How Brands Win AI Shopping with GEO

The search landscape has been completely disrupted by artificial intelligence (AI). As AI shopping experiences improve, brands cannot just depend on traditional SEO to be discovered. LLM (Large Language Model) tools like Google’s Search Generative Experience, Perplexity, and ChatGPT are changing how people shop. These tools pull data from the open web and are becoming the new walled gardens for research and comparison.

Generative Engine Optimization (GEO), a strategy focused on optimizing content for visibility in AI-driven shopping experiences and generative models like ChatGPT and Google AI Overviews, is becoming increasingly important.

The best practices in this guide were developed by combining publicly available insights on how AI-powered search experiences rank and surface shopping content with known AI ranking signals such as structured data, trusted domains, and engagement metrics.

For example, at MikMak, we noticed ChatGPT appearing as a traffic source for our brand partners in 2024. This means ChatGPT was already including MikMak-enabled commerce experiences in its AI product search results. This trend is growing quickly. To help brands succeed in this new environment, here are some key tips for AI shopping search optimization, including how MikMak is already helping top brands put these tips into action.

Since November 2024, traffic from ChatGPT to MikMak Commerce-enabled pages has grown more than 250x, with an average month-over-month increase of 164.5 percent. The chart below details this AI commerce search growth and shows how frequently MikMak’s shoppable media pages are being surfaced through AI shopping in ChatGPT.

Cumulative Growth in MikMak Traffic from ChatGPT between November 2024 and May 2025

This explosive growth highlights the critical need to prioritize generative AI optimization in your eCommerce strategies. If you are not discoverable in AI product search, you are missing a major source of qualified traffic.

Brands looking for guidance on how to boost eCommerce sales with generative AI must consider not just how their products are listed, but how AI tools interpret their overall presence across the digital shelf.

As AI-powered search tools increasingly surface answers from closed-loop environments, without necessarily driving traffic back to your site or paid media, brand equity becomes your most defensible asset. Just like in the days of SEO and social, brands with high awareness, strong reputations, and clear digital presence are more likely to be recommended by AI product search engines. The difference now? AI is the filter, and your content must already be authoritative to be included.

That is why continued investment in demand generation beyond the AI search walled gardens, including Reddit, Meta, Amazon, and CTV, is essential. It is not just about buying traffic. It is about consistently showing up and building trust across paid, earned, and owned channels, which all feed into how Generative Engine Optimization models evaluate and rank your brand.

It is important to note that, unlike traditional paid search or programmatic ads, AI-generated shopping results do not always surface or prioritize paid placements directly, but paid media still plays a vital role in fueling the signals AI looks for. A successful Generative Engine Optimization strategy encompasses not only optimizing your product pages but also creating the optimal media mix to enhance brand authority across all channels. Here is how:

Generative Engine Optimization drives engagement on your owned and earned assets

When you run paid media that directs traffic to your brand website or high-performing retailer product pages, you generate clicks, time on site, and conversions. These are signals that search engines and AI-driven shopping platforms may use to evaluate your content’s authority.

Generative Engine Optimization amplifies user-generated content, earned media, and reviews

Paid creator campaigns, influencer partnerships, and whitelisted ads increase the volume and visibility of UGC, which AI shopping tools often summarize or reference when recommending products. Mentions of your brand in editorial articles, product roundups, news features, and expert reviews can directly influence how and where your brand is featured in generative AI search engine optimization environments, especially when they link to your product pages or contain keywords AI uses for context.

Generative Engine Optimization improves the performance of content already referenced by AI

If AI is pulling from your product pages or retailer listings, optimizing those pages with better-performing paid creatives, such as visuals, headlines, and pricing, improves downstream engagement and conversions, which in turn makes them more likely to be elevated by AI commerce engines.

These are essential components of AI in marketing, where performance depends less on traditional ad placements and more on brand presence across ecosystems that feed into AI summaries.

Brands asking how brands are using AI to win across search, social, and shoppable platforms will find the answer in how consistently they apply Generative Engine Optimization across all touchpoints.

How MikMak Helps Brands Show Up in AI Shopping Searches

MikMak connects your paid, organic, and owned media efforts to actual retail outcomes. Through closed-loop measurement across platforms like Meta, Google, TikTok, Pinterest, and CTV, brands can identify which SKU, creative, and retailer combinations are driving conversions. This allows for smarter investments that support both performance and visibility in AI commerce.

AI systems rely on clean, structured data to identify and surface relevant products. Schema markups like Product and Offer help ensure that your listings are machine-readable and enriched with the details that AI platforms use to generate product recommendations. Brands that invest in maintaining accurate, structured product feeds improve their chances of being featured in AI-generated carousels, summaries, and purchase prompts.

How MikMak Helps Maintain Product Data for GEO

MikMak supports structured product feeds with real-time inventory and pricing and integrates with Product Information Management (PIM) systems to ensure product details are always consistent, accurate, and ready for syndication. This ensures that listings are not only discoverable but also up-to-date with accurate stock and promotional activity at the moment of search, which is a critical factor for AI platforms seeking to match user intent with immediately shoppable results.

Today’s shoppers increasingly begin their journeys on mobile, often expecting AI-powered assistants to show them the fastest path to purchase, whether online or in-store. Ensuring that your product pages and Where to Buy pages on your website are mobile-optimized, real-time, and geo-aware is essential to meeting those expectations.

How MikMak Helps Visibility in AI Shopping Searches for Local Shoppers

MikMak’s mobile-friendly Where to Buy solution, MikMak Commerce, gives consumers a seamless shopping experience across online and brick-and-mortar channels. MikMak Commerce’s geolocation technology dynamically populates retailers with in-stock products and enables shoppers to refine searches by state, city, or postal code, view store addresses, and get directions from their current location.