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Thursday, September 10, 2026

12 articles

Google Adds Post View Counts To Business Profiles
Search Engine Journal·Sep 10, 2026
Important

Google Adds Post View Counts To Business Profiles

Key Takeaways

  • Post view counts now visible in Business Profile dashboard for all posts from the past 18 months
  • Metrics combine views from both Google Search and Google Maps
  • Data shows which post types generate engagement without requiring third-party analytics tools
  • API access to post view count data is not yet available

Why it matters: Local SEO professionals can now measure Business Profile post performance directly within Google's native dashboard, helping them optimize content strategy and justify posting efforts to clients without external tools. However, the lack of API access limits automation and integration with existing analytics workflows.

Business ProfilesLocal SEOGoogle AnalyticsPost Metrics
Is Your Local SEO Strategy Ready For Google’s Next AI Updates? [Webinar]
Search Engine Journal·Sep 10, 2026
General

Is Your Local SEO Strategy Ready For Google’s Next AI Updates? [Webinar]

Key Takeaways

  • The webinar focuses on how Google's next AI Search updates will change local discovery mechanisms
  • Five specific strategy fixes are promised to help local businesses get recommended and booked in AI answers
  • The content targets local SEO professionals managing multiple locations competing for visibility
  • The webinar is hosted by Search Engine Journal staff
  • Registration is available for the upcoming webinar session

Why it matters: Local SEO professionals need to understand how AI Search changes will affect how customers discover and book local businesses. The five strategy fixes could directly impact visibility and conversion for multi-location businesses competing in AI-driven local search results.

Local SEOAI SearchGoogle UpdatesWebinar
Everyone Is Quoting The Same Number And Getting Different Answers
Search Engine Journal·Sep 10, 2026
Good to Know

Everyone Is Quoting The Same Number And Getting Different Answers

Key Takeaways

  • Anthropic's crawl-to-refer ratio has been reported as seven different values by various publishers, all citing Cloudflare as the source
  • The reported ratios range from 2,237:1 to 70,900:1, a spread of roughly 30x, published within a 13-month window
  • Two reports claiming the same publication month differ by approximately a factor of 17, suggesting methodology or interpretation differences
  • The article emphasizes that conflicting data doesn't necessarily mean anyone lied—different calculation methods or data snapshots can produce legitimately different results from the same source
  • This highlights the importance of understanding how metrics are calculated and what assumptions underlie published figures in AI search reporting

Why it matters: When evaluating AI crawler impact and traffic potential from AI platforms, practitioners need to understand that published metrics from the same source can vary dramatically based on methodology. Blindly citing a single crawl-to-refer ratio without understanding how it was calculated can lead to incorrect assumptions about traffic opportunity from AI sources like Anthropic.

AI CrawlersData InterpretationAnthropicMetrics Methodology
How Do I Keep Control As Platforms Automate My Account? – Ask A PPC
Search Engine Journal·Sep 10, 2026
Good to Know

How Do I Keep Control As Platforms Automate My Account? – Ask A PPC

Key Takeaways

  • Use transparent reporting to track and measure automated campaign performance against defined KPIs
  • Implement brand-safe creative guardrails to prevent automated systems from generating off-brand or inappropriate ads
  • Structure campaigns strategically to guide automation while preserving control over key performance levers
  • Monitor AI-driven bidding and creative decisions to ensure they align with business objectives
  • Balance automation benefits with human oversight to catch issues before they impact performance

Why it matters: As Google and Microsoft push Performance Max and AI Max as default campaign types, PPC managers need practical frameworks to prevent automation from running unchecked. Establishing guardrails and measurement systems now protects account performance and brand safety while platforms increasingly delegate decisions to AI.

Performance MaxAI MaxCampaign AutomationPPC ManagementBrand Safety
YouTube Gives You Feedback On Shorts Before Publishing
Search Engine Journal·Sep 10, 2026
Good to Know

YouTube Gives You Feedback On Shorts Before Publishing

Key Takeaways

  • Get Feedback reviews three specific elements: hook, pacing, and visuals before a Short goes live
  • The tool is now available to U.S. creators on mobile devices
  • Feedback is optional and the tool does not edit or modify the video itself
  • This is an expansion of an existing feature, not a new launch

Why it matters: YouTube Shorts creators now have pre-publish quality feedback to optimize engagement metrics before going live, which could improve initial performance and reduce the need for re-uploads. For content marketers and video strategists, this is a free optimization checkpoint that may influence how Shorts perform in YouTube's recommendation algorithm.

YouTube ShortsCreator ToolsVideo OptimizationContent Performance
Google Launches Meridian GeoX Globally
Search Engine Journal·Sep 10, 2026
Important

Google Launches Meridian GeoX Globally

Key Takeaways

  • Meridian GeoX enables marketers to run geo-based experiments to measure campaign incrementality and causal impact
  • The tool integrates incrementality results directly into marketing mix modeling workflows
  • Meridian is Google's open-source marketing mix modeling platform receiving updates focused on causal measurement
  • The global launch expands access beyond beta testers to all eligible marketers
  • GeoX allows measurement of true campaign impact by isolating geographic test and control groups

Why it matters: Marketers can now measure true campaign incrementality and causal impact at scale using geo experiments, moving beyond correlation-based attribution to understand what revenue or conversions are actually driven by their campaigns. This is critical for budget allocation decisions and proving marketing ROI in a privacy-first, cookieless environment.

