TIP | Companies should invest more in PR, according to Robby Stein (Vice President of Product Management at Google Search).

What does the current transformation of Google search mean for businesses?

Google Search is evolving into a platform where users can ask virtually anything and effortlessly obtain information on almost any topic. This represents a fundamental shift from traditional keyword-based search. Users no longer need to enter specific keywords but can instead ask complex, multi-sentence questions in natural language. Google leverages AI to access its vast knowledge base, the context of the web and the world, and specific product information. This allows the search algorithm to deliver more relevant and precise results than ever before. The fundamental functionality of search remains unchanged, but it expands to encompass new dimensions of use.

How does AI work in generating recommendations?

Google's AI functions very similarly to how a human would approach making recommendations. The underlying system for AI mode uses a technique called query fan-out. In this process, the reasoning model performs dozens of related search queries based on the user's question. These queries aren't simply generated arbitrarily, but are based on contextual understanding. The AI ​​uses Google Search itself as a tool and performs these searches under the hood. This means that for each user query, the AI ​​actually goes through multiple search and analysis processes to arrive at a comprehensive answer. This approach allows the AI ​​to consider relevant context that might be missed in a direct response.

What role do PR and content play in AI visibility?

PR and content play a central role in visibility in the AI ​​era, albeit with a shift in focus. Established SEO practices and the generation of high-quality content remain crucial. However, Robbie Stein from Google emphasizes a change in focus: companies should invest more heavily in PR, not just so that people see the content, but primarily so that AI can find and utilize this information. This is a significant conceptual shift. If information about a company appears in respected publications, business directories, or public articles, AI will classify these sources as trustworthy. Many users report investing in PR but later discovering that people aren't seeing the articles. When they then query AI on the same topic, the AI ​​finds the article and uses the information. Therefore, the focus on PR hasn't become obsolete, but rather taken on a new dimension.

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How do the requirements for content in the AI ​​era differ from classic SEO requirements?

The fundamental requirements for high-quality content remain unchanged in the AI ​​era. Standard best practices for creating great content still apply. This means that businesses should continue to focus on creating informative, valuable, and well-structured content. However, there is an important nuance. The types of questions people ask AI are increasingly complex and fall into different categories than traditional keywords. People primarily use AI for how-to guides, purchasing decisions, and life advice. This means that businesses should align their content strategy to support these usage patterns. For example, if a business operates in e-commerce, it should not only create product descriptions but also comprehensive buying guides, comparisons, and informative content to aid in decision-making.

Another important point is the clarity and comprehensibility of the information. Because the AI ​​uses Google Search as a tool and then processes the results in its context window, websites that offer clear and helpful information are more likely to appear in this context window. This allows the model to consider these websites when answering user queries.

How does AI use personalization to deliver better results?

Google is working on further personalizing search, with the future option for users to integrate services like Gmail and Google Drive to receive even more helpful answers. This isn't fully implemented yet, but initial experiments are already available in Google Labs. Users can already experiment with personalized shopping and local restaurant recommendations in Google's search labs. The vision is that AI could eventually know which brands you love, which places you frequently visit, or what school projects you have coming up, in order to generate even more interesting and personal answers. This would transform search from a generic tool into a personal assistant that understands and considers the user's individual needs and preferences.

What multimodal search options does Google offer?

Multimodal search is one of the fastest-growing ways to find information. Visual searches via Google Lens have seen a 70 percent year-over-year increase. This means that users can not only search using text, but also upload images or take photos, and the AI ​​can then find similar products, related content, or further information. This multimodal functionality is also being extended to include voice, allowing users to have live conversations with the AI ​​by speaking. The system can then analyze real-time videos or respond to real-time information. This opens up entirely new ways to interact with information.

How are local businesses recommended by AI-powered search?

