When I think about AI search, I realize it’s more than just translating or localizing results. It’s about deciding which sources, narratives, and realities emerge on top. This complex system is incredibly fascinating to me, especially when I consider how multilingual regions like Catalonia challenge these AI search systems.
The unique geography of Catalonia, where Catalan and Spanish languages coexist, serves as an excellent stress test for AI technology. It’s intriguing to see the underlying patterns unfold when the same queries are entered in both languages across platforms like Google AI Overviews and ChatGPT.
In Catalonia, a query like Tradicions de Sant Jordi shows how AI systems can sometimes misidentify the language, often tagging Catalan as Occitan. This discovery was both surprising and revealing, shedding light on broader problems that transcend multilingual spaces.
Consider this: an AI system operating out of Barcelona with a local IP may choose the less prevalent language of Occitan over Catalan, a decision that feels bizarre given Catalonia’s linguistic and geographical context.
This issue isn’t isolated. In January 2023, Google acknowledged downgrading Catalan results in favor of Spanish, which sparked dissatisfaction among users. The subsequent updates improved things somewhat, but the root language-identification errors persist, affecting how AI synthesizes information today.
My journey into this topic has involved documenting AI search variations across Hispanic markets, observing how it often treats diverse Spanish-speaking regions as uniform, ignoring their unique contexts. However, in Catalonia, where geography remains constant, the retrieval patterns unfold in more distinct and educational ways.
For me, multilingual regions expose the foundational defaults in retrieval systems. Here, users can switch languages and observe firsthand how the system reallocates meaning, authority, and even the language of an answer.
The reality is, the same issues will likely emerge in seemingly monolingual markets, manifesting in different ways as AI technology advances.
In February 2025, I watched a captivating display as humanoid robots graced the CCTV Chinese New Year stage. Although their steps were shaky, it was still delightful to witness.
A year later, these robots at the Spring Festival Gala had transformed, executing smooth moves, somersaults, and full kung fu routines. This rapid progression felt like a decade’s worth of technological advancement condensed into one year.
The technological leap wasn’t limited to robots. It raised a crucial question for digital marketers targeting the largest web population: How have China’s search trends evolved recently?
A parallel in the Chinese search landscape
We’re seeing early signs of a major shift. AI hasn’t replaced traditional search engines yet. Instead of a single breakthrough, change comes from consistent, subtle advancements.
New language models frequently emerge, each refined for a specific niche. Tech companies in China are increasingly sharing these developments openly, with players like Baidu integrating advanced models like DeepSeek into their platforms.
To understand the current search behaviors in China, we need to grasp the shift from simple link searches to more reasoning-based approaches and adjust our 2026 SEO strategies accordingly.
The great narrative fallacy: Is web search dead in China?
There’s a persistent narrative in marketing circles that traditional search, especially on Baidu, is obsolete — that everything is happening on platforms like WeChat. But how true is this?
The social supremacy argument
Indeed, China’s web is mobile-first and dominated by super-apps. While social media is pivotal, it’s not the sole avenue for B2C brands aiming to thrive amidst such a vast, versatile environment.
For instance, platforms like Xiaohongshu excel in lifestyle research, while Pinduoduo and Douyin are social commerce powerhouses. Meanwhile, WeChat is indispensable for everyday tasks.
The B2B reality check
For B2B sectors, dismissing Baidu is a mistake. Metrics show ongoing engagement and tangible results from Baidu SEO, often outshining Western counterparts in lead quality and conversion rates.
When B2B professionals seek industrial solutions, they prioritize verified websites over endless scrolling on social media apps, indicating an undying need for structured web searches.
Mapping the 2026 landscape: Intent-based specialization
As someone deeply integrated into the Chinese market, I’ve noticed that users select tools based on intent rather than defaulting to search engines. It’s an everyday occurrence here.
While optimizing for Baidu, others in my circle might be using Pinduoduo for deals or Xiaohongshu for travel plans. The right tool for the right task wins their clicks.
1. Traditional web search: The authority tier
Traditional search continues to dominate B2B and high-authority research areas. Baidu, despite narratives of its decline, remains central to mobile and web searches.
Baidu: Dominates mobile search with a vast user base. Though AI-driven, it remains a key player in web search.
Microsoft Bing: Offers a professional experience for a tech-focused audience.
