Using intelligent search, companies can quickly find the exact information they need according to their search intent.
Almost all organizations today deal with multiple information systems where data are scattered in an unstructured format.
As a result, employees fail to get the information they need. Also, traditional searches only depend on the keywords, ignoring the user intent. Hence, they end up showing the wrong results.
Intelligent search can help in such scenarios. It uses Machine Learning technology to show you accurate search results.
What Is Intelligent Search?
Intelligent search is a search technique that can understand your goal or intent using AI and ML to provide results based on your objective. It does more than what the traditional searches do — directly matching the queries.
Instead, intelligent search uses the elements of ML technology and semantic vector search to get an overall picture of the user objective. Removing data silos, it allows employees and customers to get the necessary information quickly and easily.
Intelligent search facilitates information extraction from inside or outside your company to the end-users. It supports data sets of various formats, including big data, digital content, document management systems, and web pages. This search is also known as AI search, enterprise search, cognitive search, and natural language search.
How Does Intelligent Search Work?
The working process of intelligent search involves connecting with different data sources to index them. It helps with the process of discovery and quick search. It also has built-in algorithms powered by AI and ML that provide accurate information to the right audience. The three main stages of intelligent search are:
#1. Connection to Data Sources
First of all, the solution connects with all data sources, including CRMs, document management systems, cloud-based file-sharing solutions, and more. Most market solutions can crawl through the structured and unstructured accessible data of the mentioned data repositories.
#2. Data Indexing
Once the data is available, the application creates a unified search index for the search results regardless of the original source. This technology supports indexing the most important information.
#3. Understanding of Intelligent Document
At this point, it will begin extracting information from these documents to identify better and classify the sorts of documents, which may be legal, financial, or presentations and videos.
Intelligent Search in Business
When someone comes to your website and searches for the product of their choice, intelligent search allows them to reach the accurate webpage quickly. By showing them the relevant results, organizations can increase the chance of conversion and better sales.
This approach is equally important for retaining the loyalty of old customers. Intelligent search can provide them with personalized search results based on their history.
The success of your business depends on the user experience of your website. Machine Learning and AI offer features like intelligent autocomplete and autocorrect. Thus, users have less chance of landing on an error page.
Intelligent search is also useful for the employees of an organization who needs to access various data throughout the day from different places. This technique helps them get the data quickly and become more productive.
By optimizing your website search with intelligent search, companies can access search performance analytics and user intent. This data helps them make better and more informed decisions.
Intelligent Search vs. Traditional Search
To understand the difference between these two types of searches, let’s have a look at an example. For example, if you search for “Thai soup,” you might have any of the following intent. You might want to know its recipe or be interested in restaurants near you serving Thai soup. Moreover, you might be looking for online shops that sell Thai soup mix.
Since the traditional search is based on keywords, the search results you get may not be clear or personalized according to your intent. In the case of intelligent search, there is a higher chance of precise search results as it uses machine learning and other technologies that can understand natural language.
Till now, you have been using a traditional search that could not keep pace with the growing data complexity and the need for integrating different information systems used in an organization. On the other hand, intelligent search solutions can connect to almost all data sources. It can also index the data to provide us with the most relevant results according to our queries.
The traditional search uses the words included in your query to find data that matches the criteria. Contrarily, intelligent search ranks the search results by trying to find out your intent behind the query.
Benefits of Intelligent Search
#1. Better Search Results
The intelligent search uses AI and ML that can understand natural language, which resolves the confusion usually responsible for poor search results. As a result, it can generate more appropriate results for any search queries.
#2. More Speed and Accuracy
Since it uses AI technology to browse through both structured and unstructured data, you will notice a significant improvement in terms of speed and accuracy. While performing a search, you also need to spend less time waiting for information.
Furthermore, it can understand the exact nature of user queries, thanks to AI and natural language. Thus, it can offer better results matching the query.
#3. Faster Decision-Making
In the fast-moving business world, companies need to make quick decisions every once in a while. Since most decisions can only be made based on the retrieved information, a delay in getting search results will defer the process.
With intelligent search, decision-makers can immediately access the required information, and hence, they can make speedy yet considered decisions whenever necessary.
#4. Advanced Archiving Capabilities
A crucial benefit of intelligent search is its ability to automatically archive incoming data. Using AI technology, it scrutinizes data to ascertain its nature and archive data more precisely than ever before. Needless to say, the organized data can be retrieved much more quickly later.
#5. Less Manual Effort
This technology helps admin executives in sorting and managing data. Also, companies might even need less manpower to manage the data archive. Especially for companies going through the digitization process, these features are highly beneficial.
#6. Support for Multi-Platform
Intelligent search can search through databases, documents, and financial records stored on multiple platforms. Moreover, this technique is capable of simultaneously searching internal and external data. Therefore, you do not have to perform multiple searches to find a particular piece of information.
Future Scope of Intelligent Search
With the improvement of AI and ML technologies, the future of intelligent search will be brighter. It will have a better understanding of natural human language and thus be able to determine the goals associated with search queries.
Enterprise or intelligent search will not only provide accurate results to the employees, but it will have an advanced grasp of what people search for across the organization. There will also be an increase in the use of voice intelligent search to find information.
However, modern businesses can opt for Algolia for a powerful and flexible digital experience. This search and discovery platform is scalable and secure that supports personalized search for the enterprise. You can utilize it to optimize SaaS application search, product discovery, site search, and digital discovery.
To learn more about the topic, you can take help from the following resource:
This book teaches how to apply AI technology to make your searches more responsive. It describes the AI theories and real-life use cases for implementing those in your work. Moreover, this resource discusses ways to transform the concepts into codes for the developers.
From this book, you can learn to make your search results better using neural networks. As you can understand how deep learning is connected with indexing and ranking, you can build search engines that can deliver intelligent search results according to the user intent.
This resource also teaches you how to make a search engine that will go better with the use.
As you can understand from the above discussion, AI and ML make major contributions to intelligent search. It saves your time and helps your workforce become more productive.
There are other benefits of intelligent search as well, so you can expect a surge in its usage in the future.