How a Travel Giant Dominated Google’s AI Overviews with SEO

Overview

With the rise of Google’s AI Overviews in search results, a leading travel brand partnered with us to adapt its SEO strategy for the next era of search. The challenge was clear: appear consistently in AI-generated travel summaries across thousands of high-intent queries—like “best places to visit in Italy for families” or “2-week itinerary Peru Chile Argentina.”

This case study outlines how we reverse-engineered Google’s AI Overviews to elevate the brand’s presence in generative results and secure long-tail traffic from high-conversion queries.

The Challenge

By late 2024, Google’s AI Overviews had begun reshaping the travel search landscape:

• Fewer blue links. Organic results were pushed below the fold.

• AI summaries surfaced answers directly.

• Only authoritative, structured, well-cited content got surfaced.

The client, a global travel booking brand with 10M+ monthly visits, noticed:

• A 17% drop in organic visibility for high-converting, long-tail queries.

• AI Overviews pulling answers from Reddit, niche blogs, and small itinerary sites instead of their high-quality content.

• An urgent need to align their content and SEO strategy with AI-first search patterns.

Objectives

1. Earn a consistent presence in AI Overviews for thousands of long-tail queries.

2. Reclaim traffic lost to AI summaries.

3. Elevate EEAT signals and structured content for better AI interpretation.

4. Improve click-throughs by enhancing visibility in AI-referenced sources.

SEO Strategy for AI Overviews

We structured our approach into 6 pillars:

1. AI-Friendly Content Architecture (Entity-Based & Structured)

We rebuilt the content framework around entities, journey stages, and semantic clustering:

• Developed Topic Hubs for ~200 global destinations, each organized around traveler intent:
  e.g., [Destination] + for families, [Destination] + backpacking itinerary, [Destination] + food & culture.

• Each hub featured:

  • TL;DR summaries

  • Structured FAQs

  • Schema-based itinerary tables

  • Internal links to deep-dive blogs (e.g., “7-Day Chile Argentina Road Trip Itinerary”)

• Used JSON-LD with TouristDestination, Itinerary, and TravelAction schemas to guide Google’s AI in parsing intent and facts.

2. Optimizing for AI Answerability

To appear in AI Overviews, we treated every subpage as a zero-click content unit:

• Started every blog post with concise, factual, citation-ready intros (2-4 sentence direct answers)

• Added rich bullet point summaries after each section

• Used data-fact tags (custom data attributes) to annotate facts for internal NLP models and fine-tuning answer snippets

• Included author bios, date of last update, and source citations to enhance EEAT

Example:
On a page for “Best Time to Visit Patagonia,” the top of the page included:

Patagonia is best visited between November and March for warmer weather and full trail access. For fewer crowds, visit in late October or early April.

3. AI Overviews Competitor Reverse Engineering

We tracked which URLs were cited in Google AI Overviews:

• Built a weekly SGE monitor of 10,000 travel queries

• Scraped referenced sources and identified:

  • Common schema types (Itinerary, FAQ, WebPage)

  • Writing style (fact-first, scannable, short paragraphs)

  • Domain authority and page freshness

Used this data to reoptimize underperforming content with:

• Shorter intros

• AI-friendly titles (e.g., “10-Day Itinerary for Peru, Chile & Argentina (2025 Update)”)

• Added inline citations to reliable travel sources

4. Internal Linking & Hub-Spoke Integration

AI Overviews favor context-rich, internally connected content ecosystems.

We built an Internal Linking Engine to:

• Automatically suggest links from blog posts → destination guides → itinerary builders

• Prioritize linking based on semantic proximity and SGE win-rate

Result: a 70% boost in crawl frequency on deep pages and a higher rate of AI citations on linked resources.

5. E-E-A-T Optimization at Scale

Google’s AI Overviews reward sites with clear expertise and transparency.

We implemented:

• Author schema for every post, including LinkedIn, Twitter, and contributor travel history

• Verified by Locals badges for posts co-authored with local guides

• UGC-sourced quotes with attribution

• Rewrote outdated content with recent sources (TripAdvisor 2025 trends, Booking.com data, etc.)

6. Generative Multilingual SEO

To win AI Overviews in non-English markets:

• Used LLM-based content translation + localization

• Adapted facts, transportation info, and cultural context for each region

• Re-optimized metadata and schemas in Spanish, German, Portuguese

Example:

Our “10 Day Spain Road Trip” guide ranked in AI Overviews for “Ruta en coche 10 días por España” with translated schema and Spanish travel quotes.

Key Results (6 Months)

• Top 3 ranking in AI Overviews for over 900 “itinerary” queries

• Outranked Reddit and Quora in 55% of “trip planning” queries

• Secured citation position in AI Overviews for Google Discover cards

Lessons Learned

• Structured content + high E-E-A-T = AI visibility.

• AI Overviews are schema-driven and fact-first.

• Content that answers directly, links internally, and cites facts consistently wins.

• Entity-based architecture is essential for semantic clustering in AI summaries.

Conclusion

This project demonstrated that optimizing for AI Overviews requires going beyond traditional SEO. By combining structured data, internal linking, answer-first content, and EEAT signals, we helped a travel giant adapt to the new era of AI-first search—and reclaim visibility at the top of the funnel.

As Google continues to evolve, AI-first SEO is no longer optional—it’s the new organic battleground.