Assisted Search: The Natural Evolution of Search

Assisted Search: The Natural Evolution of Search

In today's digital age, enterprises are faced with the challenge of providing an efficient and effective means for their customers and employees to search for relevant information within an ever growing set of content on their website or internal knowledge systems. In customer-facing industries like telecommunications, customers expect quick and accurate answers to their questions about their plan or service. Similarly, large enterprises often have vast internal knowledge bases that can be difficult to navigate, making it challenging for employees to find the information they need. In this article, we will explore the 4 levels of search, which offer advanced and accurate ways to quickly and easily find the right information.

Level 1: Keyword Search

This is the most basic level of search and what we're all familiar with. It involves typing in a few keywords into a search engine and hoping that the results will be relevant to our query. While this level is still effective for simple queries, it falls short when we're looking for more complex information or have trouble coming up with the right keywords. If, for example, we're looking for information about the best restaurants in Auckland, we might type in ‘best restaurants in Auckland’ and hope for the best.

Level 2: Semantic Search

Semantic search takes keyword search up a level by considering the meaning behind the keywords, rather than just the keywords themselves. This means that we don't need to use the exact keywords to find what we're looking for. Instead, we can use synonyms and related words and still get relevant results. If we're looking for information about the best eateries in Auckland, we might type in ‘top dining spots in Auckland’ and still get relevant results.

Level 3: Contextual Search

Contextual search goes beyond just matching the meaning of the keywords to also take into account the specific user and their intent behind the search. This means that the search engine can provide more accurate and personalized results based on the user's context - such as if we're searching for information about a particular car model, the search engine might take into account our location, our past search history, and other contextual factors to provide us with more relevant results.

Level 4: Generative Search

Generative search takes search to the next level by not just returning relevant results but also generating an answer based on those results. This means that the search engine can directly answer the user's query, rather than just providing a list of potential results. For example, if we're searching for the recipe for a particular dish, the search engine might generate a summary of the recipe, including the ingredients and steps needed to make it.

At ElementX, we believe that search should be more than just a simple keyword search: that's why we offer a better search solution for enterprises that leverages the power of semantic, contextual, and generative search to better serve information to their staff and customers. By understanding the user's intent and context, we can provide more accurate and personalised results, making it easier for users to find what they're looking for. Contact us to learn more about how we can help improve your enterprise search solution.

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