For local recommendations, AI uses information from multiple sources. Google has a database of 250 million or more real-world locations worldwide. This database is live and constantly updated with information from local businesses that update their Google listings. When the AI ​​receives a query like “I want an Italian restaurant for a romantic dinner date,” it uses the query fan-out technique to perform related searches. For example, it might search for “great Italian restaurants for romantic dinners” and then analyze the reviews, information, images, and other contextual clues to generate recommendations. The system can thus analyze reviews, consider the quality of information, and make personalized suggestions based on the user's preferences.

Will Google Ads disappear in the AI ​​era?

Robbie Stein doesn't believe Google Ads will disappear. The way people use Google isn't fundamentally changing, but rather expanding. People will continue to make the various traditional search queries they use today, but they will also increasingly make more complex, multimodal, and agent-based queries. Google is initially focused on building great products and experiences. But there are already experiments with AI-powered ads. New and novel ad formats could emerge. For example, a user with a complex query like, "I want to renovate my house, I have this type of wood, these tradespeople are nearby, and this is my budget," could receive targeted offers for services or products relevant to that specific situation. These new ad formats would offer more precise and helpful recommendations than are possible today.

How can companies optimize their visibility in AI search?

Companies should take several concrete steps. First, it's crucial to follow best practices for high-quality content. This means creating content that is genuinely helpful, informative, and clearly structured. Second, companies should invest more heavily in PR to ensure their information appears in reputable sources that AI can easily find and process. Third, companies should become experts in their own industry and the use cases of AI. This means understanding the questions users are asking and ensuring their content answers those questions. Fourth, companies should leverage tools like Google Trends and the features in Google Ads to understand what users are searching for and what trends are emerging. These tools provide insights into the types of questions people are asking and allow companies to adjust their content strategy accordingly. Fifth, companies should ensure their Google Business Profiles are complete and up-to-date, as AI will utilize this information.

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What types of content should companies create to be found by AI?

Based on Robbie Stein's findings, companies should focus on three main content categories, as these are the primary use cases for which people utilize AI. The first category is how-to guides. This means creating detailed, well-structured instructions that explain complex processes step by step. The second category is purchase decision content. Here, comprehensive product comparisons, reviews, guides, and information that support potential customers in their decision-making process are crucial. The third category is life coaching and personal advice. This can vary across different industries, but generally involves creating content that helps people with important life decisions or everyday challenges. For all these content types, it's essential that the information is easy to understand and clearly structured so that AI can process it easily.

How are ratings and the authenticity of business information assessed in AI search?

This is a difficult question, and Robbie Stein offers a nuanced answer. Reviews could potentially be considered by AI if they prove helpful. However, it's challenging to look at a single factor in isolation. Generally, a business should focus on established best practices similar to those that rank highly in traditional Google search results. AI thinks like a person discovering a page for the first time. When you Google something, which pages appear at the top? This is still a good indicator of how AI might evaluate a website. Regarding authenticity, AI likely uses similar signals to the traditional Google algorithm. This means that websites with established authority, verified information, and backlinks from trusted sources will perform better. Therefore, buying reviews or other artificial signals is likely not only unethical but also ineffective, as AI will utilize similar recognition mechanisms to the traditional algorithm.

What new features has Google implemented to support AI recommendations?

Google has introduced several new features. One of the most notable is the Agentic capability, which allows AI to perform actions on behalf of the user. For example, a user can say, “Find me a dog grooming appointment,” and the AI ​​can actually make phone calls to local businesses to check availability and book an appointment. This is a significant step beyond traditional search. Another important feature is visual inspiration and shopping. Users can take a photo of a cream and ask, “Find me similar products” or “Show me similar ingredients.” The AI ​​can then analyze web images, find similar products, and help the user find what they are looking for. This is particularly useful for industries such as fashion, interior design, or beauty. Another feature is live video search, which allows users to point their camera at an object and ask the AI ​​what it is or where to buy it.

How does Google Search differ from ChatGPT and other AI assistants?

