“I can’t find it.” 

Sadly, this conclusion is often still part of the modern enterprise search experience.

But it shouldn’t be. Consumers and employees require fast search experiences powered by first-rate technology that anticipates search queries and generates relevant results. Whether someone’s looking for products or extracting back-end data, search must be efficient and smart.

This is where the cognitive search skillset makes a grand entrance.  

Cognitive search capabilities help organizations deliver hassle-free user experiences and let employees work more efficiently with overwhelming datasets. Whether it’s a customer who can’t locate support information or an employee drowning in irrelevant data, cognitive search dons the red cape of knowledge discovery and comes to rescue. 

What is cognitive search? 

“Cognitive search” sounds as though the search engine is looking for information stored in its search index based on its cognitive skills — its thoughts. And to a certain degree, while it can’t technically “think” as a human would, it’s doing something brainy: knowing what a consumer wants thanks to artificial intelligence.

Forrester describes cognitive search as “a new generation of enterprise search solutions that employ AI technologies such as natural language processing and machine learning to ingest, understand, organize, and query digital content from multiple data sources.” 

How does cognitive search work? It uses natural language processing (NLP) and machine learning to make sense of and process product specifications, descriptions, and images in a database. Then, with this AI enrichment, it creates unique personalized search experiences for individuals who need the information. This improves search relevance for them, as well as, conceivably, generates higher revenue for their organizations. 

Cognitive search vs. traditional keyword search 

It’s not the fight of the century, but it’s a battle that matters. Picture cognitive search as being in one corner of the ring with its custom skills, facing off with the reigning champ, traditional search, in the other.

For decades, traditional keyword-based search has been the norm. But search results generated from only keywords were too broad. Consumers and employees alike had to search — and then continue refining their searches — to get to relevant information. This amounted to a major, annoying waste of time. Greater search relevance and personalization were sorely needed. 

Cognitive search work builds on the foundations of traditional search, but it brings to the search experience some key advantages.

Superior relevance levels

The big difference is better, more relevant search results. Unlike keyword search, cognitive search crawls unstructured data and structured data, recognizes patterns and meaning, and generates high-quality search results from all the sources. This ensures that whatever type of search your users or employees initiate, they’re presented with results appropriate to their query. 

Let’s say you have a prospective customer browsing your ecommerce site and then searching for the key phrase “winter coat”. They know exactly what they’re looking for. They can picture it. They can see themselves in it. Now they want to get their hands on it.

But first they need to find it.

A keyword search for a winter coat would typically lead to an array of results that are too general or don’t quite hit the mark for the shopper. The customer would likely have to refine their query to cut through all the noise and zero in on what exactly they want.

Enhanced language understanding

Aided by enhanced language understanding, cognitive search goes one step further. In embarking on this search, it might already “know” about fabric types for coats, popular colors, gender, and other relevant details. In short, a cognitive search is like a knowledge management librarian who points you to just the right search results, eliminating your need to keep poking around in the stacks. 

Comprehensive results

Employees might be needing to pull data and information about a product — perhaps stock numbers or sales figures, for instance — to compile a report. With traditional search, the results would likely be sporadic and lead to additional attempts to extract only what’s needed. With cognitive search, all the pertinent data would be expediently compiled from an array of sources, letting them move on and start the report instead of, say, pulling their hair out. 

Cumulative learning 

With your work teams, you want to see growth and notable productivity increases over time. Search engines should progressively get more effective, too. It’s not going to happen with keyword search, but look out if you’re implementing cognitive search. You’ll find that this search method keeps learning and improving as it processes and notes what’s in user queries. Cognitive search is like being a professor with a student who knows nothing about a subject going in but faithfully attends all the lectures, pays close attention, and applies every little detail learned, at the end of the semester delivering an A+ paper that blows you away.  

Let’s look at the cognitive-search “student” in action. A consumer does a search for “LG TV 55 inch” and then immediately does another for “Amazon Fire Stick”. The search engine’s machine-learning functionality sits up and takes notice. It gets that the two searches could be related. It thinks about that for a bit, and then, on the second search, goes a step further, presenting results that incorporate information from the first search.

But it doesn’t stop there. Filing away these queries for future reference, it continues getting “smarter” over time and begins to anticipate and connect other queries.

Business benefits of cognitive search  

The improved relevance and efficiency, and the time savings as a result, lead to enterprise benefits such as a higher conversion rate, a more loyal customer base, a more productive sales force, and higher revenue. 

Cognitive search goes deeper, bringing greater efficiency to the workplace or enhancements to how clients engage with the brand.

Supercharged productivity  

Did you know that according to McKinsey, employees spend roughly 19% of their work day searching for information? Imagine how all that wasted time could be better spent. Delays in getting the right data can slow the time to market and decrease efficiency. 

Let’s say an employee is in need of various client contracts. If this were occurring a few years ago, they’d probably be trawling through numerous enterprise file systems — documents stored in various databases — relying on keyword search that generates mediocre results and necessitates more sleuthing. Now, with cognitive search, rather than trawling through reams of data, they can instantly pull up contracts by entering the client name and company in the search box. And instead of spitting out random results based on keywords, the cognitive functionality easily retrieves not only the needed contracts but related email and other items.

Satisfying user experiences  

It may be frustrating to businesses, but it’s true: enterprise users and customers expect search on websites and in apps to work as efficiently as Google does. They want answers to their queries in a heartbeat, not at a snail’s pace by entering successive queries. And with 88% of online customers saying they won’t return to a website where they’ve had an unpleasant experience, companies’ producing seamless user experiences is vital. 

Cognitive search gets closer to meeting enterprise users’ expectations. It “thoughtfully” anticipates their needs, connects them to what they’re looking for, and deepens search personalization. 

A support use case

Picture a customer that needs support for a purchased product. They’re using the self-help portal on the company’s ecommerce site, which is powered by cognitive functionality. The portal is full of answers to questions, and exploring and finding the needed support could take a while.

However, it could take less time than expected because cognitive search focuses on providing personalized search experiences. So if the customer searches the portal for “warranty policy on Smart TV”, and they’ve also previously searched for an answer to a technology-related question, they could quickly get more-accurate, personally oriented results that factor in both the problem and their interest in warranty details. 

Unlocked data   

There’s a secret at the heart of every company’s enterprise data. According to MIT, 80–90% of data is unstructured: in a format that’s not easily searchable, for example, text and social media posts. Digging through this slush pile is typically no easy task.  

But cognitive search technology can make sense of data using indexing, text analytics, and AI technologies. Let’s say your marketing team wants to identify consumer search patterns for last quarter. Gathering the data through traditional search methods would be a fairly epic project. By contrast, a cognitive-search service would speed up the process, culling your organization’s multiple information sources, pulling relevant data from unstructured forms, and determining the highest-priority items to display.

An enterprise game changer

Enterprise search applications are a key business tool. Utilizing them needs to be an easy experience for everyone, whether they’re an employee or a customer. 

Cognitive search delivers that value, making search easier both inside and outside the office.

Want to generate higher revenue with a state-of-the-art cognitive search solution? Our search API is scalable, reliable, and secure. We offer tiered pricing, too.

Let’s put the power of cognitive search to work for your company’s bottom line. Contact our team today.