Businesses, irrespective of their size and domain, require access to information in order to make informed business decisions and develop successful strategies. This information is often derived from data, so we might think that more data leads to more information, so more is better. However, it is possible to have too much of a good thing. Data is only valuable if you can use it, and without proper structuring and management tools, companies can find themselves drowning in data.
At the onset of the “digital age,” enterprises struggled to weed through bottomless pits of data, searching for information in unstructured environments. Employees would spend hours of valuable time that could have been used on more meaningful and productive tasks. Initially, search results were determined solely by the presence and frequency of specific keywords. Search functions have, of course, improved and changed in many ways since those early days. One of the most important shifts came with the introduction of natural language processing and machine learning capabilities, which today power cognitive search tools.
So what is Cognitive Search?
When it comes to data and information, accuracy and relevance make all the difference. Even with the right keywords and key phrases, you can spend hours looking through and collecting information, and still not find what you’re looking for. With so much data on hand - and more being added by the minute - it isn't easy to extract what’s relevant.
Cognitive search is driven by artificial intelligence (AI) and aims to deliver contextual information that is highly relevant to a user’s search request. Relevancy determinations are achieved by inferring a user's intent and finding patterns and relationships within the data.
How does Cognitive Search work?
Natural language processing (NLP) and machine learning are used to mine, extract, and summarize data from different sources, irrespective of the formats.
NLP has some restrictions, as it focuses solely on linguistics, whereas cognitive search follows a language-independent, statistical approach to understanding human information that is fine-tuned by the use of linguistics. Simply put, cognitive search is aligned with users more naturally, providing a 360-degree view of the user journey and their past interactions to personalize the experience.
Here are some benefits of cognitive search and how it can be an asset:
Penetrate extensive data sources
We’ve all heard that data is a valuable commodity in today’s world, but even the best information is no good if you can’t get to it. Cognitive search has enabled businesses to extract information buried within voluminous sources quickly, and more accurately, effectively unlocking the potential value of large, previously daunting datasets.
Improve user experience and engagement
Cognitive search doesn’t just make it easier for employees to find valuable information and make smarter choices. A customer-facing cognitive search function can create a more effective, streamlined, and satisfying user experience. One of the biggest turn-offs for potential customers is a website that is confusing or difficult to navigate. Including a search function that accurately directs them to content, based on their intent rather than just the keywords they used, can make a huge difference - especially in jargon-heavy industries.
Access relevant and accurate information
Natural language processing doesn’t just help cognitive search tools better understand the intent of the search query - it also helps the system gauge the relevance of text content like email, blog, report, research work, and document, as well as media content like meeting videos and audio recordings. This helps it do more in-depth research and come up with relevant information.
Enhanced search results
Machine learning algorithms help in providing better search results. It touches searches through structured and unstructured data and lends profound, meaningful, insightful search results.
Users’ previous histories and usage patterns can be factored into each new query, better learning their preferences and interests to recommend content that is more likely to be relevant.
Learn more about what cognitive search can do for your business.