Google has several unique advantages over other AI platforms. The first and most important advantage is access to Google's knowledge bases and systems. Google has spent years working on systems that index and update financial information, local business information, product information, and much more. For example, if the AI ​​is asked to plot the top-performing pharmaceutical stocks, it can pull that information from Google Finance. A second major advantage is its connection to the web. Google AI can not only answer questions but also provide links to trusted sources where users can find more information. This is a significant difference from ChatGPT, which only generates text. A third advantage is its integration with visual features. Google Lens and its visual search capabilities allow the AI ​​to understand what the user is looking for, not just through text but also visually. A fourth advantage is its inspiration and design orientation. While ChatGPT focuses on text, Google has integrated AI into the context of inspiration and design, which is especially useful when users want to decorate their homes or make design decisions. Finally, Google AI has access to real-time information and live updates, which makes it possible to provide current information immediately.

What advice does Robbie Stein give entrepreneurs on developing products in the AI ​​era?

Robbie Stein highlights several key points for product developers and entrepreneurs. First, he advises becoming a “student of gaps.” This means identifying gaps in the market and understanding what people expect from a technology that doesn't yet address them or doesn't master them well. Inspiration or design could be examples—areas where AI has historically struggled but where there is significant user interest. Second, he emphasizes that software development is becoming increasingly democratized through natural language, requiring less programming knowledge. This means the idea will be more important than the technical implementation. Third, he advises conducting in-depth interviews with a small group of users to understand whether the idea actually works. A dozen thorough interviews are sufficient. The critical question is: Are users still using the product daily two months after the initial demonstration? Fourth, he stresses the importance of daily value stickiness for mainstream consumer products. This means the product must offer daily value and motivate users to use it regularly.

How many user interviews are necessary to assess whether a product idea works?

Robbie Stein is a big advocate of small sample sizes and thorough research with limited sample sizes. He believes that around a dozen people is sufficient. The key test is this: if you give someone a prototype and say, "Here's a product, try it out," they'll use it for the first week, especially if they're friends. But the crucial question is whether users are still using the product daily two months later. Without exceptional circumstances, this won't happen unless the product offers them genuine added value. This is a very practical criterion, suggesting that entrepreneurs should prioritize quality over quantity during the testing phase. It's better to work very closely with a small group and get genuine feedback than to survey a large group without seeing real engagement signals.

How should companies use Google's existing tools to optimize their strategy?

Robbie Stein recommends that businesses and marketers leverage multiple Google tools to inform their strategy. Google Trends is a tool many businesses underestimate. It provides real-time insights into current trends and offers keyword values ​​for various search terms. This can help understand what users are looking for. Google Ads also has fantastic estimation features. While booking ads, you can see traffic estimates for different keywords, which helps understand the level of interest. Additionally, there's Google Search Console and other search tools that provide insights into how a website performs in search results for various queries. Robbie Stein also suggests that Google will provide even more data on what people are searching for in the future, not just for advertisers, but for everyone. This will be especially important as more people search using these new search methods, whether through long, specific questions or multimodal and voice-based queries. Understanding these new search trends will be crucial for any business that wants to remain relevant.

What is the key message for companies in the transition phase to AI-powered search?

The central message is that best practices are not obsolete. High-quality content, clear and helpful information, and strategic PR remain essential. However, these practices must be executed with a new focus. Companies should not only ensure that people see their content, but also that AI can find and understand it. This means creating more precise, clearer, and better-structured information, with a stronger focus on PR to ensure that this information appears in reputable sources. It also means understanding the new use cases of AI, whether it's how-to guides, purchasing decisions, or life advice. Companies should also understand the new tools and features that Google offers and evaluate their opportunities and risks. For entrepreneurs and product managers, the message is that in a world where software development is democratized, the idea and understanding of customer needs will be more important than pure technical expertise. This means being a keen observer of market gaps and conducting in-depth user research to ensure that the idea truly addresses a genuine need.

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