Search News: AI-Powered Search, Analytics Updates, and Strategic Shifts

Recent headlines reveal a rapidly evolving search landscape, with AI-driven experiences, analytics advancements, and new transactional capabilities reshaping how brands achieve visibility and ROI. From Perplexity’s $400M integration with Snapchat to Google’s deprecation of structured data and the expansion of agentic features in AI Mode, search professionals must adapt to new user behaviours and optimisation challenges. Marketers are also seeing enhanced analytics granularity, a stronger focus on brand mentions for AI rankings, and actionable frameworks for future-proofing SEO and PPC strategies. Below, we break down the most significant news items and their implications for agencies and in-house teams alike.

Perplexity Bets $400M On Snapchat To Scale AI Search Adoption

Perplexity’s $400 million partnership with Snapchat marks a pivotal moment in AI-powered search adoption. By embedding its AI answer engine directly into Snapchat’s chat interface, Perplexity gains access to a vast, predominantly Gen Z audience. Reportedly over 943 million monthly users. This integration positions AI search not as a standalone utility, but as a seamless part of daily digital conversations, meeting users where they already spend significant time.

For search professionals, this signals a profound shift: AI-driven Q&A is moving beyond traditional search engines and into social and messaging platforms. The classic playbook of optimising for Google’s SERPs is no longer sufficient. Brands must now consider how their content, products, and expertise are surfaced in conversational interfaces, where AI-generated answers and entity recognition take precedence over conventional ranking factors.

At a strategic level, senior marketers and agency leaders should anticipate a fragmentation of the search landscape. Search visibility will increasingly depend on being referenced and recommended within AI-driven environments, not just on keyword rankings. This demands investment in digital PR, brand authority, and content that is easily understood and cited by AI systems. For operational teams, monitoring how AI integrations like Perplexity-Snapchat affect discovery, engagement, and conversion among younger demographics will be essential. Agencies should proactively educate clients about these shifts and explore opportunities to optimise for emerging AI-powered channels.

Google Deprecates Practice Problem Structured Data In Search

Google’s decision to deprecate Practice Problem structured data is a clear reminder that the search giant is continually refining which schema types it supports. For educational and e-learning websites, this means Practice Problem markup will no longer generate rich results or enhanced visibility in Google Search from January onwards. The move is part of Google’s broader effort to simplify search results and phase out features that are underutilised or offer limited value to users.

For SEO professionals managing educational content, this change necessitates an immediate audit of structured data implementations. Outdated or unsupported schema can lead to Search Console errors, missed opportunities for enhanced SERP features, and potential confusion in reporting. Agencies should prioritise removing or updating deprecated markup and focus on other supported schema types, such as FAQ, HowTo, or Article – to maintain or improve organic presence. This is also a timely moment to review all client sites for deprecated or at-risk schema, ensuring ongoing compliance with Google’s evolving guidelines.

At a higher level, this development underscores the importance of agility in technical SEO. As Google continues to iterate on its SERP features and structured data support, agencies must remain vigilant, proactively communicating changes to stakeholders and reallocating resources to the most impactful optimisation opportunities. For senior decision-makers, investing in regular schema audits and ongoing education around structured data best practices will be key to sustaining organic visibility in a dynamic search environment.

YouTube Separates Organic & Paid Metrics In Channel Analytics

YouTube’s latest analytics update introduces a clear separation between organic and paid performance metrics, allowing marketers to distinguish views, engagement, and growth driven by organic discovery versus paid campaigns. This granular filtering addresses longstanding confusion around how advertising impacts channel performance, enabling more accurate attribution and campaign optimisation.

For search and PPC professionals, this is a significant advancement. Marketers can now measure the true impact of organic SEO efforts on YouTube, independently of paid promotion. This clarity supports better decision-making on content strategy, audience targeting, and budget allocation. It also empowers agencies to deliver more transparent reporting to clients, demonstrating the distinct contributions of organic and paid activities.

At a strategic level, this change enables brands to identify high-performing content that resonates organically, refine creative for paid campaigns, and optimise spend for maximum ROI. Senior marketers should leverage these insights to inform cross-channel strategies, ensuring resources are focused on tactics that drive sustainable growth. As YouTube continues to evolve as a hybrid search and social platform, staying abreast of analytics enhancements will be crucial for agencies managing integrated search and paid media campaigns.

