As someone delving into the world of GEO in biotech, I find the field both new and challenging. Many of us in this niche are still refining our approaches, and in biotech, that
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Author: shivamcrushpressai
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Top Marine GEO Agencies of 2026: Leading the Industry
In my latest exploration, I dived deep into the world of marine and maritime marketing agencies. I closely examined 29 firms dedicated to serving sectors like recreational boating, commercial maritime, yacht brokerages, marine technology, marina operations, and offshore services. What I found was enlightening. Each agency was rigorously evaluated based on five key factors that I consider essential.
The criteria included the innovative AI Visibility Score, where I looked at how effectively these agencies could place their marine clients in the limelight of platforms like ChatGPT, Perplexity, Claude, and Gemini. It wasn’t just about having a presence; it was about being recognized. I also considered the prestige of their notable clients, coupled with the leadership experience that tipped the scale in their favor.
Add to that the customer review scores sourced from trustworthy platforms and the number of media references that showed their industry influence, and you’d get a clear view of what makes an agency stand out.
Allow me to present the seven highest-scoring agencies, each a powerhouse in its own right, capable of shaping the future of maritime marketing.
The Top Marine GEO Agencies of 2026
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Navigating Revenue Integrity: Insights from Enjoin’s Sarah Laird
In my conversation with Sarah Laird, we explored the dynamic collaboration between physician expertise and technology in fostering enduring trust within healthcare organizations.
Enjoin stands out as the premier physician-directed, tech-driven revenue integrity platform in the U.S., boasting an impressive 97% client retention rate and recovering over $2 billion for health systems in the last four decades. At First Page Sage, we partner with trailblazers in complex B2B spaces, and few areas are as high-stakes as the healthcare revenue cycle. I had the pleasure of speaking with Sarah Laird, Enjoin’s Senior Director of Staffing and Advisory, to learn how their models integrate clinical judgment and technology to safeguard revenue, enhance internal capacities, and solidify trust within the organizations they support.
Health systems are under enormous financial strain, and it’s crucial to understand where revenue integrity fits into the discussions CFOs and revenue cycle leaders engage in. According to Sarah, revenue integrity is now a strategic leadership priority, crucially placed at the convergence of financial performance, compliance, and operational efficiency. With growing margin pressures, payer scrutiny, and audit risks, these leaders are moving beyond traditional metrics to focus on whether documentation, coding, and billing genuinely represent the provided care.
Revenue integrity is established well before claims are billed. When clinical documentation, coding, CDI, and revenue cycle teams collaborate effectively, organizations can better reduce denials, heighten audit readiness, and secure reimbursements that are accurate, defensible, and compliant. It’s no longer just a function of the revenue cycle but a comprehensive effort that demands shared accountability across clinical, operational, and financial teams.
Organizations observing a proactive approach to compliant revenue integrity tend to see stronger outcomes, as evidenced by Enjoin clients who experience a 900% return on investment and face 17 times fewer denied claims through pre-bill chart reviews.
Enjoin’s physician-directed model highlights the essential role of clinical judgment in CDI and revenue cycle tasks, even in an era abundant with advanced technology. Sarah explains that the magic lies in the synergy between technology and human expertise. While technology can facilitate case reviews, identify patterns, and scale operations, physician-led reviews deliver the clinical validation, education, and defensibility needed for compliant revenue integrity and to endure payer scrutiny.
Effective revenue integrity hinges on ensuring the clinical record, coded record, and financial outcome align with the care provided. Physician advisors bring a unique vantage point, balancing clinical realities with documentation standards to ensure accuracy in coding, quality reporting, and reimbursement.
Enjoin’s pre-bill chart review process adds a crucial layer of validation, enabling organizations to evaluate whether the clinical record, coded record, and resulting DRG are harmonized and documented correctly. It identifies broader trends, educational opportunities, and process enhancements that might go unnoticed in individual case reviews.
By merging physician-led clinical proficiency with EnFORM+ technology, health systems expand visibility across discharges, prioritize valuable opportunities, and assure that reimbursements are accurate, defensible, and compliant before submission.
Sustainable revenue integrity is more than just individual chart reviews; it involves translating findings into education, process improvement, and shared accountability across the organization. Enjoin aids health systems in building stronger internal CDI and coding capabilities by helping them comprehend trends and root causes behind documentation and coding opportunities, thus facilitating lasting improvements.