Haosou (360 Search): Known for its security and enterprise-centric approach.
Sogou: Integrates with WeChat, bridging between app-based and traditional searches.
Google: Despite restrictions, it’s accessed by tech-savvy users via VPN for global insights.
2. Social discovery: The inspiration tier
Here, search turns into discovery. Users are led by interests rather than predefined keywords, making SEO a matter of being on the right social platforms at the right time.
WeChat (Weixin): For brand news and internal communications.
Xiaohongshu (RED): Essential for lifestyle and luxury brand discovery.
Douyin: Offers visual insights into product utility.
Kuaishou: Used predominantly in emerging markets for grassroots content.
Weibo: Ideal for real-time trends and news.
Bilibili: Focus on long-form video content and niche interests.
3. Ecommerce: The transactional tier
While Westerners often end their buying journeys on Amazon, Chinese users tend to both start and finish on the same platform, whether for variety or efficiency.
Taobao / Tmall: The prime destination for diverse product offerings.
JD.com: Favored for electronics and efficient logistics.
Pinduoduo: A leader in group-buy and value-driven purchases.
Douyin Mall: Capitalizes on impulse purchases through engaging content.
Xianyu (Goofish): Supports second-hand markets and niche hobbies.
4. Generative AI (LLMs): The reasoning tier
This emerging layer focuses on “thinking” searches where AI synthesizes data into insights rather than mere lists.
Doubao (ByteDance): Popular for casual queries.
DeepSeek (Domestic): Integrated with WeChat for deep logic queries.
Kimi (Moonshot AI): Specializes in handling lengthy documents.
Qwen (Alibaba): Plays a crucial role in business and coding tasks.
Tencent Yuanbao: Focuses on WeChat content.
Wen Xiaoyan (Baidu): Represents the next stage of Baidu’s AI search capabilities.
5. Hyper-local and logistics: The utility tier
This sector addresses immediate, location-driven demands, prioritizing services that cater to “now” and “near me” needs.
Meituan / Dianping: Leading platforms for food and leisure services.
Amap (Gaode) / Baidu Maps: Vital for navigation and local search optimization.
Ctrip (Trip.com) / Railway 12306: Key for travel and transportation booking.
From mapping to maneuvering: The Baidu specialist’s edge
Optimizing Baidu SEO extends beyond ranking web pages; it’s about mastering search landscape intricacies.
The ‘walled garden’ SERP: A decade of distraction
Focusing solely on Google-style tactics might overlook nuances like Baidu’s ad-heavy SERPs and content positions.
The ad-heavy layout: Ads can dominate substantial SERP real estate.
The Baidu monopoly: Prime organic positions often favor Baidu properties.
The portal giants: High-authority contributors also claim space within results.
Riding the Chinese SERP dragon
In this scenario, relying on long-tail strategies often proves more lucrative than targeting head keywords due to the complex Chinese language and diverse user base.
Whether leveraging platform authority or becoming a trusted contributor, it’s essential to adapt upcoming SEO tactics to sustain visibility.
What is changing in Baidu SEO?
The competition among AI models emphasizes versatility over loyalty, making Baidu SEO a nuanced challenge.
The AI-switching reality
Chinese users frequently shift between AI models, seeking superior intelligence or alternatives when certain models falter. This behavior means SEO must account for broader dynamics.
Brainstorming the wisdom platforms
Understanding the foundational platforms for AI development can greatly boost a brand’s presence in AI-dominated searches.
Tencent is invested in Sogou: Hence, Sogou Baike becomes integral for WeChat-based AI queries.
Bytedance owns Baike.com: Engaging here helps brands appear in Doubao’s results.
The neutral giants: Zhihu sits at the intersection of multiple investments, making it a balanced source for varied AI insights.
The new SEO commandment
SEO is now about optimizing for diverse data sources that fuel AI models, across various ecosystems.
In the B2B realm, Baidu remains central. Yet for ecommerce, branching into Alibaba or Doubao ecosystems will expand visibility across key AI systems.
The 2026 China SEO/GEO blueprint: From keywords to semantic saturation
Anticipating a specific SEO guide for AI like DeepSeek or Doubao misses the evolving landscape’s essence. The need is not for singular-model focus but a diversified approach that shifts with frequently changing user and model preferences.
