The biggest shift was moving from keyword optimization to intent optimization. We started training our AI to understand the context behind search queries rather than just matching terms. For instance, when someone searches "small business marketing automation," they're often really asking "how can I save time on repetitive marketing tasks without losing personal touch?" We restructured our clients' content to answer the underlying intent, not just the surface query. This approach doubled qualified lead generation because we're now capturing prospects at the exact moment they're ready for solutions.
Our visibility strategy is no longer about "ranking for clicks". It's about being cited as a trusted, machine-readable source in AI-generated answers. We moved from chasing page-by-page rankings to building AI-friendly visibility around the entire brand entity. Google's SGE and AI Overviews don't look for keywords. They pull from sources they trust and can interpret. Thus, your structured data must match what's on your site and what's said about you across LinkedIn, product catalogs and other mentions. On the practical side, we rebuilt e-commerce content into AI-parsable. Product details in raw HTML, fragment-ready definitions (bulleted specs, anchored FAQs), and expanded descriptions around real buyer queries ("best sofa for small apartments under $800"). We layered in Product, Review, and FAQ schema and encouraged detailed customer reviews — which AI now often echoes directly in summaries.
The most disruptive was the reconsideration of the organization of content based on purpose, as opposed to isolated keywords. Using the AI search, users can query with more in-depth questions, and thus we repackaged pages to look more like full-fledged answers than postings. To give an example, rather than creating a number of articles on how to build links, guest posting, and backlink audits, we created an authority hub page covering the whole gamut of link acquisition techniques, overlaid with FAQs, schema markup, and internal links that were reflective of follow-up queries. The change not only boosted the positions in classic SERPs but also augmented making it to the AI-generated summary and dialog search previews. The trick was to write in a style that predicts the subsequent queries of the user, or what he would reasonably wish to know later, and to incorporate the same into the body. This actually implied less spindly posts and more heavily organized resources, which AI models are more likely to prefer today because it is how individuals formulate queries in natural language.
At Lusha, we adapted our visibility strategy for AI-powered search by launching our own AI-powered lead generation tool and placing strong emphasis on customer success stories with concrete ROI metrics. This approach allowed our content to be recognized as having practical value, which helped us secure features in major technology publications. The most significant change was shifting from general product messaging to highlighting specific customer outcomes, as this created the type of substantial, verifiable content that AI search engines prioritize.
The team transformed their content organization approach to create answers suitable for AI systems instead of human readers. The legal client used to focus intensely on keyword placement and header organization in their content. The content needed to follow a question-answer structure while including statistical data and brief summary sections that AI systems like Google's SGE and ChatGPT could directly extract. The most significant change? The team redirected their content creation efforts from targeting Google's first page to creating content for the featured snippet section which serves as the AI's response output. The company achieved a spot in SGE and received three times more inquiries during one month after transforming their 2,000-word blog into a simple Q&A format.
AI-powered search has in a short time replaced traditional SEO efforts, or has at minimum added significant overhead. One example is the need to perform SEO on multiple platforms, for example traditionally one could focus on Google with a side trade in Bing and Yandex, however now businesses must also perform SEO through leading LLM providers such as ChatGPT, Anthropic, Deepseek and many others. There are many paid services that have appeared over the past year alone that provide LLM specific SEO which has increased marketing budgets. Free SEO can be performed by creating a free account on each service and regularly just asking questions about the company. Long tail searches such as "what does Genbounty do?", "how does Genbounty provide EU AI Act compliance services". By asking these natural phrases just as a user would you can assist LLMs in providing the correct information.
You know, for a long time, our visibility strategy was all about keywords and trying to rank for a search term. But with the rise of AI-powered search, we knew that wasn't going to work anymore. Our customers aren't just searching for a keyword; they're asking a complex question. Our old content was getting lost in the noise. The most significant change we made to our visibility strategy was to shift our focus from being a publisher to being a direct resource. We stopped trying to create content that would rank. We started creating content that would answer a customer's specific, nuanced question. The core insight came from our operations team. They are on the front lines, and they were hearing about all the specific, detailed problems our customers were facing. From a marketing standpoint, we created a new content strategy based on those problems. Our content isn't just an article; it's a detailed, step-by-step guide that is a direct solution to a problem. The impact this had was a massive increase in our brand credibility and our visibility. Our content is now being surfaced by AI recommendation systems because it's a direct solution to a customer's problem. We're not just getting a mention; we're getting a mention from a system that knows our customer's specific problem. The biggest win is that we've turned our business into a trusted, reliable source of information. My advice is that the best way to get noticed by AI isn't to try and outsmart it. You have to be a direct solution to a customer's problem. When you do that, your content becomes a direct solution for your customers.
I don't have a "visibility strategy" for AI. My strategy is just to be helpful and honest. The most significant change I made was to stop treating my website and social media like a sales flyer and to start using them to answer the real, simple questions people have about their roofs. My office manager told me that people were calling all the time with the same questions: "How do I know if my roof has hail damage?" or "What's the difference between a roof repair and a full replacement?" So, my approach was to write direct answers to those questions on our website. My "strategy" was just to be a good neighbor, and my office manager helped me get the answers online. This has made a huge difference. When people search for a question about their roof, they find our website. They see that we're a local company that's willing to give them free, honest information. They see that we're a resource, not just a company trying to sell them something. This has led to a lot of new business from people who are already convinced that we are the right choice. My advice to other business owners is simple: stop trying to be clever with your marketing. The most significant change you can make is to just be a source of honest information. The best way to get found online is to be a person who is trying to help. That's the only strategy you'll ever need.