If you are investing in SEO today, you're probably wondering how to drive more qualified organic traffic. Valid question, but no longer sufficient.
Consumers are turning to AI-powered search tools to ask questions, seek recommendations, and compare options. One in four customers[1] already turns to AI-powered platforms as their primary source when searching for information, making purchase decisions, or finding recommendations. Retail discovery is therefore being reshaped by AI systems that synthesize options, compare products, and recommend brands before a user clicks on a website.
People are moving from traditional search methods to AI-powered, conversational search engines and agents. AI search engines increasingly provide ready-to-use answers early in the customer journey, shaping decisions before users click on links, as they can now manage the entire purchase journey, from search and comparison to transaction, within a single conversation.
This is where Generative Engine Optimization, or GEO, enters the picture. Generative AI platforms such as ChatGPT and Gemini are transforming how consumers discover products and evaluate purchase options. Brands must adapt their strategies to remain visible and relevant within these new AI-driven discovery environments.
The following article explains what the shift from SEO to GEO represents in practice: how search behavior is changing, why retail is leading this transformation, and what companies can do to improve their visibility in AI-driven discovery.
Search behavior is moving from short keywords to structured, conversational questions. As shown in our AI-Generated Website Traffic Report, users are starting to ask full, natural language questions, rather than isolated product terms.
And while traditional search engine optimization (SEO) focuses on ranking links in search results, retail generative engine optimization (GEO) is about becoming the direct answer in AI-driven discovery platforms.
Instead of searching for “smartphone,” they ask:
Then, AI systems respond with synthesized summaries. In this context, Generative Engine Optimization (GEO) focuses on helping brands appear in the answers generated by AI systems, not just in the list of links shown in search results. As AI tools increasingly summarize options and recommend products directly to users, brands need to structure their content so it can be understood and included in these responses.
At the same time, the interface itself is changing. In 2024, 59.7%[2] of searches resulted in no clicks. Users are consuming information directly on Google’s results page. Ahrefs’ December 2025 update shows that AI Overviews reduce CTR for position one results by approximately 58%[3].
This confirms that many purchase decisions are now shaped earlier in the customer journey, often before a user clicks on a website.
If you lead a retail business, this means that the shortlist is often formed before a user reaches your eCommerce site.
Retail is not just another vertical in this transition. It is the primary one, especially for e-commerce, which is heavily impacted by AI-driven discovery.
Our cross-industry analysis shows that Retail generated over 550,000 AI-driven visits between January and October 2025, roughly eight times more than the next sector analyzed.
Retail decisions frequently involve:
AI acts as a decision assistant in these scenarios.
For example, when a user asks: “What is the best laptop for remote work and occasional gaming under 5,000 RON?”
The AI response typically includes:
Brands with high awareness and strong reputations are more likely to be recommended by AI product search engines.
If your brand is not structured and clear enough to be included in that answer, you are invisible at the most influential stage of the funnel.
Brands must adapt their content, data, and commerce experiences to remain visible in AI-driven discovery. In practice, this often means structuring product pages more clearly, creating comparison content that answers common buying questions, and building stronger brand visibility across trusted sources online.
One of the key insights from our report is what we call the “Quality Filter” effect in retail.
Mass-traffic players do not automatically dominate AI-driven discovery. Brands with:
They all tend to perform disproportionately well in AI environments, because AI systems prioritize clarity and reliability over pure volume.
If your product pages contain vague descriptions, inconsistent specifications, or unstructured blocks of text, they are difficult for AI systems to extract and synthesize.
GEO focuses on building content around conversational queries and question-driven sections, such as FAQs and explainers, to reflect how users interact with AI assistants and chat tools. Instead of focusing only on traditional keywords, GEO also considers the questions people are likely to ask when evaluating a product or service. In this environment, content must be structured not only for search engines, but also so that AI systems can easily interpret and synthesize it.
Practical ways to optimize for AI include:
SEO remains foundational. Technical performance, structured data, internal linking, and crawlability still matter. Digital marketing strategies are now essential in the context of retail generative engine optimization (GEO), as evolving online channels and AI integration demand high-quality content and engagement across platforms.
However, if you stop there, you leave value on the table.
We began discussing this shift publicly on June 28, 2024, when we analyzed the impact of Search Generative Experience[4] and the future of SEO in an AI-driven environment.
