Digital Digest
Marketing Intelligence Weekly
Weekly updates on the digital marketing news you need to know, including data reform, AI, cookie deprecation and platform updates.
Data privacy
Platforms
Google removing key GA4 privacy control for advertisers
- Google is removing a key GA4 privacy control for advertisers. From 15 June, turning off Google Signals will no longer stop advertising data from flowing into Google Ads.
- Consent Mode now becomes the main control point. After the change, whether ad-related data is collected will depend on the ad_storage setting, not the Google Signals toggle many teams previously relied on.
- This raises real compliance risk, especially if your CMP defaults to consent. If your banner is set to “granted” by default or is misconfigured, you could be collecting ad data without valid user consent.
- Google is effectively forcing a trade-off between privacy and performance. To fully block this ad data flow, businesses may need to set ad_storage to “denied” by default, but Google says that will hurt measurement, conversion tracking, and campaign performance.
- For EU/EEA advertisers, the stakes are even higher. With existing GDPR scrutiny around Google Analytics, brands may now have less direct control over data sharing while still carrying the legal responsibility as data controllers.
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AI in digital
Platforms
Anthropic launches Claude Opus 4.7
- Anthropic has launched Claude Opus 4.7 as its most capable publicly available model, with a strong focus on advanced coding, long-running task execution and improved instruction-following.
- The model introduces major upgrades in multimodal capabilities (especially vision), enabling it to better interpret complex images, diagrams and screenshots for real-world workflows.
- A key shift is more “agentic” behaviour — the AI can self-check its work, recover from errors and handle complex tasks with less human oversight, making it more useful for automation.
- Anthropic has baked in stronger safety controls, particularly limiting high-risk cybersecurity use cases, while positioning Opus 4.7 as a safer, more accessible alternative to its more powerful (but restricted) Mythos model.
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Platforms
UCP (Universal Commerce Protocol) guide from Google
- Google has released an onboarding guide for its Universal Commerce Protocol (UCP), giving merchants a clear path to enable AI-driven checkout directly within Search AI Mode and Gemini.
- UCP is part of Google’s push into “agentic commerce”, where users can move from product discovery to purchase without leaving conversational AI experiences.
- To get access, merchants must complete a technical integration, submit an interest form, and go through an approval process, with sandbox tools available to test setup (APIs, identity linking, checkout flows).
- The rollout is gradual and currently U.S.-focused, with a dedicated UCP integration tab in Merchant Center expected to expand over the coming months.
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AI in digital
Platforms
Google launches Skills in Chrome for changing Search behaviour
- Google has launched Skills in Chrome, a new feature in Gemini in Chrome that lets users save their best AI prompts as reusable one-click tools, so repeat tasks no longer need the same prompt typed over and over.
- The pitch is simple: users can turn successful prompts into repeatable workflows and run them on the page they’re viewing, plus other selected tabs, which makes AI more useful for comparison, summarisation and research-style browsing.
- Google is also launching a ready-made Skills library with prebuilt workflows for common use cases, including product ingredient breakdowns, gift selection, document scanning and side-by-side shopping comparisons.
- From a product and adoption angle, this is Google trying to make AI in Chrome feel less like a chatbot and more like a practical productivity layer built into everyday browsing. That’s an inference based on how Google describes repeated use cases and one-click workflows.
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AI in digital
Platforms
New York Times shows Google AI Overviews gets it wrong in 10% of searches
- Google’s AI Overviews are getting better, but they still got factual questions wrong about 9% of the time in February 2026, up from 85% accuracy in October to 91% after the move from Gemini 2 to Gemini 3. At Google scale, that small miss rate can still translate into millions of incorrect answers every hour.
- The bigger issue for marketers is trust, not just accuracy: more than half of the correct February answers were reportedly “ungrounded”, meaning the cited sources did not clearly support what Google claimed. That makes it harder for users to verify information and weakens confidence in AI-generated summaries.