AI Search Playbook: The Strategy Leaders Want, and Teams Can Act On

A new playbook for AI search optimisation provides actionable strategies tailored for both leadership and operational teams. The guide emphasises the importance of aligning SEO and content strategies with AI-driven ranking factors, integrating structured data for better AI comprehension, and adopting a test-and-learn approach to emerging AI search features. Cross-functional collaboration between marketing, product, and data teams is highlighted as essential for maximising AI search opportunities.

For SEO professionals, the playbook delivers practical frameworks for measuring AI search visibility, optimising for entity-based signals, and ensuring content is structured for machine-readability. It encourages experimentation with AI search tools and continuous monitoring of performance metrics to adapt strategies as the landscape evolves. For agencies, this resource is invaluable for guiding clients through the transition to AI-centric search, helping to maintain competitive advantage and visibility.

At a senior level, the playbook provides clarity on how to future-proof search marketing efforts. Leaders are encouraged to invest in education, foster a culture of experimentation, and break down silos between teams to respond quickly to AI-driven changes. The overarching message is clear: sustainable growth in search will depend on agility, data-driven decision-making, and a willingness to embrace new optimisation paradigms as AI reshapes user discovery and conversion paths.

AI SEO: How To Understand AI Mode Rankings

With Google’s AI Mode gaining traction, understanding how rankings are determined in AI-powered search has become critical for SEO professionals. Unlike traditional SERPs, AI Mode relies heavily on entity recognition, semantic relevance, and the ability to satisfy latent user questions—those that are implied but not explicitly stated in the initial query. This marks a shift from keyword-centric optimisation to a more holistic, topic-based approach.

The article highlights the importance of optimising content for clarity, topical authority, and machine-readability. Techniques such as reverse question answering can help identify which questions your content answers, ensuring it aligns with the information needs of AI models. Additionally, robust internal linking, up-to-date structured data, and a focus on being mentioned across authoritative sites are now more influential than traditional backlinks in determining AI visibility.

For agencies and senior marketers, the rise of AI Mode requires a re-evaluation of tracking and reporting frameworks. AI-driven results may differ significantly from classic rankings, necessitating new metrics and KPIs. Educating clients about these changes and updating SEO frameworks to prioritise entity optimisation, brand mentions, and content comprehensiveness will be essential. Staying ahead in AI-driven search means embracing a post-keyword era, where context, authority, and digital PR play an outsized role in organic success.

Google AI Mode Starts Rolling Out Agentic Booking In Labs

Google’s rollout of agentic booking capabilities within AI Mode Labs represents a major step towards transactional search experiences. Users can now book appointments and services, such as restaurant reservations, event tickets, and wellness appointments – directly through AI-powered search interactions, without leaving the search environment. This development signals a fundamental change in user behaviour and conversion pathways.

For search marketers, the implications are significant. Brands must ensure their business information, structured data, and booking integrations are accurate and up-to-date to be eligible for in-search transactions. The traditional website visit may decline in favour of direct, in-search conversions, requiring marketers to rethink attribution models and optimise for visibility within AI-driven booking features.

Agencies should closely monitor the rollout of these capabilities and advise clients on best practices for eligibility and optimisation. For senior decision-makers, the expansion of agentic features underscores the need for a holistic digital presence. One that goes beyond website optimisation to include seamless integrations with third-party platforms and booking systems. Preparing for a future where search is both interactive and transactional will be key to maintaining relevance and driving conversions.

Holiday PPC Guide 2025: Advanced Strategies For Smarter Bidding, Budgets & Audiences

The 2025 Holiday PPC Guide delivers a comprehensive set of advanced strategies for optimising paid search campaigns during peak shopping periods. Key recommendations include leveraging automation for bid adjustments, using historical data to forecast demand, and segmenting audiences for tailored ad creatives. The guide also stresses the importance of real-time performance monitoring and dynamic budget allocation to capitalise on shifting trends and maximise ROI.

For PPC professionals, the guide offers tactical advice on smarter bidding; such as using seasonality bid adjustments, portfolio bidding, and inventory-aware automation to avoid wasted spend on out-of-stock products. Creative best practices, including multi-asset pinning in Responsive Search Ads and staging ad waves to combat creative fatigue, are highlighted as essential for standing out in crowded auctions.

