IAB Australia report finds instant answers reshape search measurement

IAB Australia published guidance on December 4, 2025, addressing how instant answers and zero-click search experiences require marketers to abandon traditional traffic measurement in favor of citation-based metrics, according to the organization's Future of Search Working Group.

The guidance document arrives as AI-powered search features fundamentally alter how users discover information online. Since Google's Knowledge Graph launched in 2012 through the recent introduction of AI Mode in Australia in early October 2025, the search industry has consistently pursued one objective: reducing friction between user questions and answers.

That objective has culminated in what the industry now calls instant answers or zero-click search, where queries get resolved directly on results pages without any click-through to websites, according to the IAB Australia report.

Microsoft integrated GPT-4 into Bing's search interface in early 2023, while Google rolled out its Search Generative Experience later that year, according to Search Engine Land. These tools synthesize information from multiple sources and deliver conversational answers directly on search pages.

Research cited in the IAB Australia document indicates that clicks following AI-driven instant answers can carry deeper intent and richer context compared to traditional search results. These search experiences absorb much of the discovery that previously appeared as traffic metrics without meaningful subsequent engagement.

The economic implications vary significantly by sector and organization type. Publishers relying on page views to create advertising inventory face more downward pressure, at least in the short term, according to the guidance.

Framework recommendations for optimization

The IAB Australia working group, comprising Anne Tran of Admatic ANZ, Gregory Cattelain of Spark Foundry, and Bonnie Dodemaide of iProspect, outlined recommended frameworks from Google and Microsoft designed to help create website content that attracts visibility in modern search engine results pages.

Both companies emphasize three core principles: transparency and structure through features like Schema.org so AI models can reliably read and use information; trust and reliability through strong site authority and clear content purpose; and future-proofing for the AI-driven "Agentic Web" by requiring either inherent content quality or direct technical interfaces.

Google's E-E-A-T framework evaluates Experience, Expertise, Authoritativeness, and Trustworthiness. While E-E-A-T itself is not a specific ranking factor, using factors that identify content with strong E-E-A-T proves useful, according to Google Search Console documentation cited in the report.

Content creators must evaluate material using Google's "Who, How, and Why" approach, according to the guidance. Visitors need to see who authored the content through bylines linking to author background information. Transparency requires explaining the creation process, including details about how products were tested or the number of items reviewed.

For content involving automation, creators must disclose AI or automation use and explain why and how the technology was utilized. The primary motivation must be genuinely helping people rather than merely attracting search traffic, as content created solely to manipulate search rankings violates Google's spam policies, according to the document.

Microsoft introduced NLWeb, an open-source framework designed to help brands transform any website into an AI-powered application allowing users and AI agents to query content directly in natural language, according to the IAB Australia analysis.

NLWeb acts as a lightweight layer on existing content, leveraging semi-structured data such as Schema.org markups, RSS feeds, and JSON-LD. Implementation requires only a small piece of JavaScript paired with optional customization. Once implemented, NLWeb automatically uses the site's structured data and a large language model backend to understand and answer queries.

The framework is model-agnostic and supports major AI models plus all search engines. Each NLWeb instance functions as a Model Context Protocol server, becoming an emerging standard for AI agents to discover and interact with web content, according to the document.

Measurement shifts from volume to value

Google's May 2025 Search Quality Evaluation found that sessions originating from AI Overview clicks are 32% longer and 21% more likely to convert than traditional organic visits, according to the IAB Australia report citing Google Developers documentation.

When users click after viewing an AI-generated answer, they spend longer time on-site, engage with more content, and demonstrate higher conversion likelihood. Google refers to these as "higher-quality clicks," signaling deeper intent and satisfaction.

Microsoft's complementary research noted that AI-mediated queries drive higher satisfaction and post-click depth across sectors such as retail and finance. In its 2025 Zero-UI report, Microsoft observed that users increasingly rely on AI and voice-powered interfaces for instant answers, but when they do click through, it's typically for in-depth exploration or purchase decisions, according to Microsoft Advertising Blog documentation cited by IAB Australia.

Industry analyst Rand Fishkin has reframed zero-click visibility as a branding opportunity, according to Search Engine Land sources referenced in the report. Appearing in featured snippets or AI citations builds familiarity and trust even when no immediate visit occurs. Fishkin calls this the "seen vs. chosen" effect, comparable to brand impressions in traditional advertising.

For publishers, this exposure may never fully substitute for monetizable visits, but it can reinforce brand authority, support direct traffic, and strengthen the case for inclusion in future AI-driven experiences, according to the guidance.

Bain & Company observed that generative AI compresses multi-step discovery journeys into concise, high-intent interactions, according to the IAB Australia document. Google's internal data corroborates this, noting that AI Overviews expose users to more diverse sources for complex queries even as total clicks fall.

New success metrics emerge

Traditional ranking has become less trustworthy due to the lack of distinction between different environments, according to the IAB Australia working group. Metrics that remain reliable include clicks, sessions, and conversion rate, as these are closely tied to lower-funnel keyword intent.

New metrics are quickly emerging including mention, citation, and sentiment, with the overarching goal to provide "Share of Model" helping advertisers and publishers understand how often their content appears in large language model outputs, according to the document.