Enjoin’s partnerships focus not only on financial recovery but on bolstering the entire revenue integrity ecosystem—encompassing documentation quality, coding accuracy, denial prevention, audit readiness, physician engagement, and governance. The right partnership does more than identify opportunities; it becomes integral to an organization’s strategy for ensuring clinical accuracy in financial outcomes.
To learn more about Enjoin’s physician-directed revenue integrity partnerships, visit enjoincdi.com.
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How AI User Prompts Impact SEO Strategies Today
I’ve often wondered how people are truly interacting with AI technology and what those interactions mean for our digital strategies. As I dive into recent survey data, it’s clear that real-world users are blending short queries with personal context, altering how brands achieve visibility in AI-driven searches.
Initially, I was surprised to learn that most people don’t use AI in the manner many Generative Engine Optimization (GEO) discussions suggest. Through surveys conducted by Stella Rising, where I’m the VP of SEO, we discovered that many AI prompts closely resemble traditional search engine queries.
For instance, in a beauty-focused study from August 2025 and a general study from January 2026, most prompts were succinct and keyword-driven, much like a Google search. However, many users are now providing AI systems with personal details, such as location and preferences, creating a deeper level of personalization.
Based on these findings, it’s evident that GEO strategies need to embrace this dual approach: accommodating classic keyword searches while optimizing for prompts enriched with personal context. This challenge presents a significant opportunity for brands willing to navigate this new landscape.
A lot of people are still typing like it’s 2008
A significant revelation from the surveys is that typical AI users still submit minimal inputs, hoping for optimal results.
Notably, our January general-audience study indicated:
- Two-thirds of users wrote prompts with 15 words or less.
- Only a small faction, about 12%, crafted what might be considered a comprehensive AI prompt.
- Most framed their questions while very few issued direct commands.
When I replicated a basic scenario — asking for a shoe recommendation — the average response consisted of eight words. Real entries included queries like:
- “Shoes nearby”
- “Tennis shoes”
- “Nike”
- “Ladies tennis shoes size 7 near me”
- “Best price for hiking shoes”
These align closely with findings from Semrush’s clickstream data, showing that the average prompt ranges between 4.2 and 8.7 words, paralleling standard Google queries. Structured, detailed prompts often surface in tasks beyond simple searches, like coding or content creation.
The shift between the two surveys
In the beauty-focused August 2025 survey, nearly half the prompts were firm, SEO-keyword-shaped. However, by January 2026, such prompts reduced to about 30%, with richer context becoming more prevalent.
Key observations included:
- Nearly a quarter incorporated the term “best,” highlighting an opportunity in “best [category]” visibility.
- A noticeable percentage mentioned budget or price, pointing to financially mindful consumers.
- “Near me” remained a common phrase, adapted from Google to AI interactions.
- A notable share included personal attributes, reinforcing the importance of personal context in queries.
However, the varying audiences surveyed offer caution. The 2025 beauty panel represented a unique demographic, while the 2026 group was more general and transactional, showcasing more complex query evolution.
The user embedding layer is where this gets interesting
The data revealing that 32% of users incorporate personal context into their prompts is significant. This includes details like job roles or life scenarios that traditional search queries do not capture. Real-world queries from users might include:
- “What shoes are ideal for standing all day at work?”
- “Find affordable running shoes on Amazon; size men’s 10.”
- “Suggest trendy, comfy women’s shoes, size 8 wide, under $120.”
The last example incorporates several layers of identity and specifics, which typical search engines never explicitly addressed. The embedding layer fuels AI’s ability to ‘know’ its user, leveraging past interactions to tailor responses, and it’s a game-changer for brand visibility.
Brands need to recognize that purchase-driving prompts often diverge from those seen in search engine results pages (SERPs). Real prompts hold significant buying influence and highlight the importance of context-rich brand mentions within AI interactions.
Where synthetic prompts fit — and where they don’t
Constructing synthetic personas helps test AI models’ representation of different user traits. However, synthetic prompts frequently miss the nuanced, ongoing dialogue a real user shares with AI tools. These personas can illuminate potential brand-user interactions but shouldn’t be the sole basis for measuring success in AI visibility.
Instead, complement synthetic prompts with insights from real user interactions for a holistic view. Pull real-world data from customer inquiries, support tickets, and search patterns to gauge true user engagement with your brand.
What to actually track
The current dynamics in AI search query patterns prompt us to reconsider our tracking strategies. With retrieval rates soaring, traditional SEO keywords are far from obsolete in AI contexts.
