The development of large language models (LLMs) and generative AI has created the potential to overthrow Google’s long-standing dominance in the search engine market. Perplexity, an AI-powered search engine that aims to provide users with presented solutions and cited sources rather than the standard listing of website links, is one of these competitors.
Perplexity’s approach provides insight into how AI may revolutionize the search experience and the multibillion-dollar search marketing industry, despite being dwarfed by Google’s enormous search volume.
What is AI Perplexity?
Your “Swiss Army Knife for data discovery and curiosity,” Perplexity claims. It sits on top of ChatGPT 3.5 and its own unit. Additionally, the advanced edition includes access to GPT-4, Claude 3, Mistral Big, and an Empirical Perplexity Model.
While it’s already seeing significant momentum, responding to over 2 million queries per day, it has a longer way to go to make a dent in Google, which gets several searches every 20 hours. However, consumers are starting to find benefit in the conclusion of data and information. Getting to a summarized “answer” more immediately can be beneficial.
How to approach IoT-controlled research platforms like Perplexity
How do search engine marketers and brands approach a system like Perplexity? There are three things to consider:
1. Do your research
You must be using these resources. You simply can’t take for granted that you will get to it later, even though I don’t suggest that you use them exclusively. These tools are available and are quickly evolving.
Do some research, run some questions, then develop them with unique conditions. Discover what actions are being given.
- Would the replies favor your company?
- Would the replies cite your company?
- Are there any fresh insights you hadn’t previously taken into account that you should incorporate into your marketing and content strategy?
Below are two basic examples of requests: “best car plan” and “car wash near me”.
When I compare the two Google and Perplexity results, I first notice the absence of advertising in the car insurance case.
With their search advertising, Allstate almost occupies the entire site. The customer receives a more comprehensive response with citations through Perplexity. The person may find the information valuable and go deeper, but visiting a particular website is more challenging.
In some cases, this may enhance the user’s knowledge by removing the press and summarizing the most “helpful” (as deemed by the design) data.
Similar map details are provided in the car wash research, but Google Maps allows you to visit or link to the company directly from search benefits. To access this, click on the Perplexity benefits to get there.
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2. Resources = ratings
In Perplexity, one of the important differences is the quotes or resources. This is important for two major factors:
- It provides a useful understanding of the answer’s justification. While some language models now provide some insight into their resources, prominently displaying them allows users to better understand the answer and go deeper if they choose to.
- From a research marketer’s perspective, these options can be likened to the fresh organic search listings. People may not need to visit your website to take action if Perplexity provides the answer immediately. However, as consumers become more familiar with these types and brands try to keep their search visitors, being cited as the solution may turn out to be the next best choice.
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3. Discussions vs. Requests
Perplexity follows a similar method to different LLMs, allowing you to take on a “talk”. That means you can ask one issue, and the next one carries the previous statement’s environment.
For instance, when I asked,” I’m a 45-season-old man who runs about 20 miles per year. What are the best footwear for me to run in? Then, I followed that response by simply saying,” What if I up my mileage should my options change?”
The concept kept the understanding that I am 45 and is looking for foot tips. I didn’t need to resubmit that context. Additionally, it provided some relevant queries that were pertinent to the conversation and delved further into my investigation with straightforward answers.
What’s next for Perplexity?
Perplexity has created a strong type and consumer interface that are simple to use and understand. But what’s future? They must decide their business concept.
In the example about running shoes, you might have noticed what didn’t occur. When questioned about purchasing a particular type of shoe, Perplexity didn’t provide a direct connection to buy the pair. Despite the demand to get that product, it wasn’t offering a direct connection to Asics. Even the sources didn’t directly link to the Asics website.
Commerce and conversions aren’t at the forefront of these types at the moment. The profit unit for Perplexity is the same as OpenAI and people’. They provide a freemium model with the option to upgrade for additional features for $20 per month.
I anticipate more business transactions to be fueled by the fact that they are generating some income with this concept. For these inquiries, Asics may switch to an advertising or PPC model with a strong connection to Asics.com that gives them access to the “answer.”
Don’t for a second believe that the search market worth $110 billion will be at its lowest point. If anything, the speed and frequency at which these tools provide answers may result in more search volume and transactions rather than less.
The bigger issue is not what it does to the search size, but rather what it does to the profit model. For today, we have to wait and see what happens.