Optimize for citations and not just clicks
Chinese SEO centers around fact density, aiming for content immediately recognizable by AI as authoritative.
The logic: AIs like Kimi and DeepSeek rank content based on factual reliability.
The tactic: Use clear, concise, data-backed writing, enabling rapid fact verification by AI.
Build an entity moat across wisdom platforms
Given that AI models distill and share intelligence, maintaining consistent brand representation across various platforms is crucial.
The goal: Ensure uniformity in brand presentation across Baidu, Sogou, and Baike.com.
The result: Consensus between AI models establishes your authority.
Leverage information gain
AI in China demonstrates a preference for recent data by about 25% compared to traditional search engines.
The tactic: Present unique, timely insights to stand out amidst common knowledge.
The era of the entity architect
We’ve moved past the initial robotic steps of 2025. In 2026, China’s search landscape is a dynamic entity, requiring an intricate understanding of intent fragmentation.
Despite the dominance of super-apps, the real revelation lies in this fractured landscape. My personal experiences echo this as my wife seeks deals on Pinduoduo, and my colleagues navigate Bing for professional resources. Meanwhile, AI enthusiasts cycle through LLMs for varied answers.
As a Baidu specialist, my role has evolved from targeting websites to designing robust entities. Building for the source, not just the bots, ensures your brand is consistently recognized and trusted, no matter which AI models deliver the solutions.
Imagine your brand becoming the celebrated go-to source, regardless of the search model. That’s the ultimate goal for today’s SEO specialists.
I’ve noticed that AI systems are improving in generating Spanish language content, but they’re not quite grasping the nuances of Spanish markets.
In fact, we often see a familiar trend: over 20 Spanish-speaking nations reduced to a single standard. Spain is typically the default, and Mexico might as well be interchangeable with any other country. The rest get simplified into statistical norms.
The root of this problem is structural, involving dialect defaulting, format contamination, and regulatory hallucination. These issues are more pronounced in a generative search setup where one synthesized response replaces several search results.
This misinterpretation acts as a barrier to visibility. Generative AI seeks clarity, and if my content doesn’t specify its market context, it defaults to an average—leading to missed opportunities and misapplication.
To tackle this, I’ve developed a framework that ensures market context is clear across content, technical indicators, and retrieval systems, so AI systems don’t have to assume.
What is Cultural SEO?
Cultural SEO goes beyond mere multilingual support or localization. Its foundation is firm on locale precision—ensuring the market context is clear in retrieval and generation practices so that your Spanish content is associated with the specific country it was intended for.
Here’s a framework that proves effective when working around Spanish and Latin American markets.
You can’t effectively optimize for a market you aren’t serving. Cultural SEO isn’t an afterthought; it’s the backbone of a strategic decision to genuinely operate within a market, encompassing logistics, customer service, compliance, and product-market alignment.
If you ship from Spain to Mexico with unrealistic delivery times or lack local support, even the best hreflang configuration won’t suffice. Users will abandon such experiences, and as AI learns from these interactions, it will deprioritize similar content.
Speaking the market’s language goes beyond spoken words—it’s about conveying trust, ensuring payment and delivery expectations are met, and adhering to regulatory standards.
Assuming you’re committed to these standards, here are the four pillars: segmentation, transcreation, retrieval constraints, and entity reinforcement. Before applying any framework, ensure this commitment.
Pillar 1: Market Segmentation at the Entity Level
International SEO often considers segmentation as a mere folder structure: /es-es/, /es-mx/, /es-ar/, but that’s merely scratching the surface.
In generative search, the challenge is ensuring the AI associates a page with a specific country like Mexico, and accumulates enough market-specific signals to prefer it over a general alternative. If the architecture simplifies differences, visibility diminishes equally.
Pillar 2: Transcreation, Not Just Translation
Translation is about converting words, while transcreation is about interpreting meaning. Given two pages with 95% similar content, the AI merges them into one representation—defaulting to one perceived as standard. Therefore, differentiating with local examples or unique terminologies is essential.
Pillar 3: Retrieval Constraints
In constructing AI experiences like RAG (Retrieval-Augmented Generation), it’s crucial to establish clear boundaries about what content should be sourced for specific markets to avoid defaulting to “Global Spanish.”