At a strategic level, the guide encourages agencies to integrate cross-channel data for holistic campaign management and ensure robust tracking and attribution systems are in place. Senior marketers should focus on guiding automation with strong business signals, protecting profitability, and turning expensive holiday buyers into long-term customers through post-season retention campaigns. The message is clear: success in Q4 requires agility, proactive planning, and a willingness to embrace both automation and human oversight.

Ahrefs Data Shows Brand Mentions Boost AI Search Rankings

New research from Ahrefs reveals that brand mentions, particularly unlinked mentions on authoritative third-party sites. significantly enhance rankings in AI-powered search results. The study found a strong correlation (0.67) between the frequency of brand mentions and the likelihood of being cited in AI Overviews and conversational answers, suggesting that entity recognition and brand authority are now critical ranking factors.

For SEO professionals, this marks a shift from traditional link-building to a broader focus on digital PR, thought leadership, and content partnerships. Being discussed across industry-relevant platforms, review sites, and user-generated content hubs like Reddit and Quora increases the chances of being surfaced in AI-generated answers. The research also highlights the value of YouTube video transcripts and authoritative citations as key signals for AI systems.

Agencies should advise clients to invest in brand-building activities that drive organic mentions and entity optimisation. Tracking brand mentions alongside backlinks, and incorporating entity-based strategies into SEO roadmaps, will be vital for maintaining visibility in both traditional and AI-driven search environments. For senior marketers, the findings reinforce the importance of reputation management and proactive outreach to ensure brands are referenced in the right context across the digital ecosystem.

Report: Google AI Overviews Continue To Drive CTR Downwards

Recent data from Seer Interactive, as reported by Search Engine Roundtable, confirms that Google’s AI Overviews are causing a continued decline in click-through rates (CTR) from both organic and paid search results. The trend has intensified, with AI Overviews increasingly capturing user attention and reducing traffic to traditional listings. The report highlights a 65% CTR decline in organic search and a 78% decline in paid search when AI Overviews are present and a site is not cited, with even cited sites experiencing significant drops.

For search marketers, this represents a pressing challenge. Optimising for inclusion in AI Overviews is now a critical tactic for sustaining visibility and engagement. Enhancing entity signals, structured data, and brand authority can improve the likelihood of being featured in AI-generated summaries, but even then, the CTR uplift is limited compared to historic norms. Agencies must also monitor CTR trends closely and adjust reporting to account for the impact of AI-driven SERP changes.

At a senior level, this data underscores the need to diversify traffic sources and educate stakeholders about the shifting dynamics of SERP real estate. Relying solely on traditional organic or paid listings is increasingly risky. Strategic investment in brand-building, alternative channels, and AI-focused optimisation will be essential for mitigating the impact of declining CTRs and maintaining digital performance.

Google AI Mode Gains 3 New Agentic Capabilities

Google has expanded its AI Mode with three new agentic capabilities: booking event tickets, beauty appointments, and wellness appointments directly through the search interface. This builds on the recent addition of restaurant reservations, further enhancing the transactional functionality of AI Mode and allowing users to complete a wider range of actions without leaving Google.

For marketers, this development highlights the growing importance of optimising business listings, structured data, and integrations with booking platforms. Brands that fail to ensure their services are eligible for these features risk losing visibility and conversions to more agile competitors. Agencies should guide clients through the technical requirements and monitor performance metrics related to in-search transactions, as traditional conversion funnels may be disrupted.

At a strategic level, the expansion of agentic capabilities signals a broader trend towards interactive, self-contained search experiences. Senior marketers must anticipate shifts in attribution, conversion tracking, and customer journey mapping. Proactively adapting to these changes by investing in robust integrations, data sharing, and eligibility optimisation – will be crucial for maintaining competitive advantage as AI-driven search becomes more transactional.

Google Tests A New Version Of AI Mode

Google is currently testing a new version of AI Mode responses within its search interface, inviting users to provide feedback on preferred response formats. This experiment, which presents side-by-side AI-generated answers for comparison, aims to refine how information is surfaced and consumed in search. The outcome of these tests may influence future SERP layouts, answer presentation, and the prominence of AI-generated content.

