performance
For businesses, semantic search is also a powerful tool. It helps to connect customers with the right products or services, increasing conversion rates.
By understanding the intent behind the question, the search provides more relevant results in the company's online store, which increases sales and promotes customer loyalty. If customers find what they are looking for faster, they will not only become new customers, they will also return to the online store in the future again.
Benefit #3: Promoting innovation
Semantic search also drives innovation forward. It enables the development of smarter applications and platforms that can better understand what users want. It is a prime example of how companies can use artificial intelligence to create better digital environments. In the future, this will also mean that AI can respond even better to user behavior, for example, to offer recommendations and insights.
Integrating semantic search into the digital strategy is essential. It not only improves user satisfaction, but also boosts company performance.
In a nutshell:
What is semantic search and what are its benefits?
Semantic search understands the context and meaning behind search queries, not just the exact words.
It provides results that better match the searcher's intent by considering synonyms and related concepts.
Search queries can be made in natural language, making the search more intuitive and user-friendly.
Semantic search helps to find the right information faster by making the search more intelligent and targeted.