Yet, it’s crucial to focus tracking efforts wisely. Generic terms or single-brand queries may not yield insightful visibility information. Here’s how I recommend setting up an effective tracking framework:
- Use synthetic-persona prompts to cater to user embedding layers.
- Gather a set of real prompts from various data inputs for short, retrieval-invoking prompts.
- Maintain a qualitative set of context-heavy prompts to ensure content relevance and thoroughness.
What the broader data tells us about AI search
Further insights from January 2026 underscore why these prompt configurations matter in AI search:
Users increasingly trust AI recommendations
Approximately 68% of respondents trust AI recommendations more than Google’s, highlighting a trust transition driven by personalization and a lack of advertising clutter.
AI search is becoming a daily habit
Half of active AI users engage with these tools daily, gradually shifting dependency from Google to AI for common tasks. This shift signifies a change in how search habits are being shaped by AI convenience.
Citations still drive traffic
A substantial number of users still click on citations, validating that mentions within an AI context act as a gateway rather than an endpoint, showing the importance of monitoring and optimizing referral traffic through AI channels.
Voice may finally be having its moment
Voice interactions are finally seeing substantial usage, suggesting the long-predicted rise in voice-activated search is materializing, reinforced by the data from Ahrefs indicating visible shifts in clickthrough patterns.
In summary, AI search is taking form as a more personalized, interactive endeavor. It blends traditional intent with modern layers of user context, posing new demands and opportunities for content optimization. SEO and GEO strategies need to align closely with these evolving practices to maintain competitive edge.
What changes — and what doesn’t
As an SEO strategist, here are my top three recommendations for leveraging these insights:
- Revamp Your Prompt-Tracking Strategy: Blend synthetic prompts with real user inputs for a fuller understanding of AI visibility.
- Align Content with User Embeddings: Identify key user personas and ensure your content addresses their specific needs.
- Continue SEO-Keyword Optimizations: Traditional searches still play a crucial role, especially with high retrieval rates in play.
It’s vital to recognize that while AI evolves, many users still engage reminiscent of Google’s era, albeit within a platform more attuned to their specific contexts. This understanding guides where our optimization efforts must focus, staying attuned to changing user interactions and preferences.
Methodology
The studies referenced were spearheaded by Stella Rising. You can delve into them further in the report titled, “New Data: How Consumers Use LLMs for Search in 2026 (And What It Means for GEO).”
The August 2025 study surveyed 178 members of Stella’s community specializing in beauty, while the January 2026 survey covered a broader user base of 524 active users with some margin of error. These insights offer a directional lens into the broader adoption and interaction patterns within the AI space.
Inspired by this post on Search Engine Land.
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Transform SEO Reports into Actionable Insights
When I work on SEO reports, I know they often include comprehensive research. This might involve keyword data, technical analysis, competitor insights, content gaps, and actionable recommendations. Yet, the challenge arises when stakeholders finish reviewing the report but remain unsure about the immediate next steps.
Take, for example, a report suggesting improvements in internal linking. It typically fails to pinpoint which specific pages need links, the team responsible for these updates, the timeline for execution, or the expected outcomes. Similarly, identifying a crawl issue without outlining its priority compared to fixing existing content gaps can leave teams confused.
This is a critical juncture where many SEO reports lose their impact. The analysis may be accurate, but the path forward often lacks clarity.
What I strive for in a strong SEO report is to guide readers into understanding the present priorities, their importance to business objectives, and the immediate actions needed. This reduces the need for further interpretation before implementation can commence.
Research Is Useful, But It’s Not the Final Output
The SEO activities I engage in, such as keyword research, SERP analysis, technical crawls, competitor reviews, and content audits unearth many hidden opportunities and risks. However, it’s crucial that these inputs don’t overshadow the final report.
What stakeholders truly need from me are the conclusions derived from this research. They need clarity on which findings are impactful, which improvements can be deferred, and which actions should be prioritized.
As an illustration, while identifying 300 pages with missing meta descriptions, the report should clarify the significance of those pages. If the descriptions are of low-value archive pages, they might not require immediate attention. However, missing descriptions on high-intent service pages demand prompt action.
The same principle applies to keyword gaps; a useful report pinpoints high-opportunity keywords aligned with commercial intent and informs stakeholders why certain issues deserve immediate action.