Pillar 4: Market Authority Through Entity Reinforcement
AI models learn from both your site’s content and external perceptions. Thus, building location-specific authority through local media presence, partnerships, and consistent regional knowledge graph reinforcement is vital to establish market-specific authority.
Ultimately, Cultural SEO ensures that content not only serves the market but resonates with it. By embracing these pillars, I can ensure my brand isn’t just another “Spanish” entity but a recognized authority in each targeted market.
This journey isn’t about merely adapting your website but architecting systems to reflexively consider the market’s dynamics from the ground up.
As someone who has been deeply engaged with international SEO strategies, I’ve noticed a significant transformation in 2026. With AI-mediated searches redefining the landscape, the traditional playbook has evolved. Yet, despite these changes, certain strategies remain effective.
For years, international SEO followed a well-trodden path: creating unique URLs for different countries and languages, localizing content, deploying hreflang, and ensuring search engines present the correct version. However, those basics aren’t enough in today’s AI-driven world.
Today, it’s not just about ranking; it’s about how well my content is retrieved, interpreted, and validated globally. Consistent visibility hinges more on these elements than on the traditional methods we’ve relied upon.
The elements that still perform effectively in 2026 are quite fascinating. Market-scoped URLs continue to triumph when they highlight real differences, reflecting true market variations rather than simple translations. For example, legal disclosures, pricing, and regional compliance are crucial.
Local intent, beyond mere language translation, proves critical for content retrieval and retention. AI systems are increasingly adept at understanding when two pages address the same user intent, even across different languages.
Although hreflang tags are still effective within traditional SERPs, their influence is somewhat diminished in AI-mediated environments where market differentiation and data clarity become essential before retrieval.
Understanding how entities are clarified is crucial. AI systems quickly need to ascertain the company’s identity, brands, products, market context, and credibility for robust content consideration.
Local authority signals are vital as well. AI systems now evaluate trust within specific market contexts, emphasizing local expertise and affiliations over global brand authority.
On the flip side, several traditional strategies no longer offer the same value. Basic translation without localization fails to deliver meaningful AI response, with English versions often taking precedence globally.
Indexing alone no longer guarantees visibility. AI retrieval now focuses on selection and prioritization of content with clear, confident disclosures.
Moreover, individual page-centric SEO strategies fall short as AI synthesis works at the level of concepts and entities, not isolated pages.
Uncoordinated publishing can lead to semantic drift, where AI may prioritize the most current or authoritative content, even if it’s from a less strategic market.
In adjusting to these changes, companies must now manage international SEO as a complex system focused on trust, relevance, and alignment across global markets, rather than just a straightforward localization task.
I’m excited to share that Semify, a leading white-label digital marketing platform, has acquired Dragon Metrics, a prominent international SEO and AI reporting provider based in Hong Kong. This acquisition marks a significant enhancement in our reporting capabilities and AI optimization tools as we adapt to a shifting search landscape increasingly focused on AI.
Why this matters to you. If you’re a Dragon Metrics customer, you can continue to expect the same great service, along with more frequent product updates. According to co-founder Simon Lesser, who shared on LinkedIn, the platform will still operate as an independent brand retaining its existing contacts and product experience. Additionally, you’ll now benefit from Semify’s expanding AI optimization strategies and the potential for future software integrations.
Details of the acquisition. On December 8th, Semify announced the acquisition of Dragon Metrics:
Semify was founded in 2008 and operates as a U.S.-based white-label digital marketing platform.
Dragon Metrics was founded in 2011 and supports multinational brands and agencies in over 50 countries, especially in regions where Google isn’t the main search engine, like China, Korea, and Japan.
This acquisition provides Semify with an enterprise-grade reporting system and comprehensive global data coverage as we intensify our focus on AI-driven metrics.
The finer points. Simon Lesser will take on the role of chief product officer at Semify, steering our AI optimization product strategy.
The Dragon Metrics engineering team will join forces with Semify’s team under the leadership of CTO Brian Sappey.
Our resellers are set to experience improved reporting capabilities via Dragon Metrics accounts, with more integrated solutions on the horizon.
Dragon Metrics customers will remain on their distinguished platform but with the advantage of increased engineering support.
White-label fulfillment will continue to be exclusive to approved agencies, aligning with our existing reseller model.
