How Intelligent Search Improves the Search Experience

Today, we have more data available to us than ever before. Yet half of people are confused about where to find information at work, affecting their overall search experience.
Uncovering insights and making meaningful decisions are key to any business’s success. But that’s difficult to do when it takes too long to find what we’re looking for. The simple fact is that we spend a great deal of effort trying to find the information we need. Poor search experiences take valuable time and energy away from doing meaningful work.
On the surface, simple search technologies may seem to make it easy to find answers. But too often, search experiences end up being far from relevant. As a result, critical information is missed, and poor decisions are made.
What matters most is finding the exact information we need. That means getting search results that are relevant to our query. As companies amass more and more data, that outcome becomes increasingly difficult to achieve.
That’s where intelligent search comes in. It uses advanced search capabilities – such as natural language processing (NLP) and deep learning – to deliver better results. The result is a next-level improvement in search accuracy and search relevance.
Today, using basic search capabilities just won’t cut it. Users need a quick, simple, and effortless way to find the exact answers to their questions. The solution is intelligent search.

Why relevant search results matter

Irrelevant search results are more than a frustration. They also cause a significant drag on efficiency. Users are forced to spend more time trying to find the results they want. That makes the search experience less fruitful and less useful.

If the process becomes too frustrating and time-consuming, some users will give up. If those users are employees, it has a negative effect on productivity and on your businesses bottom line. If they are customers, they may go to a competitor. Many will never return.

In other words, irrelevant search results cause a direct hit to the bottom line. A poor search experience leads to lower productivity, missed opportunities, and lost revenue.

Accurate and relevant search results are crucial for business. To get those results, companies need to embrace intelligent search.

How intelligent search improves search accuracy and relevance

Intelligent search uses a combination of advanced technology to better understand all of your company information and the intent behind each search. For example, intelligent search algorithms use advanced NLP. This technology focuses on the interaction between computers and humans. Advanced search engines can better understand information and intent to power relevance using NLP. Knowing that, it produces more accurate and relevant search results.

Intelligence search also uses machine learning. ML uses algorithms to identify patterns in data. Then it learns from these patterns to improve future search performance. This continuous analysis and learning keep improving search results over time.

Some intelligent search algorithms use techniques such as semantic search and query expansion. NLP understands the context and meaning of individual words and phrases. This gives the algorithm a greater understanding than matching simple keywords. In turn, this helps the algorithm deliver results that are much more relevant.

With query expansion, the search engine identifies terms and synonyms related to a query. Then it adds these terms to the query. This increases the chances of finding relevant search results. For example, a search for “marketing strategies” might also return results for “digital marketing tactics” or “marketing plans.”

Often, intelligent search technology also uses an improved search interface. This incorporates advanced features that help the user narrow down the results. Auto-complete is a good example. It might also use features such as query suggestions and advanced search options. This makes it easier for users to refine their searches and improve the results.

Using these advanced techniques, intelligent search technology improves the accuracy of search results. It delivers more relevant answers. This way, users can find the information they need quickly and with less effort.

5 business benefits of intelligent search

1. Improved cost savings

A poor search experience hampers knowledge workers. They often spend more time trying to find information than actually utilizing it. That adds up to a great deal of time and resources spent searching. Intelligent search cuts down on that waste, creating cost savings for companies.

2. Increased efficiency and productivity

An intelligent search interface is more usable and easier to navigate. It often includes helpful features such as auto-complete and query suggestions. It can also offer advanced search options. This helps users find the information they need faster, which saves time and increases productivity.

3. Smarter decisions

People tend to make decisions based on opinions or hunches when information is difficult to find. But intelligent search makes it faster and more efficient to get up-to-date information. Using intelligent search, companies can make smarter decisions based on real-time data.

4. Intelligent insights

One of the most significant benefits of intelligent search is that it helps companies discover critical insights. Advanced search algorithms are more efficient at uncovering critical data. Companies can leverage that data to gain intelligent insights. Intelligent search unlocks the potential of a company’s data to inform its strategies at every level of business.

5. Competitive advantage

The business landscape changes today faster than ever. Technologies, trends, and market conditions are constantly changing. The needs of users and customers evolve with them. Intelligent search makes it easier to meet those changing needs. Companies that leverage intelligent search can gain a competitive advantage in the marketplace.

The future of intelligent search: Chat GPT and Neural Search

The technology behind intelligent search continues to evolve. Generative LLMs like those powering ChatGPT are a perfect match for search because they extend how employees can interact, refine, and reformulate search results. Where ChatGPT excels is synthesis, summarizing complex topics into a paragraph or two of text that captures the most common (although not necessarily the most important!) points. In a search, this automates the research and collection of information. And humans are lazy. Rather than choosing a few links and reading several web pages, only to find out some are not what we want and some are repetitive, we would much rather read a summary.

Another technology driving the future of intelligent search is Neural Search. Sinequa brings the power of generative AI to the workplace by pairing two powerful technologies to work together – the unmatched relevance of Sinequa’s Neural search technology and the summarization and interactivity of generative AI. This combination is key, as it provides the only way to unleash the power of generative LLMs to the enterprise safely, powering the chat with secure enterprise content thanks to Sinequa’s extensive connectivity to all enterprise sources.