Tailor Reports to the Stakeholder
In my experience, SEO reports often fail to incite action because they treat all stakeholders the same. Each stakeholder, whether a CEO, marketing lead, developer, or content manager, requires different levels of detail, and presenting information in their context is critical.
For executives, I focus on business opportunities, risks, resources, and expected impacts, while marketing leads need to understand how SEO efforts tie into demand generation and campaign strategy.
Developers require a clear technical path, and content teams need page-specific action plans. My goal is to present findings in a way that each stakeholder can easily act upon.
What a Decision-Ready SEO Report Should Show
In crafting a useful SEO report, I aim to address a concise set of questions that, while varying across stakeholders, consistently serve the purpose of guiding the next steps.
By starting with clearly identifying where SEO can create business value, pinpointing constraints, and defining prioritized actions, I ensure the report supports effective decision-making.
Finally, outlining how progress will be measured ensures stakeholders remain aligned and motivated as the project unfolds.
Turn Every Finding into a Clear Next Step
All significant findings in an SEO report should be immediately actionable. By answering what was found, why it matters, and what action should follow, I enable stakeholders to move forward confidently.
For instance, a discovery of high-traffic pages lacking links to commercial pages should lead to specific steps involving content updates and measurement, ensuring progress is tracked and objectives are met.
What to Cut from SEO Reports
To make SEO reports concise and effective, I exclude unnecessary data such as tool screenshots and extensive keyword exports. While supporting materials are valuable, the main report should focus on clarity and priority.
I also shorten methodologies unless essential for building trust or understanding. Keeping the report streamlined ensures stakeholders are not overwhelmed with information that doesn’t aid in decision-making.
The Best SEO Reports Make the Next Step Obvious
Ultimately, my objective with SEO reporting is to minimize uncertainty. After reviewing the report, stakeholders should clearly understand what requires attention and the direction to proceed.
Although SEO lacks absolute prediction, each recommendation should outline expected impacts and the signals used to measure progress, turning findings into active projects that propel the business forward.
Inspired by this post on Search Engine Land.
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Google Held Accountable for False AI Claims in Germany
Recently, a German court ruling caught my attention because it asserts that Google can be directly liable for false claims made in their AI Overviews. The Regional Court of Munich’s decision highlights a significant shift, considering AI-generated summaries as Google’s own content rather than just protected search results.
This ruling emerged from a case where AI Overviews mistakenly linked two Munich publishers to scams and dubious practices, despite the linked pages containing no such evidence, as reported by The Decoder.
AI Overviews are not just search tools. According to the court, these Overviews go beyond merely assisting users in finding third-party content. They actually process and present information in their own distinctive manner.
What struck me was the court’s findings that the AI Overview allegedly made standalone accusations regarding questionable business practices, which were not substantiated by the linked sources. Because Google crafts and controls these features and their algorithms, the court ruled these statements to be Google’s own content.
Traditional search protections didn’t apply here. Google argued that they should be protected by German case law, which generally shields search engines as indirect infringers. However, the court disagreed, emphasizing that AI Overviews are distinct as they generate new statements from multiple sources.
The court also dismissed Google’s argument that users could verify claims by reviewing linked content. They highlighted that AI Overviews offer claims that stand as complete answers without needing verification.
Why does this matter to me? The court’s stance implies that AI Overviews aren’t neutral links. If they issue incorrect claims about a company, Google may bear direct responsibility for these words.
Mismatched connections and misinformation. The court determined that misinformation resulted from AI conflating data about other entities with that concerning the publishers.
Given that the contested claims weren’t present on the linked sites, the publishers lacked a clear third party to target legally, should Google be considered only as an intermediary.
Interestingly, the court insisted that Google could compare AI-generated content against primary sources, at least in analogous situations.
Action required from Google. The injunction demands that Google refrains from repeating the disputed claims, which include allegations of scams and nonexistent business practices.
Furthermore, Google is instructed to bear 80% of the legal costs, while each publisher covers 10%. Despite Google’s lack of a cease-and-desist declaration with a penalty clause, the potential for repeat violations was noted, emphasizing the importance of this ruling for future similar claims.
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Mastering Prompt Tracking: Strategies for Accurate AI Insights
I’ve come to realize that prompt tracking is often misunderstood as mere noise, but it’s actually a golden opportunity to refine AI interactions through a structured approach.
AI responses can be unpredictable. However, by utilizing repeated runs, establishing fixed sampling rules, and calculating confidence intervals, we can transform variance into a trustworthy metric.