For search marketers, these ongoing tests signal that the AI-driven search experience is still in flux. Agencies should closely monitor developments and assess their potential impact on organic visibility, user engagement, and content strategy. Optimising for clarity, authority, and machine-readability remains essential to increase the likelihood of being featured in evolving AI Mode formats.

At a higher level, adaptability is paramount. Senior marketers should foster a culture of responsiveness, ensuring teams are prepared to pivot strategies as Google iterates on its AI interface. Staying informed about interface experiments and user feedback will help agencies and brands maintain relevance and visibility in a rapidly changing search environment.

Google Merchant Center Adds Promotions For Top Performing Products

Google Merchant Center has introduced a new promotion method specifically for top-performing products, enabling merchants to highlight their best sellers in Google Shopping and Search. This targeted approach allows advertisers to allocate promotional resources more strategically, focusing on items with proven demand and conversion potential.

For PPC professionals and e-commerce marketers, this update offers a valuable opportunity to maximise ROI by boosting visibility and sales of high-converting products. Agencies should review clients’ Merchant Center accounts to identify eligible products and implement targeted promotions, ensuring that promotional budgets are directed towards SKUs with the highest impact.

At a strategic level, the change underscores the importance of ongoing product performance analysis and inventory management. Senior marketers should invest in robust data infrastructure to track top performers, respond quickly to market trends, and optimise promotional strategies in real time. Leveraging this new capability can help brands stand out in competitive shopping environments, drive incremental sales, and improve overall campaign efficiency during peak retail periods.

Google Merchant Center Smart Cropping – You Can Opt Out

Google Merchant Center now allows merchants to opt out of Smart Cropping, a feature that automatically crops product images for better display in Shopping and Search. While Smart Cropping aims to enhance visual presentation, some brands may prefer manual control to maintain brand consistency or highlight specific product details.

For marketers, this update provides greater flexibility in managing product imagery. Agencies should evaluate the impact of Smart Cropping on their clients’ listings, considering whether automated adjustments improve or detract from image quality and messaging. Testing both options and reviewing Merchant Center settings will help determine which approach best supports campaign goals.

At a senior level, the ability to opt out empowers brands to uphold visual standards and control how products are presented across Google’s surfaces. Consistent, high-quality imagery can influence click-through rates and conversion performance, making this a key consideration for e-commerce and retail marketers. Agencies should proactively communicate this option to clients and integrate image management into broader optimisation strategies.

Which Countries Have the Most AI Overviews? 108 Million Queries Analyzed

Ahrefs’ analysis of 108 million search queries reveals significant geographic disparities in the prevalence of Google AI Overviews. Indonesia leads with AI Overviews appearing for 37.2% of all keywords, followed by the Philippines, Mexico, India, and Nigeria. The US, UK, and Canada see lower—yet still substantial—coverage, with AI Overviews triggering for around 20% of queries.

For search marketers managing international campaigns, this data is invaluable. Brands operating in high-AI Overview regions must prioritise optimisation for inclusion in these features, focusing on structured data, entity signals, and authoritative content. Content localisation and market-specific strategies become even more important as AI-driven SERP features expand unevenly across geographies.

At a strategic level, agencies should use this data to tailor their approaches by market, ensuring clients remain visible where AI Overviews are most active. Senior marketers must invest in international SEO capabilities, monitor AI feature rollouts, and adapt content strategies to local user behaviours and search environments. Staying informed on AI Overview distribution is critical for maintaining competitive advantage in global search.

AI Can’t Replace SEO Tools. But It Can Use Them

This article explores the evolving relationship between AI and traditional SEO tools, emphasising that while AI cannot fully replace specialised platforms, it can leverage their data and functionalities to enhance optimisation efforts. Integrations like the Ahrefs Model Context Protocol (MCP) allow AI assistants such as ChatGPT to access live SEO data, bridging the gap between conversational interfaces and robust analytics.

For search professionals, the takeaway is clear: AI-driven workflows can automate repetitive tasks, surface actionable insights, and accelerate analysis, but human expertise and critical thinking remain indispensable. Agencies should experiment with hybrid approaches that combine AI capabilities with established SEO processes, using AI to scale insights and streamline reporting while retaining strategic oversight.

