2nd Order Thinkers
2nd Order Thinkers.
The New Search Engine War Perplexity vs. Google Search
0:00
-10:13

Paid episode

The full episode is only available to paid subscribers of 2nd Order Thinkers

The New Search Engine War Perplexity vs. Google Search

Will Google adapt or become obsolete in the next ten years?

I still remember the days when MSN and Yahoo! were used, and then Google became the go-to place whenever we needed to find an answer to a question.

In the early 2000s, Google emerged as the best solution available.

Unlike Yahoo’s cluttered portal approach, Google’s innovative PageRank algorithm was complemented by a simple, fast, and user-friendly interface focused solely on search, as you and I know today.

On the revenue side, the AdWords advertising model provided a significant revenue stream that supported its growth, allowing it to maintain a competitive edge and dominate the market.

Yet, this method was a product of its time — limited by the technology available. We accepted the need to click through multiple links and pages because there was no better alternative.

Google is so ingrained in our lives that “Google it” has become a universal phrase. With over 90% of global search queries going to Google and 65% of people using Chrome as their browser, you’d think Google’s position was unshakable.

Despite Google’s nearly 30 years of dominance, users’ fundamental needs to find what I’m looking for when searching online have remained consistent.

Google Has Never Properly Addressed the Search Intent

Our fundamental need has been consistent: to find answers to our questions.

Whether it was finding the right book in a library before the internet or searching on Google since the 2000s.

The unchanged intent, we always look for:

  • Efficiency: Getting answers with minimal effort and time.

  • Accuracy: Receiving correct and relevant information.

  • Simplicity: Interacting with straightforward interfaces.

However, Google has not fully satisfied these intents.

My question to you: when was the last time you Googled something slightly complex, like the best price of a hotel in Canada or how to fix my relationship with my girlfriend, not lead you to link after link for you to explore or to click through?

I wanted to know How many years have passed since Google was launched.

This is what I got from Google:

A screenshot of the question: How many years have passed since Google was launched.

Not only has it not answered my question, but it has also got my intention wrong.

We never see these as a problem because we have known this way of doing things for years. This is how it works until it is not valid. This is only a behavior we developed, adapting the best tool that was available to us. 
This unnecessary need for adaptation led to the emergence of new technologies aimed at bridging this gap.

Why Google Search Is Showing Its Age?

As a product professional at heart, I believe that Google’s search experience feels cluttered due to its significant dependence on SEO-driven content and advertising within the SERP. This strategy has led to a compromised user experience, heightened friction, and diminished trust.

This misalignment between our needs and the product offering presents an opportunity for competitors who prioritize user-centric design and direct answers.

While Google has attempted to incorporate AI into its search with features like the AI Overview, it still largely relies on its traditional model:

  • Ad-Centric Results: Prioritizes sponsored content, which can detract from relevance and user satisfaction.

  • SEO Influence: Search results can be manipulated through SEO tactics, not necessarily reflecting the most accurate information.

  • Inefficient Journey: Users often need to navigate multiple links to find precise answers.

The Advancements in AI Achieved What Google Couldn’t in 1998

With these limitations becoming more apparent, advancements in AI have opened doors to more effective solutions. We have reached a point where AI can deliver on the original user intent more effectively:

  • Natural Language Processing: Allows systems to understand and interpret human language with greater accuracy.

  • Neural Networks and Large Language Models:Enable platforms to process vast amounts of data and generate human-like responses, improving over time through fine-tuning and updates.

Followed by the conversational interfaces, only possible after the above two happened. This UI provides direct answers in a dialogue format, reducing the need for additional clicks. Products like Perplexity and chatbots like chatGPT or Claude leveraged the above advancement.

We saw a complete transformation that allows users like you and me to receive clear, contextually relevant answers without the distractions of ads (for now) or the clutter of SEO-optimized but unhelpful information.

Perplexity AI vs. Google Search: A Shift in User Expectations

Now, here’s Perplexity filling the gap. You all know ChatGPT too well already, so I’m not repeating that.

Listen to this episode with a 7-day free trial

Subscribe to 2nd Order Thinkers to listen to this post and get 7 days of free access to the full post archives.