By embarking on this journey with me, you’ll soon be equipped to create a reliable AI tracking system.
You’re already ahead if you’ve embraced persona-based prompt design as discussed in Synthetic Personas for Better Prompt Tracking.
For those immersed in AI SEO strategies, understanding the true trajectory of your efforts over the noise is crucial. Explore more with How Much Can We Influence AI Responses.
While many have dismissed prompt tracking due to its variability, I’ve discovered that it mirrors the unpredictability seen in weather forecasts and credit scoring, which are still meticulously tracked.
Reflecting on keyword tracking’s evolution, I see a parallel path for prompt tracking, which requires adapting its methodology to account for the numerous platforms now at play.
At pivotal industry events, experts speak of a shift from single search queries to a conversational model, emphasizing the changing landscape we must adapt to.
The shortcomings of current prompt-tracking tools are evident in their lack of innovation, yet I believe we can rise above with a more strategic approach.
Although single-turn prompts provide limited insight, constructing full conversational sequences reveals persistence, a vital metric often overlooked.
Imagine tracking a B2B SaaS CRM journey through defined stages, extending prompts to capture decision-making across multiple touchpoints to truly gauge influence.
HubSpot’s visibility across platforms like ChatGPT and Perplexity illustrates the nuanced understanding needed to strategize investments in brand-centric content.
The future of prompt tracking resembles opinion polling, employing systematic and repeatable methodologies to extract meaningful data amidst variability.
This piece first appeared on the author’s website and is shared with permission here.
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Publishers Demand Halt in AI Data Collection by Common Crawl
Could AI be losing a crucial source of its training data? As a major shift looms, significant publishers are urging Common Crawl to pause its collection and distribution of their content for AI training.
Digital Content Next (DCN) has sent a cease-and-desist letter to the Common Crawl Foundation, asking them to stop scraping and sharing protected publisher content.
Representing leading digital publishers like the AP, the New York Times, NBC Universal, Bloomberg, NPR, and Fox, DCN is also insisting that Common Crawl remove its members’ content, including paywalled and subscriber-only news articles, from its datasets.
Concerns Over Opt-Outs: Questions arise regarding Common Crawl’s adherence to publisher opt-out requests. Specifically, DCN’s lawyers are scrutinizing whether previous statements about compliance—often citing technical costs and delays—were perhaps misleading.
- The registry maintained by Common Crawl does list sites opting out, including several prominent news organizations.
Claims of Infringement: DCN firmly holds that copyright isn’t an opt-out system. They allege Common Crawl has been “flagrantly infringing” on publisher copyrights by distributing protected content without authorization or compensation.
- The group further critiques how Common Crawl shares this content with AI developers.
- DCN’s CEO, Jason Kint, signifies this legal action is a stance against the notion that online content is available for unrestricted collection, storage, and reuse.
Common Crawl’s Defense: Rich Skrenta, the Executive Director, denies allegations of bypassing paywalls and misleading publishers. He references a prompt and technical response to remove previously crawled content upon request.
- “Our removal process aligns with our dataset’s technical framework,” Skrenta explains.
Importance of This Battle: The outcome of this dispute could drastically influence the scope of publisher content that AI search engines use without explicit permission. Should there be heightened consent requirements, licensed sources may prevail, reducing reliance on openly available web content.
The High Stakes of AI Training: Established in 2008, Common Crawl has amassed billions of webpages to form a free public repository, a vital tool for training AI models. Notably, The New York Times’ lawsuit against OpenAI in 2023 cited that Common Crawl comprised 60% of GPT-3’s training data, as reported by Press Gazette.
- A 2024 Mozilla Foundation paper found generative AI would scarcely exist today without Common Crawl.
- Common Crawl’s ongoing efforts to create AI crawling standards indicate a willingness to adapt, yet DCN calls for decisive action—fully halting the scraping of protected content.
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Unlocking AI Search and Ads: Insights from Ginny Marvin
After Google Marketing Live, I’m still left with a lot of questions, and I’m sure I’m not the only one. Thankfully, Ginny Marvin, Google Ads Liaison, joined a comprehensive Q&A with Julie Bacchini and the PPC Chat community to tackle big topics like AI Max, AI Search ads, first-party data, and more.
The discussion was enlightening, bringing clarity to AI Search eligibility, reporting challenges, and Google’s increasing focus on data quality.
