Is ChatGPT The Death Of Search?

If you work in technology, you've undoubtedly heard of, and likely even used, ChatGPT. (For the record, I did not use ChatGPT to write this blog… but I did think about it.)

My experimentation with ChatGPT started as a fun party trick. I gave prompts like "Write a Muppets script in the style of The Office" or "Would humans be able to beat the Na'vi from Avatar in a game of basketball". While I highly enjoyed chats like these, my attention quickly shifted to wondering how this technology would be used in the practical world.

Most of us who have played around with ChatGPT have tried using it to answer questions that we would normally prompt to Google. This behavior has many tech enthusiasts wondering if ChatGPT will threaten Google — and the search industry as a whole.

That's a big proposition – but is it true? I decided to run through some use cases and find out for myself.

Unsurprisingly, by running a variety of queries, I've found that chat and search each excel in different areas — and they can best be used as complements to each other.

Searches for "encyclopedia-type" knowledge (such as "what is the history of the television?") yielded much better results on ChatGPT than traditional search. ChatGPT excels at delivering thorough, readable, article-style answers to these types of queries.

However, when searching for actionable, intent-focused searches (such as "where can I buy a new television?"), the outcome was the opposite — and traditional search performed much better. That's because the results were actionable, not descriptive.

But you don't have to take my word for it. Funny enough, ChatGPT will tell you itself:

In addition to differences in the type of query they answer best, there are a few other inherent strengths of chat and search that make each technology powerful for specific use cases and situations. Here are just a few:

ChatGPT Strengths:

• The user inherently expects chat to be a more conversational, slower experience. A longer time to respond means you can use bigger, more powerful models to generate more detailed responses.

• Chat can take the history of the conversation into account. This means users can ask follow-up questions and dig deep into certain topics. (E.g., chat could help you debug your code.)

Search Strengths:

• Search is better for browsing experiences. For example, you would never want to use chat as the primary interface to your eCommerce site or your store locator. Those are visual browsing experiences, ideal for search.

• Search makes it easier to merchandise/hard-code results based on business logic. This is quite difficult to do in chat — though not impossible.

• It's much cheaper and faster: search is basically free to run. Chat is comparatively more expensive.

• Search will never make anything up. It will only return results based on the information and content that has been indexed in the search engine's database.

The answer here is easy: both. There are massive benefits to each that businesses need to start incorporating into their strategy. Customer experience is critical, and businesses can't afford to lose any opportunities to drive engagement based on poor experiences.

With conversational AI (powering chat) businesses are able to provide that streamlined, natural language-based conversation that consumers are looking for. Chat is able to bring context and continue the conversation — unlike search, which is limited from one search to the next.

It's worth noting that Chat is just one application of large language models (LLMs), and there are many more. You're even able to ask them to perform arbitrary tasks such as finding a pattern in data and making changes (which is a concept the Yext platform leverages in its AI Data Cleaning transform).

With search, on the other hand, businesses can streamline the customer journey and drive engagement. Not only are searches faster, but they can insert valuable calls-to-action, maps, and other rich results that help drive engagement and revenue.

Generative models are amazing at "understanding" natural language and generating natural responses that seem accurate.

However, they also:

• Make stuff up (otherwise known as "hallucinating")

• Can't look up real-time data

• Do not provide a business with control over the answers

• Take a LONG time to train

The key to providing an amazing chat or search experience exists with the underlying data. There are different times and places where each can be useful, but at the end of the day, whether you are searching or chatting, you just want the right answer.

Sometimes this data is sourced from the entire internet, which is great for answers to the "encyclopedia-type" queries mentioned above. However, for many queries, businesses will want to provide specific data that they are the ultimate authority on, such as their menu items or hours of operation.

Enter the knowledge graph. A knowledge graph a headless content management system (CMS) that uses entity relationships to optimize an organization's content for 3rd party search, voice search, chatbots, and other sophisticated AI. When you combine the power of the Knowledge Graph with multiple large language models (LLMs) including ChatGPT and other proprietary technology, you can to deliver an accurate and seamless natural language experience that functions effectively in a business context.

With a knowledge graph, a business can gain control of their content and bolster their digital experiences by serving as an interface between the business and the generative model powering chat, or the algorithms powering search.

This architecture provides the consumer with the benefit of a seamless, conversational experience, and gives the business control of the information that is surfaced.

That said, we are still in the early stages of understanding how conversational AI is going to change the way we access information. The speed at which information changes is going to leave businesses searching for ways to marry the right experience at the right time with accurate and up-to-date information. Adaptability will continue to be the name of the game.

Want to learn more about how to apply the proliferation of generative AI to your marketing and personalization strategies? Click here to watch our recent virtual event.