Anastasia Braitsik stands at the forefront of the digital marketing evolution, recognized globally for her ability to turn complex data analytics into high-impact SEO and content strategies. As businesses struggle to adapt to the era of generative AI, Anastasia has pioneered a unique methodology that bridges the gap between traditional paid search and the burgeoning world of AI-driven discovery. Her expertise lies in identifying the “hidden” assets within a company’s marketing stack—specifically the years of data buried in search accounts—and repurposing them to dominate platforms like ChatGPT, Google’s AI Overviews, and Perplexity. By focusing on how real humans speak rather than just how algorithms crawl, she has helped countless brands secure a foothold in the future of search.
In our conversation, we explore the shift away from speculative AI strategies toward data-backed visibility. The discussion covers the transition from short, robotic keywords to long-tail conversational queries that mimic natural human speech. We dive into the practical application of the search terms report as a research tool and the critical importance of aligning high-performing ad copy with on-page text to satisfy AI crawlers. Additionally, we touch on the technical optimization of product feeds and a comprehensive five-step framework designed to help marketing teams move from guessing to knowing exactly what information AI tools need to cite their brand.
Many search queries are shifting from short, punchy phrases to long, conversational questions. How should businesses adapt their historical search data to meet this new behavioral trend in AI-driven search?
The shift toward natural language is the most significant behavioral change we have seen since the invention of the mobile search. People are no longer just typing “crm small business” into a search bar; they are asking ChatGPT very specific questions, like “what’s the best CRM for a five-person landscaping company that mostly needs scheduling and invoicing?” To keep up, brands need to stop treating their Google Ads account as just a lead generator and start treating it as a research laboratory. You should be exporting at least 12 months of search term data to find those long-tail, conversational queries that broad match and Performance Max have been capturing for years. These terms aren’t just keywords; they are the exact blueprints for the questions your customers are asking AI right now, providing you with a direct line into the user’s intent.
What makes a paid search account such a powerful, yet often overlooked, asset for gaining visibility in AI search tools compared to starting an AI strategy from scratch?
Most marketing teams are panicking and trying to build AI strategies from the ground up, but they are ignoring the fact that they already own the raw data required for AI visibility. Your ad account contains years of validated experiments, showing exactly which value propositions earn clicks and which products actually drive revenue. AI tools like Perplexity and Microsoft Copilot reward clear answers and structured data—things that paid search practitioners have been optimizing every single day to improve Quality Scores. When you realize that your product feed infrastructure and your best-performing landing pages are already formatted for machine learning, you stop guessing and start leveraging assets you have already paid for. It’s the difference between starting a fire with two sticks versus having a tank of gasoline and a match ready to go.
You’ve mentioned that a brand’s best-performing ads often contain the exact messaging AI tools like to quote. How can marketers effectively move that ad copy onto their websites to improve organic AI visibility?
There is often a massive disconnect where a website says one thing, but the high-performing ads that actually convert say something completely different. Since AI tools only see your website and never your ads, you have to bring that winning language into the light. If your best-performing headline is “24/7 emergency service — arrival in 90 minutes or less,” that specific promise needs to be on your page as plain, crawlable text, not just hidden in a script or an image. AI tools love specific numbers, concrete timeframes, and guarantees because they are easy to cite as facts. By identifying your top responsive search ad assets and republishing them as on-page content, you provide the “quotable” evidence that AI systems look for when deciding which business to recommend to a user.
Product feeds are traditionally viewed as a tool for Shopping campaigns, but you suggest they are now a primary signal for AI. How should a company upgrade its feed for this new environment?
Your product feed is essentially a structured map of your business, and it is now a primary eligibility signal for whether you appear in Google’s AI Overviews or AI Mode. The era of keyword-stuffed, robotic titles is over; you need to rewrite your product titles in descriptive, plain language that mirrors how a person would describe the item to a friend. For example, when OpenAI rolled out product feed ads in May, they made it clear that ChatGPT’s shopping results draw heavily from these structured feeds. You should fill in every optional attribute you’ve been skipping, keep your pricing and availability updated in real-time, and submit your feed directly to any AI search tool that accepts one. One well-maintained feed can now power both your paid Shopping campaigns and your organic recommendations across multiple AI platforms simultaneously.
For a marketing team looking to implement these changes immediately, what are the most critical steps in your five-step framework to ensure they don’t lose ground to competitors?
The very first thing you must do is “open the gates” by making sure your site is indexed in Bing and that your robots.txt file isn’t blocking AI search crawlers like OAI-SearchBot. After that, the heavy lifting happens in your search terms report, where you should filter for queries that are five or more words long to identify themes of conversational intent. We once worked with an HVAC client who found customers asking, “why is my AC running but not cooling the house,” which led us to create specific, citable answers that didn’t exist on their site before. Once you have those answers, you add schema markup—that simple behind-the-scenes code—to ensure there is zero confusion for the AI about what your page is claiming. Finally, you have to measure your progress by setting up specific tracking in your analytics for visits from chatgpt.com and other AI portals to establish a baseline.
What is your forecast for the future of AI search?
I believe we are moving toward a total convergence where the wall between “paid” and “organic” AI visibility completely disappears. We are already seeing this with Google’s AI Overviews and the way ChatGPT is integrating product feeds directly into its conversational interface. In the next few years, businesses that continue to run two separate strategies—one for paid search that learns and one for organic search that guesses—will find themselves outspent and outpaced. The companies that will dominate are the ones that treat their data as a single, fluid asset, using every search term and every winning ad to strengthen their overall digital footprint. Eventually, your “ad account” won’t just be a place to buy traffic; it will be the primary data source that dictates how the entire AI-driven internet perceives and recommends your brand.
