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More recently we’ve seen a shift from chatbot-style interfaces to an “answer engine” user interface from the likes of Perplexity and Claude.
Instead of raw text responses, we are now seeing accurate answers with authoritative sources in the text as links.
This has prompted a change in my search habits which I never thought I’d see.
While Google remains a staple for many kinds of search workflows, I increasingly find myself turning to AI-powered “answer engines” to complement my research.
The allure of direct, concise answers makes it feel more efficient and offers a real alternative to link-laden search results.
Google's search model relies on algorithms that index the web and return a ranked list of links in response to user queries.
This model has created an entire industry around search engine optimisation (SEO), where businesses, agencies and content creators compete to have their pages ranked higher.
The effectiveness of this model is evident in Google's market share, which has hovered around 90% for the last two decades.
However, this model has its limitations.
Users often need to sift through multiple links and pages to find the specific information they seek, which can be time-consuming and inefficient.
Despite advancements in algorithms and AI to improve search results, the fundamental approach remains the same: serving up links and creating real estate which serves their AdWords model.
Unlike Google, answer engines provide direct, personalised answers to user queries, drawing from an ever-expanding corpus of data and understanding context in an increasingly nuanced and accurate way.
Perplexity can answer complex questions on an infinite array of topics directly whilst providing links to sources.
This ability to provide immediate, contextually accurate answers significantly enhances the user experience, making search faster and more efficient.
Google's situation illustrates the innovator's dilemma: when established companies risk losing their leading position by fortifying a successful business model rather than adopting disruptive innovations.
A large part of Google’s commercial success, including its revenue from search advertising, is built on the traditional search paradigm.
Transitioning to an answer engine model will cannibalise its existing revenue streams and require a massive overhaul of its business model.
Google's investment in SEO-driven content has created an ecosystem where businesses and agencies are deeply entrenched in a Search Engine Results Pages (SERP) interaction model.
Shifting to an answer-engine approach would not only disrupt Google's internal processes but also the broader digital marketing industry.
The shift towards answer engines will inevitably disrupt SEO practices.
In the current model, SEO focuses on optimising content to rank higher on SERP.
However, in an answer engine environment, the focus will shift towards creating content that AI can easily parse and understand to provide direct answers.
This change will likely prioritise content quality, context, and relevance over the dark arts of SEO such as keyword stuffing and backlink building.
Businesses will need to adapt by ensuring their content is authentic, engaging and aligned with user intent to be favoured by AI answer engines.
For businesses and SEO practitioners, this shift demands a reevaluation of strategies and practices.
Embracing the change and focusing on creating high-quality, contextually relevant content will be crucial in the new era of search.
As we stand on the cusp of this transformation, the ability to adapt will determine who thrives in the age of generative AI.
In much more recent news (Tuesday 5 Aug 2024), after being sued by the US Department of Justice for monopolistic behaviour, a US judge ruled that Google acted illegally to crush its competition and maintain a monopoly on online search and related advertising.
Ironically, Google now faces real competition from AI answer engines so its monopoly won’t need to be challenged in the courts, but on these streets instead.