Marketing Mix ModelingIncrementality MeasurementMeridian GeoXCausal MeasurementGoogle Analytics
Google Expands Data Manager And Adds Uplift Measurement
Search Engine Journal·Sep 10, 2026
Important

Google Expands Data Manager And Adds Uplift Measurement

Key Takeaways

  • Data Manager is now available across both GA and DV360 platforms for unified first-party data management
  • New Data Strength Uplift Metric allows advertisers to measure how first-party data impacts campaign effectiveness
  • The expansion enables better integration between analytics and advertising platforms for data-driven decision making
  • First-party data measurement capabilities are now more accessible to advertisers using Google's ecosystem

Why it matters: For PPC and digital marketing professionals, this expansion makes it easier to leverage first-party data across Google's advertising and analytics platforms, and the new uplift metric provides concrete measurement of first-party data ROI—critical as third-party cookies phase out and first-party data becomes increasingly valuable for targeting and optimization.

Google Data ManagerFirst-Party DataUplift MeasurementGA IntegrationDV360
How Local Businesses Can Build Visibility In AI Search
Search Engine Journal·Sep 10, 2026
Good to Know

How Local Businesses Can Build Visibility In AI Search

Key Takeaways

  • Accurate and up-to-date business listings are foundational for AI search visibility
  • Fresh customer reviews signal relevance and trustworthiness to AI systems
  • Broader brand mentions across multiple web sources improve AI visibility beyond traditional local SEO
  • Coordinated brand activity across platforms strengthens local business presence in AI search
  • AI search visibility for local businesses requires a multi-signal approach, not just traditional local SEO tactics

Why it matters: Local businesses need to adapt their visibility strategies as AI search becomes more prominent. The multi-signal approach outlined—listings, reviews, mentions, and coordinated activity—differs from traditional local SEO and requires practitioners to expand their optimization focus beyond Google Business Profile and local citations alone.

Local SEOAI SearchBusiness VisibilityLocal Listings
Google DeepMind Develops New AI Search Ranking Model
Search Engine Journal·Sep 10, 2026
Good to Know

Google DeepMind Develops New AI Search Ranking Model

Key Takeaways

  • Google DeepMind created a new AI model called Autoregressive Ranking
  • The system is designed to overcome limitations in current ranking approaches
  • The technology is positioned as a potential advancement in how search results are ranked

Why it matters: If Google deploys this technology in production search, it could fundamentally change how documents are ranked and surfaced, affecting SEO strategies and content visibility across the board. However, without confirmation of deployment plans or timeline, the practical impact remains speculative.

Google DeepMindAI RankingSearch AlgorithmAutoregressive Ranking
How Freshpet Earned AI’s Trust: A GEO & AI Visibility Playbook
Search Engine Journal·Sep 10, 2026
Good to Know

How Freshpet Earned AI’s Trust: A GEO & AI Visibility Playbook

Key Takeaways

  • Strong SEO performance and brand recognition do not automatically generate AI citations; AI visibility requires a distinct strategy.
  • Content must be written for humans while remaining machine-parseable as standalone passages that LLMs can quote directly.
  • AI visibility audits should start with representative prompts tested across major LLMs, then prioritize gaps closest to conversion.
  • Technical foundations matter: crawler access, JavaScript rendering, page speed, clean HTML, and relevant schema all affect AI discoverability.
  • Community conversations reveal user questions and concerns worth addressing, even when direct brand participation in those spaces isn't appropriate.

Why it matters: As AI-generated answers increasingly replace traditional search results, brands can no longer rely on Google rankings alone to drive visibility. Practitioners need a separate AI visibility strategy that addresses how LLMs discover, parse, and cite content—and this case study provides a tested framework for auditing and improving that visibility.

AI VisibilityContent StrategyAI OverviewsTechnical SEOCitation Strategy
Le Monde Says AI Overviews Haven’t Hurt Its Audience So Far
Search Engine Journal·Sep 10, 2026
Good to Know

Le Monde Says AI Overviews Haven’t Hurt Its Audience So Far

Key Takeaways

  • Le Monde has not seen a sudden audience drop following AI Overviews' France launch
  • App traffic and subscriber growth are complicating the broader traffic picture for the publisher
  • APIG, which filed an August complaint about AI Overviews, also reports no massive impact in early reports
  • AI summaries may function as teasers that drive readers to full articles rather than replacing them

Why it matters: Publishers and SEOs tracking AI Overviews' real-world impact on traffic have been waiting for concrete data from major news outlets. Le Monde's report suggests the feature may not be the traffic killer some feared, though the complexity of measuring impact across app, web, and subscription channels means the full picture remains unclear.

AI OverviewsPublisher ImpactFranceTraffic Data
5 AI Models, 4 Signals: What 120K Mentions Reveal About Multi-Location SEO
Search Engine Journal·Sep 10, 2026
Good to Know

5 AI Models, 4 Signals: What 120K Mentions Reveal About Multi-Location SEO

Key Takeaways

  • Analysis covered 3,793 locations and tracked mentions across ChatGPT, Gemini, Perplexity, and two other AI models
  • Four consistent signals drive AI recommendations across all models tested, though market share is not one of them
  • Review volume and star rating are among the factors evaluated, but the article does not specify their relative weight
  • Each AI model has its own ranking personality and preferences for local business selection
  • The research identifies actionable optimization tactics for multi-location businesses to improve AI visibility

Why it matters: Multi-location businesses need to understand how AI models select and recommend local locations, as AI search is increasingly influencing customer discovery and booking decisions. This data-backed analysis reveals which signals matter across different AI platforms, helping practitioners prioritize optimization efforts beyond traditional Google Local SEO.

Local SEOAI SearchMulti-Location OptimizationAI Models

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