A Guide to Semantic Search Engines and Why It's Crucial to Your Business: A blog about how semantic search engines are becoming more prominent.

Semantic Search engines can give more relevant results than traditional lexical search engines. While the conventional search engines can only search for keywords and find pages containing them, semantic search engines work with a more complex set of algorithms to find pages similar to keywords entered by searchers. The difference between the two types of search engines is so vast that those who stick with traditional methods risk losing their competitive edge or going out of business soon.

The quality of the semantic search engine will determine the accuracy of its analysis (not to mention how user-friendly it is). For example, if you were to enter "Software Marketing" as a keyword, a semantic search engine will analyze all content on your website and show results based on the meaning rather than on the presence of key terms in the query. It will show the articles or documents about marketing or promoting software technology. The keywords may not even be present in those documents but are meaningfully relevant to the topic.

Over the past decade, advances in understanding language semantics and ontology for a broad spectrum of QA problems, such as open-domain QA, question answering, and question mining, have been constant and considerable. Semantic search engines are massive databases of linked data and combine the traditional features with natural language processing technologies. Today, we can find such applications in all the areas of Natural Language Processing, including information retrieval, machine translation, summarization, question answering, etc.

Search has evolved from:

1) Keywords – Matching keywords to web pages that are optimized for those specific keywords, but not providing the best answer to the searcher’s query.


2) Synonyms – Matching synonyms of keywords used in the query with synonyms in web pages. This is a step in the right direction but still doesn’t completely solve the problem of providing exactly what the user is looking for.


3) Semantics – Understanding searcher intent, along with context and relationships between words in order.

Semantic Search considers context

Semantic Search considers context when processing search queries. Semantic Search engines understand the intent behind a search query and the user's context, allowing them to deliver results based on meaning rather than syntax. The end goal is to provide results that match the user's intent rather than just the keywords they entered.

Why It's Becoming More Important?

Semantic Search is becoming more prominent due to many factors. Three major factors include increased content availability, raised mobile usage, and voice search queries.

With so much content online, it has become difficult for users to find accurate information. Semantic Search engines make it easier to find accurate information because they understand the intent behind a query. If you were to type "What is the fastest car?" into a Semantic Search engine, it would give you results based on what it assumes that you're asking. For example, it would recognize the fastest car among many.

Existing keyword targeting strategies will become less effective as Semantic Search becomes more ubiquitous

Keyword-based search queries are becoming less effective as Semantic Search becomes more popular. This is a significant shift for marketers and business owners who have included specific keywords on their websites to reach their target audiences.

Semantic Search differs from keyword-based search engines in that it focuses on the meaning behind words, not just a specific sequence of them. Marketers need to create content that provides value rather than stuffing their website with keywords.

The benefits of Semantic Search are many:

  • It provides better answers than traditional keyword-based searches. In other words, it gives you a better bang for your buck by delivering accurate content that matches your query instead of irrelevant or misleading results (which can be costly to both businesses and searchers).
  • It increases user satisfaction because answers are more accurate, decreasing bounce rates and increasing conversions (or sales).
  • It provides precise results that eliminate wasted clicks and time. Saving both business owners and consumers from spending money on irrelevant results. It makes searching easier.

Semantic intent and user intent are different things.

With Semantic Search, you need to understand both the semantic and user intents of a query to provide more relevant results.

To fully understand Semantic Search, you must first understand the semantic intent and its distinction from user intent. Semantic intent is the intent derived from query text, while user intent is derived from user preferences and past searches, also known as user context. Search engines interpret semantic intent by answering the question, "what does this query mean?" They interpret user intent by answering, "what does this person want?"

On a semantic search engine, one would expect the search results to match their semantic intent most of the time. For example, if a person searches for a "red shoe" then the semantic intent of the query is to know more about red shoes. The user intent of the search query might be to buy a pair of Italian designer shoes. This can be determined by looking user’s search history on your site.

The user's intent, past searches, and preferences are essential for search engine ranking signals. The problem is that there has been no way to measure user intent and understand how it relates to the query text. Semantic Search seeks to solve this by understanding the relationship between words and meaning.

Be ready for the shift to semantic search to remain competitive.

Semantic Search using Natural Language Processing (NLP) and artificial intelligence (AI) is revolutionizing how we interact with the internet.

What if you could type a sentence into a search engine and get exactly what you were looking for? What if, instead of getting an overwhelming list of links to sift through, your results were tailored to meet your needs? This is the promise of Semantic Search — a new technology that's changing how we use the internet.

Why does this matter for your eCommerce business? Because if you want to be found by customers online, you need to start preparing your websites for Semantic Search now.

More than half of all online traffic is mobile, and over half of smartphone users use voice search at least once per week. That means people are entering Search queries like "Where can I buy [product] in [city]?" rather than typing in "[product] [city]" into their phones' browser windows. So if you want customers to find your products, you need to make sure your website is set up to be seen by Semantic Search engines like Google Voice Search and Apple Siri.

If you want to be found by potential customers, you have to get your sites ready for Semantic Search. It's no longer enough to have a website–you need to make sure it's set up for voice search.

Takeaway: Semantic search engines are here, and you need to understand how they work if you want your business to thrive online.

In the end, a semantic search engine still only returns search results that adhere to its algorithm. If a user needs a specific answer, they should still find it. However, they now have help if they cannot communicate their intent correctly. As search engines continue to adapt—along with user behaviors and demands—semantic search engines will become more prevalent and offer new benefits for those who use them.

Semantic Search will likely continue to increase in popularity and usage, but at the same time it should become easier for marketers and webmasters to use as well. Whether you're a seasoned SEO or just beginning to explore the field, you must understand the importance of these engines and what they can do. Hopefully, this blog has helped introduce semantic search engines and give you a good idea of what they have to offer.