As a global leader in SEO, content marketing, and data analytics, Anastasia Braitsik has her finger on the pulse of how digital discovery is evolving. In a recent observational study, she challenged the prevailing industry narrative that AI has fundamentally changed how people find local services. Her findings reveal that when it comes to transactional needs—finding a doctor, a dentist, or a clinic—our search habits are far more traditional than many experts assume. We sat down with Anastasia to discuss the surprising persistence of keyword-style searches, the transactional nature of local AI queries, and what this all means for the future of local SEO.
With 75% of users still relying on keyword-style searches for local services in ChatGPT, what does this reveal about ingrained user habits? How should a local business practically apply this insight to their SEO strategy, and what specific metrics should they prioritize?
It’s a powerful reminder that old habits die hard, especially when they’re efficient. For two decades, we’ve been trained to communicate with search engines using a specific shorthand, and that behavior has become second nature. It simply requires far less cognitive effort to type “dentist 11214” than it does to formulate a complex sentence. We saw this clearly in our study; users consistently chose the path of least resistance. For a local business, this is actually reassuring. It means the foundational work of traditional keyword research and tracking is not only relevant but critical. They should continue to prioritize and track performance for these core, location-based keywords, because that’s precisely what potential customers are still typing into AI models when they need a service.
We’re observing that nearly half of local service searches on ChatGPT are single, “one-shot” prompts. Why are users so transactional in these moments, and how does this contrast with the more conversational behavior seen when their intent is purely informational? Please share an example.
When a user has a specific, transactional need, their mindset is fundamentally different. They aren’t looking for a deep conversation; they’re looking for a solution. Our data showed that nearly half of all sessions—45% to be exact—were just a single prompt. The user asks, the AI answers, and the interaction is over. This is because their goal is to get a list of providers and then move on to the next step, like visiting a website or checking reviews. For example, a user looking for a “hair transplant” used an average of only 1.33 prompts. This stands in stark contrast to an informational query, where a user might ask ChatGPT to explain a complex topic, leading to a natural back-and-forth. For local services, the interaction is a means to an end, not a journey of discovery.
Some in the SEO industry advocate for converting traditional keywords into long, conversational sentences for AI. Given that users are sticking to simple keywords, what are the risks of this over-complicated approach? Please outline the key steps a local clinic should follow for effective keyword research today.
The biggest risk is simply wasted effort. You’re optimizing for a hypothetical user who doesn’t seem to exist yet, at least not in the local service space. The data is clear: people are still using keywords. For a local clinic, the process should remain grounded in reality. First, they need to identify their core transactional keywords, such as “dermatologist to check a mole” or “place to get botox.” Second, they must combine these with all relevant geographic modifiers—zip codes, neighborhoods, and city names. We saw a user type “good plastic surgeons in brooklyn 11214 area,” which is a perfect example. Finally, they need to track these keyword variations to understand their visibility. This straightforward, proven approach directly mirrors current user behavior and is far more effective than over-engineering prompts.
Current behavior seems driven by efficiency and old habits. As users become more accustomed to advanced AI, how might their search behavior for local services evolve? What specific AI advancements could finally shift them from keywords to more complex, multi-turn conversations for their transactional needs?
Right now, efficiency is king. As long as a simple keyword prompt gives users what they need, there’s little incentive to change. However, I do believe this will evolve. The shift will likely happen when AI can offer a truly superior, value-added experience through conversation that a simple keyword search can’t replicate. Imagine an AI that not only lists dentists but also cross-references your insurance plan in real-time, checks their immediate appointment availability, and books it for you within the chat. When the AI becomes a genuine assistant that can complete the entire transaction through a nuanced dialogue, that’s when we’ll see users naturally adopt more conversational habits. Until then, the lower-effort option will almost always win.
What is your forecast for the future of local SEO? Specifically, how will the relationship between traditional keyword optimization and conversational AI search evolve for small businesses over the next three to five years?
My forecast is one of evolution, not revolution. For the next three to five years, traditional keyword optimization will remain the bedrock of local SEO. Small businesses absolutely must not abandon it. However, they will need to start layering a “conversational” understanding on top of that foundation. This means ensuring their website content, business listings, and FAQs directly and clearly answer the types of questions users might ask verbally. The relationship will be symbiotic: keywords will get them into the AI’s consideration set, but rich, well-structured, and authoritative content will determine whether the AI actually recommends them in its conversational response. It’s about being findable through old habits while also being prepared for the more sophisticated queries of tomorrow.
