Semantic search is a new development in search techniques. We will tell you their main characteristics and in what context semantic or keyword search would be beneficial. We also provide concrete examples of organizations already implementing these best practices.

What is keyword search?

Keyword search is a search algorithm that looks for the exact words inputted. It will output results that contain the keyword. It is suited for situations where users know precisely what they are looking for. We will give examples later in this blog.

What is semantic search? 

Compared to traditional search algorithms, such as keyword search, semantic search algorithms offers additional features and more variety when searching for information. 

Here you cannot only type and search but also speak and search, which gives the user more freedom in expressing their search query. Semantic search specializes in understanding your search's contextual ad intentional meaning - the semantics -. By enabling voice search, users can simply search more naturally, solving the issue of spelling mistakes and using synonyms that would normally not lead to any results.

Additionally, semantic search is known to provide you with more topic-related results next to the specific answer to your question. Not only are you able to find the exact information you have been looking for. Also, you will be recommended additional content based on your search topic. 

Keyword search is better suited in these contexts

E-commerce

If users know exactly what they want, why bother them with other options? Imagine going to the bakery for a baguette, ordering one, and the baker not only giving you a baguette but also two croissants and a chocolate cake. This is what using semantic search in most e-commerce scenarios is like. Just don’t do that. Just because it’s new doesn’t mean it’s better.

Customer Relationship Management

You don’t want to be bothered by related names and addresses when you need to find someone's name or address. You’re looking for a specific person. It is recommended to not only search for the exact text that is inputted by the person that searches. Names can be hard to spell correctly, so a minor spelling error shouldn’t be a problem. Just look at the amount of ways to write Johnson.

Semantic search is better suited in these contexts

Knowledge management

Semantic search performs well with large amounts of data. There are many relations between data points. The algorithm excels in situations. Organizations are scattered across different databases; this is where you need a more exploratory search algorithm. 

Lots of information that’s useful for the employees of an organization is also helpful for customers of that organization. You should not let your customers find your employee handbook; other instruction manuals are fair game.

Archives and databases

Being able to find factual information in archives and databases should be key. Nowadays, data and content can be found in various formats, such as text, audio, pictures, and videos. Therefore, it becomes even more crucial to access specific content within these files. Semantic search is optimized to do so. This is because it focuses on the meaning of the query rather than matching characters as a keyword search does. Hence, it is advantageous to use synonyms instead of keywords. Another example is searching for specific content in footage libraries within audio, pictures, or video files.

Using metadata to find a more concrete answer

The WCAG and ADA guidelines state that every video on a website should have subtitles. Many software companies provide automatic translation services like Scriptix or Kapwing, meaning there’s a transcript for every video on a website. If you index these subtitles, semantic search finds the part of the video where the answer is. This should increase the discoverability of your video content. Simultaneously, you increase the accessibility of your website content. 

Concluding

In some situations, you should be using a keyword-based search algorithm. In other cases, you should implement a semantic search algorithm. Most often, a hybrid form is the way to go. The complex thing would be deciding when to use keyword search and when to use semantic search. Using the length of the users’ input seems to be one way to make that distinction. Also, people that speak would use words like how, what, when more often. This makes their queries longer and, thus, more suited for semantic search. Another option for combining keyword and semantic search is to let the keyword algorithm do the searching but let semantic search take care of recommendations.

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