Generative Engine Advertising (GEA): How advertising works in AI responses

More and more customers are no longer starting their product search with just two or three keywords. Instead, they are describing their problem in a complete sentence, asking follow-up questions, and letting AI assist them in making the perfect choice!

For example, "buy pool pump" becomes:

Which energy-efficient pool pump is suitable for a 40-cubic-meter saltwater pool and can be easily connected to my existing system?

For merchants, this shifts not only organic visibility. Paid advertising is also migrating into AI-powered search results and conversational dialogues. Ads are already appearing in or alongside Google AI Overviews, in Microsoft Copilot, in Perplexity, and in ChatGPT.

This exciting development is increasingly referred to as Generative Engine Advertising, or GEA for short. But how does GEA actually work? What makes it different from SEA and GEO? And do shop owners need to create brand-new campaigns for every single AI platform now?

The Key Takeaways at a Glance

• GEA refers to paid advertising within AI-powered search and conversational interfaces.

• The term is not yet uniformly defined and serves primarily as a collective term for innovative new ad formats.

• GEA does not replace SEA. In fact, many AI ads draw directly on your existing Search, Shopping, or Performance Max campaigns.

• GEO and GEA are not the same: GEO improves organic visibility in AI answers, while GEA purchases labeled ad placements.

• High-quality product data, highly relevant landing pages, and clean conversion tracking are becoming more important than ever.

• For most shop operators, a controlled test is much wiser than a complete shift of your advertising budget.

What is Generative Engine Advertising?

Generative Engine Advertising describes ads that are displayed within a search or conversation shaped by generative AI. Unlike a classic search ad, the platform doesn't just evaluate a single keyword. It can also take into account the content of an AI response, the ongoing conversation, and the clear purchase intent behind it.

For instance, a customer might first ask which running shoes are best for knee problems. Next, they narrow down their requirements by surface, fit, budget, and preferred brand. It is only during the course of this dialogue that a concrete intention to buy emerges—and that is exactly where a perfectly tailored ad can shine!

However, GEA is not yet a clearly defined campaign type that works the same way on all platforms. Rather, the term groups together various dynamic advertising formats:

• Ads above, below, or right within an AI-generated search overview,

• sponsored products alongside an AI answer,

• ads tailored to the context of an ongoing conversation,

• sponsored follow-up questions,

• interactive ads through which customers can ask additional product questions.

Crucially, there is a clear separation between the organic answer and the advertisement. The major platforms label paid content clearly and emphasize that advertisers cannot simply buy the organic AI response. In ChatGPT, OpenAI states that ads do not influence the answers. Similarly, Perplexity explains that advertisers are given no influence over the actual content of the responses.

GEA, GEO, SEA, and SEO: What's the Difference?

While these terms sound similar, they pursue completely different goals!

Thus, GEO influences whether a brand appears in an answer due to relevant, trustworthy, and machine-readable content. GEA, on the other hand, creates additional paid reach around those answers.

In practice, these disciplines go hand in hand. An ad can successfully capture attention, but the underlying product page must convincingly answer the customer's question. That is why product data, rich content, reviews, and a technically clean website remain absolutely crucial even for paid AI advertising.

Why GEA is Becoming Vital for E-Commerce

Classic search engine advertising reacts heavily to keywords. In contrast, generative systems can take a much broader context into account. This opens up amazing advertising opportunities in situations where a customer has already described their problem in great detail.

This is particularly exciting for products that require explanation. Think of spare parts, technical components, furniture, health products, or B2B assortments. In these areas, customers aren't just searching for an item; they want to know which solution fits their specific requirements perfectly.

For shop operators, this brings about three exciting shifts:

1. The Search Query Becomes a Conversation

A single search entry no longer represents the entire purchase intent. Through dialogue, the AI learns about the customer's specific requirements, limitations, and priorities. This allows advertising to become incredibly context-rich and relevant.

