Will chatbots replace search engines?

Advances in chatbot technology could bring huge changes when it comes to finding answers. But we are creatures of habit – we still use search engines, such as Google, Bing, DuckDuckGo, etc. to answer our immediate questions.

Whether you’re looking to spell a difficult word or find an easy way to fix a zipper, search engines have been consumers’ go-to source for years. However, the way we search online has evolved significantly since the deployment of search engines in the 1990s.

More than 30 years ago, the Internet was still relatively new, which also meant that search engines were also in their infancy. If you typed in a specific question, chances are few, if any, results will show up. Fast forward to the present day and search engines are capable of handling hundreds of thousands of queries.

Due to the popularity of search engines, content providers have gone to great lengths to tailor their content to what consumers are looking for, increasing the chances that you will return to their websites. This ensures that search engines have the answers to almost all of your questions, as content providers have made your search experience seamless.

Although search engines and chatbots are not a direct apples-to-apples comparison, there are overlapping similarities in their two capabilities. Additionally, advances in artificial intelligence (AI) and natural language processing (NLP) have allowed chatbots to become more human-like and function more like a search engine. Which begs the question: could chatbots one day replace the need for search engines and mobile apps?

The rise of chatbots

Despite the vast differences in business size and structure, the need to respond to customers with accuracy, speed and consistency is common across all industries. While you probably have an FAQ page with frequently asked questions or a phone number that customers can call for help, chatbots likely play an important role in your communication stack.

The benefits of AI-enabled chatbots are clear: they are available 24/7, offer more personal direct interaction, and can save time for organizations and end users. In 2024, it is estimated that consumer retail spending via chatbots worldwide would reach $142 billion, up from $2.8 billion in 2019. As chatbots continue to prove their worth, a challenge they continue to make face is the ability to understand the intricacies of human language.

A misspelled or misused word can have a huge impact on a conversation with a chatbot and can cause a customer to leave the conversation altogether if their question is not answered accurately. However, if chatbots can authentically understand human language, customer communications would completely transform.

Understand human language

Search engines have taken steps to understand human language by establishing a process to better understand words in the context of search queries. For instance, in 2018, Google launched the BERT (Bidirectional Encoder Representations from Transformers) model. After recycling an architecture typically used for machine translation, Google allowed the model to learn the meaning of a word relative to its context in a sentence, giving it the ability to perform a wide range of linguistic tasks. Last year, Google doubled down on past claims that “the future of search is conversational” and unveiled its LaMDA Conversational Technology, a chatbot designed to converse on any topic.

Recent language models such as BERT and Lamda demonstrate the value of NLP and machine learning (ML). ML algorithms have proven essential, especially in AI applications in customer services. They have the ability to process information and automate conversations, increasing the ability of businesses to have conversations with their customers anytime, anywhere.

But, despite overwhelming consumer interest in initiating and responding to two-way conversations with brands, most companies are not equipped for such messaging capabilities, which makes customers unhappy. While these algorithms will play an important role in the customer journey, it will be critical for organizations to gain a deeper understanding of human language as they seek to improve customer interactions.

Chatbots versus search engines

Interactions with chatbots are increasing with 76% of shoppers having interacted with a chatbot in 2021, up from 51% in 2020. Of these, more than half appreciate the immediate availability of an automated response. Chatbots equipped with NLP can help better understand customer requests and respond accordingly. Using NLP technology, chatbots are able to learn from previous interactions with customers and handle large volumes of conversations efficiently, while reducing human error.

In contrast, the majority of search engines only work with specific keywords, rather than a true understanding of what a user is looking for. However, smart search applications enabled by NLP allow users to ask any question, and the engine will be directed to a knowledge base where it can find the answer you are looking for.

The value of smart search apps

Sometimes the best experience for customers is a single place to ask a question and easily retrieve the content you want, rather than looking through a deep and complex navigation menu. That’s why a smart search engine with answering questions can be the best choice for your business.

While smart search apps allow you to have a search box on your website to search your FAQs, they can also search any document or website. Using ML algorithms, these applications can also be easily integrated with your existing technology, such as a chatbot. For example, smart search can handle questions your chatbot doesn’t know about and create a better bot experience for your customers. This way you can make your chatbot smarter and avoid having multiple sources of truth. Some smart search apps can even suggest answers, route messages, and help first- and second-line agents by searching your knowledge database. By reducing the number of common questions in the call center, agents can focus on solving more complex issues.

You might be wondering if smart search apps always get the right answer. The answer is no. A smart search application works like a search engine: it returns search results and ranks them as best it can. However, just like with other search engines, you may not find exactly what you are looking for.

Look forward

Although there continue to be breakthroughs in NLP, more work needs to be done for this technology to reach its full potential. Many of these systems still lack common sense, which can lead to inaccurate conversations and general customer frustration. However, given the evolution of chatbot technology, I suspect that it will eventually overtake search engines.

There will never be a powerful chatbot that can do it all at once, but investing in a smart search app can improve your chatbot’s overall functionality. The combination of these two technologies allows your chatbot to function more similar to a search engine and can make a huge difference in the way you communicate with your customers. As more brands focus on two-way conversations, it’s more important than ever to make sure you’re answering customer questions accurately and efficiently.

Using chatbots in this way may or may not have crossed your mind, until now. With new advancements in AI and NLP, these deserve special attention as they can help streamline your business and increase overall customer satisfaction. Customers want more human interactions, and the best way to provide that experience is to equip chatbots with intelligent search. The technology already exists, now companies just need to prioritize it.

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Rosemary S. Bishop