These metrics can be measured by third-party tools like BrightEdge, Evertune, Share of Model, and Profound, though adoption needs tailoring for each business need, according to the guidance.

However, no industry standard has been established, and these metrics can fluctuate significantly due to varying large language models and highly personalized queries. The impact differs by industry; some AI models exclude sectors like finance and pharmaceuticals, which face more pressure, while industries such as fitness, travel, and entertainment may need to adopt new metrics more quickly.

Evaluating search increasingly becomes a full-funnel affair. At category and discovery level, share of model dimensions are key. As consumer intent gets close to final outcomes like specific content consumption, leads, or purchases, traditional metrics remain valuable for evaluating search effectiveness, according to the working group.

Case study demonstrates optimization potential

F45, a leading global fitness franchise with major U.S. presence, illustrates how visibility in AI-generated answers can grow when brands actively optimize for it, according to proprietary data supplied to IAB Australia with permission from F45.

Since January 2025, AI Overviews across the brand's fitness-related keywords in the U.S. increased by 472%, while F45 grew its own inclusion within those Overviews by 797%, significantly expanding the share of AI answers in which it was cited.

This uplift was achieved by focusing on emerging success measures and getting fundamentals right: ongoing content optimization, structured-data improvements, and authority-building partnerships with brands such as Hyrox and Reebok. This demonstrates how brands that strengthen entity signals, content depth, and topical authority can grow their presence within AI-generated summaries, even in a zero-click environment, according to the case study.

Recommended actions for marketers

The IAB Australia working group provided five priority recommendations for agencies and brands adapting to instant answer environments.

Traffic volume is increasingly likely to be replaced by more valuable clicks and intent compression. Brands should consider shifting content strategies to focus more on in-depth content that complements AI-referenced content, designed to add value when users want to see more. This recommendation carries high priority.

Optimizing for AI answer readiness requires shifting from pure traffic to citation-focused optimization. The working group recommends starting audits and adapting highest-value pages and top-performing content so they are concise, schema-marked, and answer-friendly for AI and voice interfaces. E-E-A-T signals such as author biographies, expertise, and source transparency should be clearly embedded. This also carries high priority.

Evolving search measurement frameworks to integrate new emerging metrics represents a medium priority. Brands should establish recurring processes to monitor how AI-generated results include or cite brand content. The guidance recommends integrating Search Console and Bing Webmaster data into dashboards to track impressions, visibility, mention, citation, and sentiment without losing focus on metrics indicating high-quality clicks.

The adoption of agentic AI will continue disrupting traditional search metrics, requiring medium-priority consideration. Brands and agencies should begin considering strategies like Microsoft's NLWeb framework to future-proof themselves for agentic traffic and accessibility.

Instant answers and zero-click search are generating a broader range of search intent further up the funnel, which can lead directly to conversions within large language model-powered searches. This means brands need to ensure correct attribution and AI-driven purchase path optimizations to convert users from awareness to purchase in "one session," according to the medium-priority recommendation.

The transformation represents fundamental changes in digital marketing measurement and optimization, requiring immediate attention from marketing professionals navigating these discovery changes.

Timeline

• 2012: Google's Knowledge Graph launched, initiating the reduction of friction between user questions and answers
• Early 2023: Microsoft integrated GPT-4 into Bing's search interface
• Late 2023: Google rolled out Search Generative Experience
• May 2024: Google launched AI Overviews in the United States
• May 2025: Google's Search Quality Evaluation found sessions from AI Overview clicks are 32% longer and 21% more likely to convert
• Early October 2025: Google introduced AI Mode in Australia
• December 4, 2025: IAB Australia published instant answers and discovery guidance
• Current state: Zero-click searches now account for approximately 69% of Google searches, up from 56% before AI Overview deployment

Summary

Who: IAB Australia's Future of Search Working Group, comprising Anne Tran (Admatic ANZ), Gregory Cattelain (Spark Foundry), and Bonnie Dodemaide (iProspect), published guidance for brand marketers and agencies navigating instant answer environments.

What: The guidance document addresses how AI-powered instant answers and zero-click searches require marketers to shift from traditional traffic volume metrics to citation-based measurement, while providing framework recommendations from Google (E-E-A-T) and Microsoft (NLWeb) for optimizing content visibility in AI-generated search results.

When: IAB Australia released the report on December 4, 2025, analyzing developments from Google's Knowledge Graph launch in 2012 through the introduction of AI Mode in Australia in early October 2025, including research findings from Google's May 2025 Search Quality Evaluation.

Where: The guidance applies globally to digital marketing professionals working with major search platforms, though it was specifically published by IAB Australia with case study data from F45's U.S. market performance and implementation recommendations relevant across markets where Google and Microsoft operate AI-powered search features.

Why: The shift matters because clicks following AI-driven instant answers carry deeper intent and richer context while overall traffic volumes decline, requiring fundamental changes in how marketers evaluate search performance and optimize content for AI-mediated discovery experiences, with emerging metrics like mention, citation, and sentiment becoming critical for measuring "Share of Model" as traditional ranking and volume metrics lose reliability.