AI Is Changing Customer Discovery Forever. Who Wins?
Until today, search has been the enabler of the internet. It served as a powerhouse of digital economics, the foundation of the Direct-to-Consumer (DTC) business model, and the model for organic customer discovery. Search Engine Optimization (SEO) underpinned how brands and companies crafted their marketing and communications strategies.
Artificial intelligence (AI) changes all of this.
Instead of searching, consumers are increasingly relying on AI for customer discovery. Two terms have emerged to try and describe optimization of the new paradigm: Artificial Intelligence Optimization (AIO) and Generative Engine Optimization (GEO).
The differences can be confusing: “Generative Engine” refers to the now well-known LLM chatbots that are serving as the front-line for customer information retrieval (Perplexity, ChatGPT, Grok, etc) where “Artificial Intelligence” refers to the broader concept of optimizing for machine intelligence, not just chatbots. In short, GEO is a subset of AIO, focusing on optimization specific to LLM-enabled chatbots.
While subtle, the differences will become more important as the technologies standardize. But for now, the recipe for success is the same for both:
- Make the right data accessible
- Measure the traffic
- Optimize
Make the right data accessible
AI doesn’t care about the visual impact of your website; it cares about the structure, relevance, and clarity of your data. While industry standards are still forming, there are actionable tips you can use to optimize for discovery.
Focus on clarity
There’s a joke that half of the world’s AI is used to expand bullet points into long-form text while the other half is to condense long-form into bullet points. Anyone who’s used ChatGPT can attest to unnecessary filler. Ironically, to feed these models, LLMs are tuned to select concise, clear, expert-level information.
Provide fresh, unique, expert data
It’s been said, “data is the new gold.” By definition, an LLM aggregates and synthesizes data. And – like search engines of the past– the internals of the LLMs are closed, and the tuning mechanisms are done behind closed doors. However, it’s safe to assume that LLMs will rely on specific, relevant, and authoritative data. Generic and stale information will be ignored.
Adopt understood schemas
Like most things with communication, standardization helps distribution. While early, there are still standards that will increase the viability of AI using your content. Schema.org is a long-recognized standard body for a unified vocabulary; experts recommend adoption to help both search and AI. Now, Model Context Protocol (MCP) is an emerging protocol for communicating with LLMs, and is shaping up to be the HTTP for communication between LLMs.
Measure the traffic
Of the three steps today, measurement is the most uncertain. There aren’t (yet) adopted standards to communicate traffic origination or referrals from Generative Engines. However, this step also holds the highest potential for reward. Brands or websites that get a leg up on measurement can begin to optimize earlier, and using SEO as a primer, they will emerge as early winners in capturing most of this emerging discovery channel.
Who wins?
DTC was enabled by search optimization and targeted advertising. AIO will reward a different set of company attributes:
- Offering a physical good or service that can provide clear access to inventory and pricing. AI can’t make you a sweater or fix your plumbing. And a scaled advertising model has yet to emerge for AI. Today, brands that can offer context and availability of their offering will top the list of LLM-referral traffic.
- Constantly updated access to unique, up-to-date information. Wikipedia is a great example of a company leaning into offering easy access to data. However, monetization of this model is a big unknown. In the past, the majority of access to content was monetized via advertising or subscriptions; the reward mechanism of AI is yet to be determined.
- Figure out accurate tracking and fast iteration. We’re going to witness the birth of a new type of company: the AI-enablers. As humans rely on AI to provide information, there will be an entirely new set of companies that enable this revolution by quickly figuring out what works.
While it’s still early days, the impact of AI is thunderous. The levels of funding, user adoption, and excitement is unparalleled in our history. Information delivery will be brokered by AI. Companies and brands that recognize and act on this paradigm will start to understand how to best engage this emerging– soon to be dominant– channel for customer acquisition.
We will look back on today as an unparalleled opportunity to understand and act on this new paradigm. How will you prepare to win?
