Google is increasingly answering search queries on its own: AI Overviews have been live in Germany, Austria, and Switzerland since March 26, 2025, and the conversational AI Mode followed on October 8, 2025. For online store owners, this doesn’t necessarily mean “less traffic”; rather, it means tracking where clicks are shifting and optimizing content so that AI responses cite it.
At a Glance
- DACH Rollout: AI Overviews since March 26, 2025; AI Mode as a separate dialogue tab since October 8, 2025.
- Ahrefs reports an average 34.5% drop in click-through rate for position 1 when AI Overviews are displayed (as of August 2026).
- This primarily affects informational how-to traffic —transactional searches and product pages are significantly less impacted.
- Actions to Take: Measure traffic by page type instead of estimating it; structure content to be citable; support product data with structured data.
Is Google AI Mode available in Germany?
Yes. AI Overviews—the AI summaries above the search results—have been rolled out in the DACH region since March 26, 2025; and AI Mode has also been available since October 8, 2025: a dedicated chat tab for follow-up questions and full-fledged research within the conversation. Both formats cite and link to sources—anyone who doesn’t appear there will largely disappear from view for that search query, even with a good organic ranking.
Will I lose traffic due to AI Overviews?
That depends on the page type. Ahrefs estimated the click-through rate loss for the top organic position when AI Overviews are displayed at an average of 34.5 percent (as of August 2026). This primarily affects informational upper-funnel traffic—how-to guides, comparisons, and buying guides. Transactional search queries and product pages have been significantly less affected so far: Google continues to display shopping results and traditional search results here. It’s therefore crucial to examine your own data.
| Page Type | Typical Impact | Recommendation |
|---|---|---|
| How-to Guides & Blogs | High (AI overviews answer the question directly) | Structure content to be citable: answer in the first sentence, data points, FAQ blocks. |
| Category pages | Medium | Supplement purchase guidance content, clean structured data, internal linking. |
| Product pages | Low so far | Keep product markup and merchant feed consistent—they also feed AI-driven recommendations. |
| Brand/direct traffic | Virtually none | Strengthen brand awareness—direct traffic is independent of AI responses. |
What content does Google cite in AI responses?
Content that clearly and verifiably answers a specific question is prioritized. In practice, this means: question-based headings based on actual user queries, the answer in the first sentence, data points with sources, tables and lists instead of walls of text, and FAQ sections with clean markup. Trust signals such as identifiable authors, update dates, and consistent company information are also among the factors that increase the likelihood of being cited—though there’s no guarantee of appearing in AI responses.
What does this mean for product and category pages?
For the transactional part of the store, the groundwork remains crucial: complete product markup (price, availability, GTIN, reviews), consistency between page markup and the Google Merchant Feed, and stable product URLs. This data now powers Shopping listings—and, increasingly, product mentions in AI responses. By also answering purchase-related questions directly on category and product pages, you anchor the advice right where the purchase takes place.
How do I measure the impact in my own store?
Use segmentation instead of overall numbers: In Google Search Console, you can analyze advice, category, and product pages separately—if impressions are rising while the click-through rate is falling, it means content is being displayed but clicked on less frequently. It’s also worth checking traffic from AI services in the referrer analysis. AI visibility can be checked externally—for example, with the Sistrix AI Check, which we featured in a separate news article. Anyone looking to set priorities ahead of the holiday shopping season should start with this assessment.
What the XONIC Shop System Offers
The XONIC Shop System provides the technical foundation for citability as standard: news and how-to articles are automatically marked up with NewsArticle JSON-LD, including an author profile; FAQ content includes FAQPage microdata; and product pages feature structured product data, including the Google Merchant Feed. Starting with version 4.8.2, you can also specifically control which AI crawlers are allowed to index the store. The feature overview provides a summary; the guide to Google tools explains Search Console and Merchant Center.
Frequently Asked Questions About AI Overviews and AI Mode
Sources
Stephan Dunger
Stephan Dunger is one of the brains behind the XONIC store system. He has been developing the platform together with the team since 2012 - from the database to the interfaces to the checkout.
A passionate programmer, technical mind and consultant at the same time: with his in-depth knowledge of store systems and e-commerce, Stephan combines the depth of a developer with an eye for the big picture. Together with the XONIC team, he shapes the technical direction, consistently thinks about functions from the retailer's perspective and advises on customized solutions.
The result is software with a face: customers don't get an anonymous provider, but a direct line to the people who develop XONIC. Pragmatic, fast and at eye level.