- The reporting highlights a few messy examples where Google either pulled the wrong fact from mixed-quality sources or misread the right source altogether, including errors tied to the Bob Marley Museum, Yo-Yo Ma, and other basic factual queries. In other words, even when the source is there, the AI can still fumble the interpretation.
- Google pushed back on the study, saying the benchmark was flawed and not representative of what people actually search for. Even so, the story adds to a broader concern for publishers and brands: Google is increasingly answering the query itself, while sending less traffic back to the original source.
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AI in digital
Platforms
Google retiring Dynamic Search Ads in favour of AI Max
- Google is retiring Dynamic Search Ads (DSA), with new campaign creation stopping in September and all eligible campaigns automatically migrated to AI Max by the end of the month.
- The shift folds DSA, automatically created assets, and broad match into AI Max—Google’s AI-led search solution that uses real-time intent signals, not just website content, to match ads.
- AI Max is positioned as the next-gen upgrade, offering more control (brand, location, creative guidance) alongside automation and dynamic landing page + copy optimisation.
- Google claims AI Max delivers ~7% higher conversions or conversion value at similar efficiency, signalling a strong push toward AI-first campaign management.
- Marketers should act early—migrating now gives more control and testing time before forced upgrades, while also helping benchmark performance ahead of the transition.
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AI in digital
Platforms
Google says Search is shifting to a more agentic experience
- Sundar Pichai said many informational queries will become “agentic in Search”, with users running multiple threads and longer tasks inside Google’s search experience. For marketers, that suggests search journeys may become more complex, less click-based and more outcome-driven.
- He also described Search as becoming an “agent manager”, coordinating actions across tools and agents rather than simply returning a list of results. That raises the stakes for brands to be present, structured and useful wherever AI systems choose to act.
- Pichai said AI Mode is already changing user behaviour, with people using it for deeper research queries and longer-running tasks. In practice, that means marketers should expect more detailed, conversational and intent-rich search behaviour.
- Google isn’t positioning Gemini as a replacement for Search; Pichai said the two will overlap in some areas and diverge in others. So marketers should plan for a future where optimisation for Search and visibility in Gemini-style AI experiences both matter.
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AI in digital
Platforms
ChatGPT unveils location sharing for localised search results
- ChatGPT has rolled out optional location sharing, letting users provide precise device location to improve “near me” queries like restaurants, shops, and local services.
- The feature is opt-in and off by default, controlled via Settings → Data Controls, giving users flexibility over whether (and how precisely) they share location data.
- With precise location enabled, ChatGPT can deliver more relevant, localised results, positioning it closer to Google in high-intent local search use cases.
- Early feedback suggests results aren’t always perfectly accurate yet (e.g. recommending venues far away), highlighting room for improvement in local search performance.
- For marketers, this signals a shift toward AI-driven local search, where visibility in “near me” queries could become increasingly important for traffic and conversions.
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Platforms
GA4 launches Scenario Planner and Projections
- Google Analytics has launched Scenario Planner and Projections (currently in beta), aiming to help marketers forecast performance, optimise budgets, and manage cross-channel spend all within GA4.
- Scenario Planner is built for pre-campaign planning, letting marketers model different budget scenarios and estimate impact on conversions, revenue, and ROI before committing spend.
- Projections focuses on live campaigns, showing whether performance is on track and enabling mid-flight budget adjustments to avoid wasted spend.
- The key shift: Google is moving Analytics beyond reporting into decision-making and planning, reducing reliance on spreadsheets and centralising workflows in one platform.
- Access is limited (for now), requiring solid historical and multi-channel data — meaning more mature advertisers will benefit most, and output is directional rather than guaranteed.
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AI in digital
Platforms
Google launches Gemma 4 for greater agentic capability
- Google has launched Gemma 4, its most capable open-weight AI model family yet, built on Gemini 3 research and designed to make advanced AI more accessible across everything from smartphones to enterprise systems.
- The big unlock is agentic capability — native support for tool use, function calling and structured outputs means developers can build autonomous workflows and AI agents, not just chatbots.
