Do you recall the days when searching required some level of proficiency? Browsing search engines to find desired results wasn't always straightforward. It often required a creative approach to keyword selection to guide you toward the information you sought. 

Today, however, being “good at searching” is a thing of the past. The burden of 'searching smartly' has largely been transferred from the user to the search engines themselves. Modern search engines are equipped with the latest technology designed to recognize keywords and understand the most likely reason why you choose a specific set of words. They aim to provide results that align with what you intended to find. So, in a way, this industry went full circle because, at first, we had to understand how search engines work, and now search engines have to understand how we work.

‍

What is Conversational Search?

As the name itself implies, conversational search aims to replicate the experience of human conversation.

In the past, inputting keywords was like dropping coins into a vending machine and hoping the right item would fall out. Now, instead of finding your way through a deluge of loosely related information, conversational search allows us to interact with technology in a more intuitive and human way. 

For example, if someone says, "It's chilly in here," in a keyword search, you might get results about cold weather. However, in human interaction, the listener understands this as a subtle request to close a window or turn up the heat. Conversational search engines have the ability to detect this implied meaning.

This means that search engines identify the intent and implied meaning behind our search query, which enables them to discern whether we want to get informed, acquire a service, buy a product, or get entertained.

With that in mind, let's take a look at five core principles of conversational search that make such problems a thing of the past:

5 Core Principles of Conversational Search

For example, searches like “tomato soup recipe” and “tomato soup nutrition” might have similar keywords but distinct intents; one is recipe inquiry, and the other seeks dietary information. Conversational search deals with this by applying the same principles you would expect to find in a person who is a “good listener.” Let's explore those qualities:

1. Contextual understanding:  If you frequently search for nutritional information about foods, the search engine learns this pattern. So, when you next search for just "tomato soup," it might prioritize showing nutritional content by understanding your usual interests.

2. Conversational comprehension With the advent of NLP (Natural Language Processing), search engines got the ability to process natural human language in all of its nuances. This technology allows the search engine to comprehend queries like "Is tomato soup high in calories?" as naturally as if you were asking a nutritionist. It interprets the query not just as a string of keywords but with an understanding of the implied question about health and diet.

3. Responsive interaction: Similar to how a thoughtful conversationalist adapts the dialogue as it progresses, the search engine responds to a query like "tomato soup recipe low sodium" with relevant follow-up suggestions, making the search feel more like an interactive dialogue.

4. Personalization:  Based on your search history, if you often look up low-sodium or heart-healthy recipes, the engine might start highlighting these options automatically in future searches. This personalization makes the search experience more relevant and efficient for your specific needs.

5. Clarification requests:  In cases of ambiguity, say you type in "tomato soup diet," the search engine might ask for clarification to discern whether you are looking for recipes suitable for a diet or nutritional information about tomato soup in diet plans.

In essence, a conversational search engine envelops all the important qualities of a good listener to provide relevant and helpful answers, even to complex queries. The goal is to achieve maximum efficiency because you don’t have to dig for information.

As the famous business consultant Peter Drucker once said: “The most important thing in communication is to hear what isn't being said.” Search engines with conversational capability are doing exactly that to ensure that the search experience yields maximum results.

Why is Conversational Search Becoming Necessary?

Predictions are that by the end of 2024, more than 59 zettabytes (ZB) of data will be created, captured, copied, and consumed globally. One zettabyte is a trillion gigabytes. Let that information sink in.

Picture it this way: if we were to store the entire digital data of the world in one place - a staggering 59 zettabytes - on standard 1TB 2.5-inch SSDs (that’s the small card in your PC), we would need a space equivalent to about 1,156 Olympic-sized swimming pools? That's 2,891,000 cubic meters of SSDs!

What is even crazier is that forecasts suggest that the amount of data generated in the next three years will exceed the volume of data produced in the past 30 years.

As we grapple with these mind-boggling numbers, it becomes clear why the keyword-centric approach to searching is no longer sufficient in our chaotic world. Imagine trying to sift through 59 zettabytes of data using just a handful of keywords. It would be like trying to find a needle in a haystack, except the haystack is as big as 1,156 Olympic-sized swimming pools.

This overwhelming abundance of information, coupled with the modern tactics of digital marketing, where keywords have been frequently overused to drive traffic, sometimes at the expense of content relevance, has called for a shift in how we find what we're looking for. 

With this in mind, the transition to conversational search seems not just like some fancy technological leap but an essential step towards more efficient data retrieval.

Everything is reliant on information. From organizing your personal life to running huge corporations, the one major predictor of success in any of your endeavors is the quality of information at your hand. Conversational search is about making the search process more human-centered to ensure that the right information reaches the right person at the right time amidst billions of data points. 

How Can Akooda Help?

Akooda integrates all the  SaaS tools that a company is already using and all of the company-wide data to create a unified operational view of what’s going on in the organization

Our platform is designed to improve decision-making and operational visibility by allowing employees to access and analyze company-wide data in an intuitive, conversational manner.

Just imagine all of your company data structured in a way that makes sense and all of it easily available, just one simple question away. Akooda exemplifies the fusion of advanced AI with NLP and a user-friendly interface to drastically improve your business workflow and make data interaction more accessible and actionable for employees.

If you want to see more about how Akooda can help your business follow the growth of information, check out our product page.