The world has reached a point where it generates almost endless amounts of data every day. Online customers have access to millions of online offers and any type of information at all times. The massive amounts of data make it harder to find specific data, so artificial intelligence is needed to increase search accuracy and information quality.
That brings us to a practice called intelligent search. It’s a popular method of prioritizing data and ensuring that it makes it to the right people. Let’s look at what intelligent search is and how it’s revolutionizing online interaction.
Intelligent Search Defined
Intelligent search is a type of advanced AI-powered search aimed at understanding the individual goals of every user. Whenever a user makes a search query, the AI finds the information and returns it to the user based on their goals. That’s why intelligence search is far more accurate than standard direct query matches.
Apart from finding basic information, intelligence search combines a semantic vector search with machine learning models to recreate or predict the goals users have when they conduct a search. For example, if you search for “raspberry chocolate pie” on a baking website, the AI has to figure out if you need ingredients, instructions, or images of baked pies.
The classic search method focuses only on the keywords used, so the user gets all kinds of answers. The search definition isn’t accurate enough, and the search engine doesn’t know what the person behind the search wants. The intelligent search uses various details to provide the user with the information they want to see. This type of search tries to understand the user’s intent before displaying information.
How do Search Engines Use AI To Find Information?
AI is a technology designed to help machines mimic human behavior. AI solutions use ML models to learn on their own and make decisions without human intervention. AI’s ability to mimic humans makes it the perfect technology for many different industries and business processes. Once it understands the drive behind certain actions, the AI can help deliver better results. The same applies to AI-powered search engines. Let’s look at how search engines use AI to improve information accuracy.
1. Search Rankings
Most search engines already use AI to rank content in search results. Google’s approach uses advanced search algorithms to rank content in various categories. The algorithms follow a long list of rules to prioritize results. Details such as keyword type used in content and the overall user experience make the most difference. Google combines all of these factors and determines which pages fit the search query.
Of course, we know how Google’s search queries work, but we don’t know the logic behind these algorithms. That is considered a company secret.
2. Understanding Search Queries
All search engines are computer apps designed to allow humans to find the information they need. These engines have to understand the query to be able to provide the correct answers. They use natural language processing or NLP to understand what humans want it to do.
Moreover, search engines such as Yandex use users’ previous searches to increase the accuracy of results and personalize displayed information. Their approach resulted in a 10% increase in the click-through rate. Google uses a similar approach, but its advanced AI search engine can provide accurate results from an image search. The company is constantly developing new ways to improve how search engines work. For example, its unique language model called BERT can now understand entire sentences, not just keywords. That helps increase result accuracy and provide better results.
3. Quality Control
SEO practices are often shady and suspicious, as SEO specialists keep developing new techniques to help increase website ranking. SEO practices such as aggressive keyword stuffing, invisible text, cloaking, and many others are used to increase SERP ranking.
While that is a valid approach to increasing website ranking, it harms search engine result quality. Instead of getting high-quality results, users simply get low-quality content stuffed with keywords. That’s why the largest search engines use AI to filter out high-quality content from low-quality spam.
4. Voice and Image Search
Voice and image search are the latest search types introduced only after AI took over search engines. As mentioned above, AI uses NLP to understand humans better. NLP capabilities have increased with time, and AI can now understand human speech. They hear and understand spoken words and translate them into the text used to generate a search.
AI can also recognize images and understand what the image shows. It is then able to provide search results relevant to the image in question.
Importance of Intelligent Search
Intelligent search is an essential element for improving the overall digital experience. It’s designed to help online customers find the information they need on the internet. The sheer amount of available information complicates online searches, and intelligent search is supposed to reform the process to make finding accurate information much easier.
However, intelligent search affects other areas of running an online business. For example, it helps prioritize ticketing and helps improve service quality. It also makes it easier for customers to find the information they need without asking live agents for help.
Intelligence search has a direct impact on many other practices such as providing accurate answers to questions, filtering content to remove low-quality information, automatic re-ranking, etc.
AI-powered solutions are practically redefining entire industries by helping them increase efficiency and production. For example, the Wizata industrial manufacturing software uses advanced AI, Internet of Things sensors, and machine learning to help streamline manufacturing and business processes to reduce costs and increase revenues.
Intelligent search is the next step in online engine interaction. It’s possible only because of the massive advances in AI applications. AI-powered search engines can provide more accurate results faster by understanding the intent behind a search query.
The technology is still new, and it will undoubtedly become even more powerful in the future. Intelligent search is needed to help filter information to ensure that customers get only accurate information in their results.
Christopher is a digital marketing specialist at Digital Strategy One and a freelance blogger. He is focused on new web tech trends and digital voice distribution across different channels. In his free time Christopher plays drums and Magic: the Gathering.