- It’s built for flexible deployment at scale, with model sizes ranging from lightweight (mobile/edge) to powerful 31B parameter versions, plus availability across Google Cloud, Vertex AI and on-device environments.
- Gemma 4 pushes multimodal + long-context performance (up to ~256K context and support for text, image, audio), alongside strong gains in reasoning, maths and instruction-following benchmarks.
- For marketers, the shift is strategic: Google is signalling that the future of AI is deployable, customisable models powering real workflows (e.g. automation, commerce, agents) — not just API-based chat interfaces.
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AI in digital
Platforms
ChatGPT’s crawler is making 3.6x more requests than Googlebot
- ChatGPT’s crawler (“ChatGPT-User”) is now making 3.6x more requests than Googlebot, based on analysis of 24M+ requests across 69 websites—marking a major shift in who’s actually hitting your site.
- The AI crawler ecosystem is getting crowded, with multiple bots per platform (e.g. OpenAI has ChatGPT-User + GPTBot), and most sites don’t distinguish between them, creating gaps in tracking and control.
- AI crawlers are generally faster and more consistent than traditional bots, but their sheer volume is increasing server load and making crawl management (e.g. robots.txt) more critical.
- There’s a key technical catch: many AI crawlers can’t render JavaScript, meaning they may see a stripped-back or blank version of modern SPA websites—impacting visibility in AI outputs.
- For marketers, this signals a shift from “SEO-only” to AI visibility optimisation—you now need to audit how AI bots access, read, and potentially cite your content, not just how Google indexes it.
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AI in digital
Platforms
Meta unveils Muse Spark from Superintelligence Labs
- Meta has launched Muse Spark, the first AI model from its new Superintelligence Labs, signalling a major reset of its AI strategy and a push back into the competitive frontier AI race.
- The model is purpose-built for Meta’s ecosystem, powering Meta AI across Facebook, Instagram, WhatsApp and more, with a focus on faster, smarter, and more personalised user experiences.
- Muse Spark is multimodal and reasoning-first, able to process text, images and more, while using multiple AI agents in parallel to handle complex queries and tasks.
- A key differentiator is its efficiency and scalability, delivering strong performance with significantly less compute, positioning it as a cost-effective foundation for future models.
- For marketers, the big play is AI-driven discovery and recommendations, with Meta aiming to turn social content into real-time suggestions that influence purchasing and engagement across its platforms.
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AI in digital
Platforms
ChatGPT rolls out advertising in Australia
- ChatGPT is set to roll out advertising in Australia within weeks, expanding on a US pilot that showed “encouraging early signals.”
- Ads will only be shown to logged-in adult users on Free and ‘Go’ tiers, with paid plans (Plus, Pro, Business, Enterprise) remaining ad-free.
- The move signals a clear monetisation shift for OpenAI, as it looks to scale revenue while keeping the core product accessible to a growing user base.
- Early formats place ads within the chat experience (e.g. alongside responses), opening a new performance channel that blends search-style intent with conversational AI.
- OpenAI maintains that user conversations remain private and that ads won’t influence responses—critical for maintaining trust as the format evolves.
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Platforms
Google March 2026 broad core update is here
- Google has officially launched its March 2026 broad core update (March 27), with rollout expected to take up to two weeks, meaning ranking volatility will continue into early April.
- This is the first core update of 2026 impacting Search, following a Discover-only update in Feb and a rapid spam update just days earlier.
- As usual, Google hasn’t shared specifics — core updates are broad quality recalibrations, not targeted penalties, focused on surfacing more helpful and reliable content.
- Marketers should expect ranking and traffic fluctuations during rollout and avoid premature analysis until at least a week after completion.
- Any performance drops don’t indicate a penalty — instead, it reflects re-evaluation of content quality vs competitors, reinforcing the need for stronger content fundamentals.
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AI in digital
Platforms
Bing now shows AI queries mapped to your URLs
- Bing has upgraded its AI Performance dashboard to map “grounding queries” directly to the pages cited in AI answers, bridging a major gap in earlier reporting.