Since then, our industry research has confirmed that traditional search traffic hierarchies do not automatically translate into AI visibility. Consistent brand presence across digital ecosystems is crucial, as it enhances AI performance and search rankings. Maintaining a consistent brand presence across various platforms enhances visibility in AI search results.
AI systems rely on signals from across the web, such as: mentions in trusted publications, product reviews, and community discussions; they all influence whether a brand appears in AI-generated recommendations. Maximizing industry publications and social platforms like Reddit, LinkedIn, and YouTube further boosts AI citation and overall brand visibility. User-generated content and reviews significantly influence how AI shopping tools recommend products. In generative AI optimization, what others say about a brand often matters more than what the brand says about itself, especially in AI search contexts.
A mature optimization strategy now includes:
Make sure that:
AI models extract content differently from traditional search engines. Clean architecture increases citation probability.
It's important to understand how different AI platforms access and interpret online content, as some rely solely on training data while others perform live web searches to provide more current information. AI platforms that use only training data may have outdated knowledge, whereas those that perform live searches can deliver fresher, more accurate responses.
Retrieval augmented generation[5] is a method where large language models ground their answers in up-to-date information by searching external sources in real time.
Retail companies can optimize generative AI engines by focusing on high-quality data integration, adopting Retrieval-Augmented Generation (RAG), and implementing Generative Engine Optimization (GEO). Using Retrieval-Augmented Generation (RAG) connects AI models to real-time, proprietary data, such as inventory and pricing, rather than relying solely on pre-trained knowledge.
Conduct prompt research. Identify:
Consider how 'ai mode' in AI search platforms influences how information is accessed and utilized, affecting whether results are based on real-time data or only on training data. Also, recognize that AI-driven ecosystems are leading to hyper-personalization, where recommendations are tailored based on user history and preferences. User history plays a key role in enabling AI agents to deliver highly personalized content and recommendations, increasing user engagement and conversions.
Then build content explicitly designed to answer those prompts.
Example: Instead of creating another generic “Best Laptops 2025” page, structure content as:
AI systems respond better to precise, context-rich answers.
AI engines synthesize across sources. Your brand authority must extend beyond your own website.
This includes:
For retail generative engine optimization, it's essential to define clear success metrics. Unlike traditional SEO, GEO requires tracking both brand visibility and website citations as distinct indicators of effectiveness. AI search creates two distinct types of success metrics: brand visibility and website citations, which require different strategies to optimize.
Demonstrating early wins through small-scale pilot programs can help build confidence and organizational support for broader GEO initiatives.
Inclusion in AI-generated answers often reflects ecosystem trust, not only on-page optimization.
If you only track rankings and sessions, you are measuring the final stage of a longer process.
A modern GEO dashboard should aim at including:
As our report notes, AI visibility functions as a form of digital endorsement. Even when AI traffic represents a small percentage of total visits, the growth trajectory is clear and accelerating.
Between June and November 2025, AI traffic share for top domains nearly doubled from 0.05% to 0.09%. Early movers are positioning themselves before this becomes mainstream competition.
The competitive question has evolved.
We are moving from:
How do we rank first?
To:
Are we among the brands AI systems trust enough to recommend?
There’s no doubt that AI-powered discovery increasingly shapes how consumers research and compare products. Companies need to rethink how they approach search visibility.
A practical way to begin is by asking three questions:
• Are our product pages structured for extraction and synthesis?
• Do we explicitly answer high-intent, comparison-based questions?
• Are we monitoring AI visibility with the same rigor as rankings?
If the answer to any of these questions is unclear, reach out.
In our AI-Generated Website Traffic Report, we identify the brands most frequently cited by AI systems across industries and outline practical steps companies can take to start building a Generative Engine Optimization strategy.
Our Digital Marketing team can help assess your current visibility and provide a complete guide to building an effective GEO strategy.
References
1. https://business.adobe.com/resources/digital-trends-report.html
2. https://sparktoro.com/blog/2024-zero-click-search-study-for-every-1000-us-google-searches-only-374-clicks-go-to-the-open-web-in-the-eu-its-360/
3. https://ahrefs.com/blog/ai-overviews-reduce-clicks-update/
4. https://blog.zitec.com/ro/impactul-sge-in-cautarile-google
5. https://www.nvidia.com/en-us/glossary/retrieval-augmented-generation/