2. The Ad Becomes Part of the Decision-Making Process

A great GEA ad must do more than just grab attention. It should offer a meaningful next step: a matching product, a helpful comparison, professional advice, a configurator, or a concrete solution to the problem described.

3. Product Data Gains Even More Importance

AI platforms require highly reliable information on products, prices, variations, availability, and features. A clean product feed is therefore more vital than ever! It is evolving into a key foundation for shopping ads, AI recommendations, and agentic shopping processes.

Where GEA is Already Happening Today

GEA is not a distant vision of the future. However, the major platforms are pursuing different approaches.

Google: Ads Around AI Overviews

Google can display existing Text, Shopping, Local, and App ads above or below AI Overviews. Ads directly within the AI overview are currently only available in selected markets. These are powered by your existing Search, Shopping, and Performance Max campaigns.

Google takes both the search query and the content of the AI overview into account. This means merchants do not necessarily have to set up a completely new campaign structure. However, at present, delivery in AI Overviews cannot always be analyzed separately, which makes a clean comparison with classic search placements a bit of a challenge.

For more details, check out the Google Ads Help on ads and AI Overviews.

Microsoft: Existing Campaigns in Copilot

Microsoft seamlessly transfers ads from existing search campaigns into Copilot experiences. For shop operators, this is a wonderfully easy entry point: your existing campaign assets, product data, and landing pages can be used directly for dialogue-oriented placements.

With AI Max and Performance Max, Microsoft aims to identify complex search intents and display ads on AI interfaces like Copilot Search and Copilot Answers. Ads in Copilot are already available in German-speaking markets.

ChatGPT: Advertising Based on Conversational Intent

OpenAI launched ads in ChatGPT in 2026 and provides its own Ads Manager for this purpose. Advertisers based in Germany can easily use this self-service platform. Campaigns can be targeted toward impressions, clicks, or conversions, depending on your business goals.

To ensure relevance, ChatGPT looks beyond a simple search term. According to OpenAI, the context and intent of the current conversation, the landing page, and the ad copy itself are all taken into account. The ad remains clearly separated from the organic response and is labeled as an advertisement.

Conversions can be measured via pixels, Conversions API, or both. This is turning ChatGPT from a purely informational platform into a highly measurable advertising channel. Details and current availability can be found in the ChatGPT Ads Information.

Perplexity: Sponsored Follow-Up Questions

Perplexity is experimenting with sponsored follow-up questions and paid placements alongside answers. This format perfectly fits dialogue-oriented usage: a brand can offer a helpful next topic of discussion without influencing the content of the organic response.

The rollout began in the US and is still more limited compared to Google, Microsoft, and ChatGPT. For many German merchants, Perplexity is currently an exciting channel to observe and test.

What Makes GEA Different from Classic Search Engine Advertising?

The biggest difference lies not in the ad format itself, but in the depth of intent available.

With classic SEA, a platform often only sees a search query like "ergonomic office chair". In an AI dialogue, however, it might also learn that the user is tall, sits for eight hours a day, suffers from back pain, and has a maximum budget of 600 euros.

This dynamically changes the campaign logic:

Keywords won't disappear overnight, of course. Google and Microsoft continue to use existing campaign structures. At the same time, audience, feed, content, and context signals are becoming increasingly powerful.

How Shop Operators Can Prepare for GEA

Before shifting your valuable budget to a new AI advertising channel, it's essential to make sure your foundations are rock solid!

Keep Your Product Data Complete and Clear

Titles, descriptions, attributes, variants, prices, and stock levels must always be up-to-date. For products requiring a high level of consultation, information on the area of use, compatibility, dimensions, materials, and exclusions is also incredibly important.

If this information is missing, neither an AI nor a campaign can reliably determine whether your product is the perfect match for the user's query.

Align Landing Pages with Real Customer Questions

An AI ad can match a situation with incredible precision. However, if the destination page only contains generic marketing slogans, that advantage is quickly lost.

