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:
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.
This screenshot compares visit stats Between Perplexity, chatGPT, Google — Jul 2024 — Sep 2024, and worldwide data. Takeaways here:
Google has captured 90% of the available user base: 4.3 billion users globally.
ChatGPT has captured around 9.81% of the market, and Perplexity held 0.22% in less than two years.
The significant barriers to AI apps are user habit, trust in AI-generated answers, and Google’s broader services ecosystem. These barriers slow their growth, but they are not insurmountable.
So, I make an assumption here based on my personal experience. It might not apply to all, but at least the early adaptors group. And it needs more information to be proven.
If anyone using those platforms is primarily looking for an answer, they can do so without switching between them. Then, the page per visit and average visit duration are actually on ChatGPT and Perplexity’s side.
The data implies that AI platforms provide quicker, more direct answers, which could attract more users who want information quickly.
Don’t believe me? I asked Perplexity the same question: *How many years have passed since Google was launched?
There was no fluff, no useless link. No taking me for a walk in the park, and still not telling me anything.
Undoubtedly, Google still has the largest number of visits; after all, it has been there with us for almost 30 years. But for how much longer?
Perplexity AI has reimagined how we search for information. Instead of giving you a list of links like a traditional search engine or SERP, it provides direct, conversational answers pulled from credible websites.
This challenges the very foundation of how Google excels at sorting and ranking.
Remember we talked about intent from the start? Perplexity has shown a path to what it is like to satisfy the intent of searching.
Perplexity’s approach better aligns with what users seek — quick, accurate answers without the need to sift through pages of results. Google’s model, while comprehensive, often requires additional time and effort to find the desired information. Many people I know have now set Perplexity as their default search engine.
This effectiveness shift has reminded me of historical examples where new technologies have disrupted established industries. Of course, it was a sad story for the one being disrupted.
A Historical Parallel: Canals vs. Trains — Adapting to Technological Change
The current situation between Google Search and Perplexity AI reminded me of a pivotal moment in transportation history: the shift from canals to railroads in the 19th century. I have previously covered the history of technology change in detail.
Canals: Once the Pinnacle of Transportation Technology
It doesn’t seem like it now, but in the early 1800s, canals were the cutting-edge solution for transporting goods and people. They revolutionized trade by providing a more efficient and reliable means of moving heavy cargo than overland routes plagued by poor road conditions. Investments in canal construction boomed, and canal companies flourished.
The Advent of Railroads
However, the invention of the steam locomotive and the expansion of railroads rapidly changed the landscape. Trains offered several advantages over canals:
Trains have drastically reduced travel time.
Canals froze over in winter, while railroads operated in (almost) all seasons.
Railroads could be built over diverse terrains, not limited to waterways.
Despite the clear benefits, many canal companies underestimated the impact railroads would have. They believed their established networks, the significant investments, and the unthinkable way to travel with steam engine machines would secure their positions.
Here’s a quote from that time:
Rail travel at high speed is not possible because the passengers, unable to breathe, would die of asphyxia. — Dr Dionysius Lardner (1793–1859), professor of natural philosophy and astronomy at University College, London
The Decline of Canal
As people soon realized that the railroads didn’t suffocate them, railroads expanded, and canal usage declined sharply. Goods and passengers shifted to the faster, more reliable trains. Canal stocks plummeted and never recovered. Companies that failed to adapt were left behind, becoming obsolete in a world that had moved on.
Just as canals were once the best available transportation solution, Google’s traditional search was the pinnacle of information retrieval in the early Internet era.
Similarly, Google faces the challenge of adapting to maintain its position in the evolving landscape.
Google’s AI Overview: An Attempt to Keep The Market Share
Google has the resources and technology to realign its search platform with user intent. They can achieve the following if they wish to:
Fully integrate advanced AI to provide direct answers and footnote the source.
Developing new revenue streams that don’t compromise user experience.
Utilizing its army of services to offer integrated solutions that add value.
Is the recent Google Replaces Search and Ads Chief, Moves Gemini Chatbot to AI Group the change to respond to the Glue in Pizza? Eat Rocks? mess it has been causing? Is the hope that introducing fresh talent into leadership can redeem Google’s tarnished reputation?
Can Google leverage its deep search knowledge combined with its AI experience and offer a genuine and no-BS solution? Or because their revenue is so entwined with ads, they continue to rely on their traditional models while others focus on delivering something users desire?
The answer is that Google quickly came up with something very similar: the AI Overview section. But, if you are a savvy searcher, you would also notice:
The AI Overview only activates when questions like why, who, when, and how are asked. It does not always activate, assuming that they are doing testing, so that's fine. However, more often than not, it generates irrelevant or wrong answers.
Perplexity, on the other hand, provides accurate, concise answers regardless of how you phrase your query. This puts Google in a tough spot.
I think the biggest hurdle for Google in this adaptation is its existing profit model. So, let’s talk business.
The Conflict of Interest: Satisfying Users’ Intent vs. Generating Revenue
As we know, Google’s search revenue comes from advertising. This model incentivizes maximizing ad exposure rather than optimizing for user experience. As users seek more direct answers, the ad-heavy model becomes a liability.
Initially, Perplexity AI distinguished itself by not relying on ads, offering a cleaner, more user-focused experience. However, sustaining growth solely through subscription fees and premium features presents significant challenges.
Subscription models can limit user adoption, especially when Google continues to offer free search options. Similarly, premium features may not generate enough revenue to support long-term profitability.
To address these sustainability issues, Perplexity AI is transitioning to an advertising-based revenue model. According to its CEO, Aravind Srinivas,
Ads are not evil…When ads are done right, it’s amazing, and generative AI is going to help us build even better targeting.
Perplexity plans to integrate native ads into related questions — which account for 40% of its queries — and offer brand-sponsored questions as users dive deeper into topics. This approach aims to introduce a sustainable revenue model without disrupting user satisfaction.
Perplexity is expected to launch ads in Q4 across 15 key categories, including:
Arts and entertainment.
Finance.
Food and beverage
Health.
Technology.
… and more.
Perplexity’s shift to advertising marks a significant change from its original ad-free model, which is understandable.
On top of this, Perplexity AI is also introducing a revenue-sharing model that allows content publishers to earn a percentage of ad revenue when their articles are cited in AI-generated responses. Early adopters include Fortune, Time, Der Spiegel, and others, indicating strong industry support for this collaborative monetization approach.
This emphasizes the necessity for innovative AI platforms to not only enhance user experience but also develop sustainable monetization strategies.
Questions for Google Search and Perplexity’s Product Leaders
Then, the questions for both Google and its competitors become:
What ratio of users are willing to pay for a direct search and an ad-free experience? Nothing stops Google from charging a premium fee for the same search experience as apps like Perplexity provide.
Is there a UI that can embed ads w/o sacrificing the experience? If a premium charge doesn’t deter users from the platform, Google has something to think about.
How much time does Google have before they start seeing a significant number of users adopting ChatGPT or Perplexity? Equally, how much time does perplexity need to secure a considerable market share before the cash dries?
Coming Next…
The tale of canals and trains is a cautionary reminder that technological advancements can swiftly overturn established industries. User intent remains consistent, but the means to fulfill it evolve. Companies that adapt thrive; those that don’t become footnotes in history.
Google can reinvent itself by aligning with user needs. The question is, will they seize this moment to innovate, or will they, like the canal companies of the past, watch as newcomers redefine the landscape?
Next, I am drafting an article about NotebookLM by Google as a sequence of this one.
Stay in touch, and
The New Search Engine War Perplexity vs. Google Search