How smart search can affect your business.
- What is smart search?
- How does smart search work?
- #one. Connection to data sources
- #2. data indexing
- #3. Smart Document Understanding
- Smart search in business
- Smart search vs. traditional search
- Benefits of smart search
- #one. Better search results
- #2. More speed and precision
- #3. Faster decision making
- #4. Advanced archiving capabilities
- #5. Less manual effort
- #6. Cross platform support
- Future scope of smart search
- learning resources
- #one. Practical AI for search
- #2. Deep learning for search
Using intelligent search, businesses can quickly find the exact information they need based on their search intent.
Almost all organizations today deal with multiple information systems where data is scattered in an unstructured format.
As a result, employees don’t get the information they need. Also, traditional searches only rely on keywords, ignoring user intent. Thus, they end up showing the wrong results.
Smart search can help in such scenarios. It uses machine learning technology to show you accurate search results.
What is smart search?
Smart search is a search technique that can understand your goal or intent using AI and ML to provide results based on your goal. It does more than traditional searches do: it matches queries directly.
Instead, smart search uses the elements of ML technology and semantic vector search to get a big picture of the user’s target. By eliminating data silos, it enables employees and customers to get the information they need quickly and easily.
Smart search makes it easy for end users to pull information from inside or outside your business. 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 smart search work?
The intelligent search workflow involves connecting with different data sources to index them. Help with the discovery process and quick search. It also has built-in algorithms powered by AI and ML that deliver accurate information to the right audience. The three main stages of smart search are:
#one. Connection to data sources
First, the solution connects with all data sources, including CRMs, document management systems, cloud-based file sharing solutions, and more. Most of the solutions on the market can crawl the accessible structured and unstructured data from 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 of the most important information.
#3. Smart Document Understanding
At this point, you will begin to extract information from these documents to better identify and classify document types, which can be legal, financial, or presentations and videos.
Smart search in business
- When someone visits your website and searches for the product of their choice, smart search allows them to quickly land on the right web page. By showing them relevant results, organizations can increase the chances of conversion and better sales.
- This approach is equally important to retain the loyalty of former customers. Smart 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 smart autocomplete and autocorrect. Therefore, users are less likely to land on an error page.
- Smart search is also useful for employees in an organization who need to access various data throughout the day from different locations. This technique helps them get the data quickly and be more productive.
- By optimizing their website’s search with Intelligent Search, businesses can access user intent and search performance analytics. This data helps them make better and more informed decisions.
Smart search vs. traditional search
To understand the difference between these two types of searches, let’s take a look at an example. For example, if you search for “Thai soup”, you might have one of the following intentions. You may want to know her recipe or be interested in restaurants near you that serve Thai soup. Also, you may be looking for online stores that sell Thai soup mix.
Since traditional search is keyword-based, the search results you get may not be clear or personalized to your intent. In the case of smart search, there is a higher chance of getting accurate search results, since it uses machine learning and other technologies that can understand natural language.
Until now, you’ve been using traditional search that couldn’t keep up with the increasing complexity of data and the need to integrate different information systems used in an organization. On the other hand, smart search solutions can connect to almost all data sources. You can also index the data to provide us with the most relevant results based on our queries.
Traditional search uses the words included in your query to find data that matches your criteria. By contrast, smart search ranks search results by trying to discover the intent behind the query.
Benefits of smart search
#one. Better search results
Intelligent search uses AI and ML that can understand natural language, solving the confusion that is often responsible for poor search results. As a result, you can generate more appropriate results for any search query.
#2. More speed and precision
Since it uses artificial intelligence technology to navigate through structured and unstructured data, you will notice a significant improvement in terms of speed and accuracy. While searching, you also need to spend less time waiting for information.
Plus, you can understand the exact nature of user queries, thanks to AI and natural language. Therefore, it can deliver better results by matching the query.
#3. Faster decision making
In the fast-paced world of business, companies need to make quick decisions from time to time. Since most decisions can only be made based on the information retrieved, a delay in getting search results will delay the process.
With intelligent search, decision makers can immediately access the required information and can therefore make quick but considered decisions whenever necessary.
#4. Advanced archiving capabilities
A crucial benefit of Smart Search is its ability to automatically archive incoming data. Using artificial intelligence technology, it examines data to determine its nature and archives data with greater precision than ever before. It goes without saying that the organized data can be retrieved much more quickly later on.
#5. Less manual effort
This technology helps administrative executives to classify and manage data. Furthermore, companies may need even less manpower to manage the data archive. Especially for companies going through the digitization process, these features are highly beneficial.
#6. Cross platform support
Smart search can search databases, documents, and financial records stored on multiple platforms. Furthermore, this technique is capable of simultaneously searching for internal and external data. So you don’t have to perform multiple searches to find a particular piece of information.
Future scope of smart search
With the improvement of AI and ML technologies, the future of smart search will be brighter. You will have a better understanding of natural human language and thus be able to determine the targets associated with search queries.
Enterprise or intelligent search will not only provide accurate results to employees, but will have an advanced understanding of what people are searching for across the organization. There will also be an increase in the use of intelligent voice search to find information.
However, modern businesses can turn to Algolia for a powerful and flexible digital experience. This search and discovery platform is scalable and secure, supporting search customized for the enterprise. You can use it to optimize SaaS application search, product discovery, site search, and digital discovery.
For more information on the topic, you can get help from the following resource:
#one. Practical AI for search
This book teaches how to apply artificial intelligence technology to make your searches more responsive. Describes AI theories and real-life use cases for implementing them in your work. Additionally, this resource discusses ways to translate concepts into code for developers.
#2. Deep learning for search
With this book, you can learn how to improve your search results using neural networks. By understanding how deep learning is connected to indexing and ranking, you can build search engines that can deliver intelligent search results based on user intent.
This resource also teaches you how to make a search engine more user friendly.
As you can understand from the discussion above, AI and ML make important contributions to intelligent search. It saves you time and helps your workforce be more productive.
There are other benefits of smart search as well, so you can expect an increase in usage in the future.
You may also be interested in learning about artificial general intelligence.