AI Max: Not a Must-Have for AI Search Ads
A major revelation was that AI Max isn’t required for participating in AI-driven search experiences. This surprised many of us, as we’d assumed AI Max was crucial for tapping into Google’s AI search surfaces.
Ginny highlighted that campaigns with broad match keywords are still eligible for AI Overviews and AI Mode. Even so, AI Max does broaden possibilities by treating phrase and exact match keywords with broad match behavior and enabling keywordless matching.
This means there are still multiple avenues available for us to access AI Search inventory.
AI Search Reporting is Still on Hold
Many of us were eagerly hoping for detailed reporting on AI-powered search results. However, Ginny confirmed that current ads in AI Overviews and AI Mode are reported like other top-of-page ads, with no distinct breakdown. Google’s still figuring out what these reports should eventually look like.
This leaves us with limited insights into how much AI-driven traffic and performance we’re actually seeing.
Google’s AI Brief: A New Layer of Control
A significant part of the discussion circled around AI Brief, set to become the control layer for AI Max campaigns. Advertisers like me will soon be able to provide specific guidance such as “never mention prices” or define target audiences, message themes, and search intents to prioritize.
The rollout will start with English Search campaigns and eventually spread to Performance Max and Shopping campaigns.
For those of us worried about automation reducing our control, AI Brief offers a promising solution.
The Core of Effective Advertising: First-party Data
If there’s anything I walked away with, it’s the emphasis on data quality, particularly first-party data. Google’s focus is what they call “Data Strength,” and tools like Enhanced Conversions and Google Tag Gateway are pivotal.
It’s clear: better data enhances AI performance and outcomes.
Exploring New Metrics: Qualified Future Conversions
Another fascinating development is Qualified Future Conversions (QFC). This metric estimates potential conversions occurring within 180 days post-ad interaction. It’s especially useful if you’re in B2B or lead generation sectors with lengthy sales cycles.
Currently, it’s in testing with select advertisers, and I’m keen to see it roll out further later this year.
Key Areas of Excitement at Google
When asked about her personal highlights from GML, Ginny shared three areas: the new ad formats for AI Search, measurement innovations like QFC, and YouTube Creator Partnerships.
This truly illustrates where Google is investing: AI discovery, advanced measurement, and creator-driven advertising.
Putting It All Together
This Q&A has definitely filled in some gaps left by the GML presentations. I’ve realized that broad match terms still provide a pathway to AI Search, AI-specific reporting is evolving, and Google’s vision continues to be centered on automation, powered by first-party data.
Most importantly, it’s about balancing automation with new controls like AI Brief to shape Google’s AI systems to our advantage.
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Discover How Many Websites Use Each Schema Type with Schema.org
Have you ever been curious about how many sites use a specific type of structured data? Now, you have the chance to find out.
I recently discovered that Schema.org is now sharing aggregated usage statistics for its terms across the public web. This means you can see exactly how many domains are using a particular schema or structured data element.
According to a Schema.org announcement, they are excited to offer a new dataset providing these statistics. Updated monthly, the data is aggregated at the domain level and categorized into popularity range buckets, which helps to filter daily noise while emphasizing meaningful adoption trends for researchers and tool developers.
What’s the appearance like? Take a look at a snapshot of two Schema.org pages, featuring author schema and event schema, displaying the usage statistics prominently at the top:
Delving deeper into the data. Schema.org has further detailed the usage statistics. Here’s a brief overview:
- Schema.org term frequencies are evaluated within Google’s public web crawling infrastructure. The aggregation occurs at the domain level (e.g., example.com), not page by page. If you use the same term on 100 pages, it still only counts as one domain using it.
- Rather than displaying exact numbers, which can fluctuate daily, websites are categorized into range buckets (e.g., “10K – 100K” domains). This approach stabilizes the data and respects website privacy.
- The raw data files can be accessed on GitHub under the Google Public Stats dataset. Both JSON and CSV formats are available, alongside a JSON summary format offering aggregated bucket distributions, all updated monthly.
- Term Type: Specifies whether the term is a
Type(e.g., “Person” or “Event”) or aProperty(e.g., “price” or “telephone”). - URI: Shows the official URI of the term, such as
http://schema.org/Person. - Domain Count Bucket: The range of unique domains utilizing the term, for instance,
100K - 1Mdomains.
If you’re interested, here’s a peek at GitHub:
Why is this important? Well, besides my love for data, understanding the popularity of a specific schema element might just convince your development team to incorporate that schema code on your site.
Inspired by this post on Search Engine Land.