Great landing pages should therefore answer concrete questions, explain differences, showcase relevant product features, and offer a clear next step. Categories, buying guides, comparisons, and configurators can be just as crucial as individual product detail pages.

Check Your Tracking and Data Transfer

New ad placements are only economically viable if you can accurately measure clicks, purchases, leads, and key milestones. This requires correct consent management, server-side tracking, clean campaign parameters, and reliable synchronization with your shop or CRM data.

Patience is key when evaluating results, as platforms and reporting features are still evolving. For example, Google points out that ads in AI Overviews cannot currently be analyzed through separate segmentation.

Use Existing SEA Campaigns as Your Launchpad

Many GEA placements are already generated from your existing Search, Shopping, or Performance Max campaigns. Therefore, merchants should first check whether their current campaigns, creatives, product feeds, and landing pages are well-equipped to handle complex queries.

GEA often doesn't start with a brand-new ad account, but simply with a higher-quality database in your existing setup!

Which Key Performance Indicators (KPIs) Matter for GEA?

Click-through rate (CTR) and cost-per-click (CPC) remain important, but they don't tell the whole story. An AI dialogue can reach customers much earlier in their decision-making process or pre-qualify them highly effectively. Therefore, your evaluation should look at multiple levels:

• Reach and impressions on AI placements,

• click-through rate and cost-per-click,

• qualified visits and interactions on the landing page,

• add-to-cart and conversion rates,

• cost per new customer or lead,

• revenue and contribution margin,

• share of assisted conversions,

• new customer acquisition rate and customer lifetime value (LTV).

The ultimate measure of success is not whether a GEA campaign generates a high volume of conversations or clicks, but whether it successfully reaches economically valuable customers for your business.

Should Your Shop Start with GEA Right Now?

Running a test is highly recommended if:

• You are already investing relevant budgets into SEA or Shopping,

• your product range requires explanation or advice,

• your customers frequently compare products or need guidance,

• your product data and landing pages are excellently maintained,

• your tracking reliably captures purchases or leads,

• you can allocate a limited test budget without short-term pressure to perform.

On the other hand, you should focus on improving your fundamentals first if you lack comprehensive product data, aren't measuring conversions cleanly, or if your existing SEA campaigns still have clear structural issues. A new channel won't fix these weaknesses—it will often just highlight them.

How to Run a Successful GEA Pilot Test

To get started, you don't need a complete overhaul of your marketing strategy. A controlled pilot project is perfect!

1. Select a Use Case: Choose a product group with a clear need for advice and sufficient search volume.

2. Verify the Data Foundation: Complete your feed, product attributes, prices, inventory, and landing pages.

3. Choose Your Channel: Start with Google, Microsoft, or ChatGPT, depending on where your target audience hangs out.

4. Define a Clear Goal: For example, target new customer revenue, qualified leads, or contribution margin.

5. Cap the Budget: Run GEA as a controlled test alongside your existing campaigns first.

6. Compare Results: Evaluate conversion, new customer share, and overall profitability, not just click costs.

7. Learn and Iterate: Analyze search and conversational intents, and continue to refine your content, feed, and ads.

This way, you build solid, actionable knowledge without prematurely replacing a well-performing acquisition channel.

Conclusion: GEA Expands SEA with Conversational Context

Generative Engine Advertising won't change the entire performance marketing landscape overnight. However, this development is already highly relevant in practice: Google, Microsoft, ChatGPT, and Perplexity are actively integrating ads into AI-powered search and dialogue interfaces.

For shop operators, the brilliant opportunity lies in reaching customers at the exact moment their needs are described in far greater detail than a classic keyword search could ever capture. At the same time, the familiar keys to success remain the same: reliable product data, relevant landing pages, clean tracking, and economically guided testing.

Therefore, GEA doesn't replace SEA—it beautifully enhances search engine advertising with the context of a natural conversation. By preparing your data and campaigns today, you can confidently test these exciting new placements without giving up your tried-and-true channels!