At a senior level, the message is one of balance. Over-reliance on AI is cautioned against; instead, marketers are encouraged to build workflows that harness both AI innovation and proven methodologies. Investing in tool integrations, staff training, and process optimisation will ensure teams can capitalise on AI’s efficiencies without sacrificing quality or strategic depth.

How to Earn LLM Citations to Build Traffic & Authority

This comprehensive guide details strategies for earning citations from large language models (LLMs) like ChatGPT, Gemini, and Copilot, which are increasingly shaping traffic and authority in AI-powered search. Key recommendations include optimising content for entity recognition, building topical authority, and securing brand mentions across reputable platforms. The article also stresses the importance of clear, factual, and well-structured information to increase the likelihood of being cited by AI systems.

For agencies, this means advising clients to invest in digital PR, expert content, and robust internal linking. Monitoring AI citation trends and adapting strategies to align with evolving LLM criteria are essential for enhancing visibility in AI-generated answers. The guide highlights that while direct traffic from AI citations is still modest, the quality and intent of these visitors are often higher, leading to stronger conversion rates.

At a strategic level, brands that invest early in citation optimisation will establish authority before the space becomes saturated. Senior marketers should prioritise content freshness, structured formatting, and amplification across the web to ensure their brands are referenced by AI systems. Tracking and reporting on AI-driven traffic and citations will become an increasingly important part of demonstrating digital marketing ROI.

AI Visibility Audit: How to Measure Your Brand’s Presence in AI Search

The AI Visibility Audit framework provides marketers with a step-by-step approach to assessing their brand’s presence in AI-powered search results. The audit covers identifying where and how a brand appears in AI-generated answers, analysing entity signals, benchmarking against competitors, and tracking citations and mentions across platforms like Google AI Overviews, ChatGPT, and Perplexity.

For agencies, conducting regular AI visibility audits helps clients understand their standing in the evolving search ecosystem and identify opportunities for improvement. The guide recommends using tools like Ahrefs’ Brand Radar to monitor mentions, citations, impressions, and share of voice, as well as analysing sentiment, accuracy, and authority in AI responses.

At a senior level, the audit process enables more targeted recommendations and measurable improvements. Marketers should use these insights to refine content strategies, strengthen brand authority, and optimise for AI-driven features. Proactive AI visibility assessments will ensure brands remain competitive as search engines increasingly rely on AI to deliver results and shape user perceptions.

Brand Gap Analysis: Find Out Why You’re Invisible in AI Search

Brand gap analysis is a methodology designed to help marketers identify why their brands may be invisible in AI-powered search results. The process involves auditing entity signals, content coverage, and digital PR efforts to uncover gaps that prevent inclusion in AI-generated answers. Actionable steps include enhancing structured data, increasing authoritative mentions, and aligning content with AI search intent.

For agencies, conducting brand gap analyses enables more targeted recommendations and measurable improvements for clients. The guide encourages marketers to benchmark their brand’s visibility against competitors, identify missed opportunities, and prioritise actions that will have the greatest impact on authority and discoverability.

At a strategic level, closing brand gaps is about more than fixing individual pages. It’s about reclaiming every opportunity where a brand should be part of the conversation, but isn’t. Senior marketers should focus on building a holistic visibility strategy that encompasses on-site optimisation, off-site mentions, and proactive outreach, ensuring their brand is represented accurately and prominently across both traditional and AI-driven search environments.

Strategic Directions: Navigating the New Era of Search and Digital Performance

The search landscape is undergoing unprecedented transformation, driven by the mainstreaming of AI-powered experiences, the rise of conversational and transactional search, and the increasing importance of brand authority and entity optimisation. For SEO and PPC professionals, success now depends on agility, cross-functional collaboration, and a willingness to embrace new tools, data sources, and optimisation paradigms.

Senior marketers and agency leaders must prioritise investment in digital PR, structured data, and AI visibility audits, while fostering a culture of experimentation and continuous learning. Attribution models, reporting frameworks, and campaign strategies must evolve to account for declining CTRs, in-search transactions, and the fragmentation of user journeys across platforms and interfaces.

Ultimately, brands that adapt quickly—by building robust digital ecosystems, optimising for both human and machine audiences, and proactively managing their presence across the web—will be best positioned to maintain visibility, engagement, and ROI in the new era of search. The time to act is now: agencies and in-house teams alike must future-proof their strategies to thrive in an AI-first, multi-channel world.