- Marketers can now click a query to see which pages are cited (and vice versa), making it much easier to tie AI visibility back to specific content and prioritise optimisations.
- The mapping is many-to-many, meaning one query can trigger multiple pages and one page can appear across multiple AI retrieval queries—offering richer insight into how AI interprets content.
- This is especially valuable because grounding queries aren’t user searches—they’re the phrases AI generates to build answers, giving a new layer of intent data for content strategy.
- Limitations remain: the dashboard is still in preview, shows sampled citation data only, and doesn’t include click-through or traffic metrics (so visibility ≠ performance… yet).
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AI in digital
Platforms
Google unveils Google-Agent giving clearer visibility when AI agents interact with your site
- Google has introduced a new “Google-Agent” user agent, rolling out over the next few weeks, designed to power AI agents that browse and take actions on behalf of users.
- Unlike traditional crawlers (e.g. Googlebot), this agent is tied to user-triggered tasks — such as form fills or assisted browsing via tools like Project Mariner.
- It gives marketers and site owners clearer visibility in server logs when AI agents (not humans or bots) are interacting with their sites.
- The move signals a broader shift toward agent-driven web interactions, where Google’s AI actively completes actions rather than just indexing content.
- Google is also testing new verification approaches (e.g. web-bot-auth via agent.bot.goog) to authenticate these AI-driven requests.
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AI in digital
Platforms
Shopify rolls out Agentic Storefronts enabling brands to sell directly inside AI chats
- Shopify is rolling out agentic commerce to all merchants, letting brands sell directly inside AI chats and assistants via “Agentic Storefronts” — no traditional website visit needed.
- Products, pricing, and inventory are synced in real time across AI surfaces, meaning shoppers can discover and purchase seamlessly wherever they’re interacting (e.g. chat, copilots).
- This signals a shift from search-led to agent-led shopping, where AI doesn’t just recommend products but can handle discovery, decision-making, and checkout.
- Shopify is positioning itself as the infrastructure layer for AI commerce, enabling millions of merchants to plug into AI ecosystems rather than building bespoke integrations.
- For marketers, this means optimising for AI visibility (structured product data, accuracy, availability) becomes critical as agents—not ads or search—drive purchase decisions.
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AI in digital
Platforms
Anthropic launches Computer Use for Claude Cowork and Code
- Anthropic has launched computer use for Claude Cowork and Claude Code, letting Claude point, click, type and navigate apps on your computer when there isn’t a direct connector available.
- The feature is currently in research preview for Claude Pro and Max subscribers, and Anthropic says it works particularly well with Dispatch, which lets users assign Claude tasks from their phone and pick them up later on desktop.
- Anthropic is leaning hard into safety messaging, saying Claude asks for explicit permission, requests access before opening new apps, and includes safeguards aimed at reducing risks like prompt injection.
- For now it’s supported on macOS only through the desktop app with the feature enabled.
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Platforms
Shopify reframes SEO as AI visibility with GEO playbook
- Shopify positions Generative Engine Optimisation (GEO) as the next evolution of SEO, as product discovery shifts from search engines to AI tools like ChatGPT and Google AI Overviews.
- GEO focuses on making brands and products appear in AI-generated answers, not just ranked links, meaning visibility now depends on being recommended by AI rather than clicked in search results.
- The shift is already material: AI-driven traffic to Shopify merchants grew 8x and orders 15x year-over-year, with a majority of shoppers now open to using AI in purchase decisions.
- However, the rules remain unclear, with no guaranteed way to “rank” in AI systems, forcing brands to act early despite limited playbooks.
- The implication is a new visibility battleground where brands that adapt first to AI discovery channels capture disproportionate demand, while others risk becoming invisible in high-intent buying moments.
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AI in digital
ChatGPT citations remain unpredictable as fan-out reshapes search visibility
- An AirOps study finds that ChatGPT retrieves far more content than it cites, with only ~15% of pages ever appearing in final answers, making visibility highly selective.
- This is driven by “query fan-out,” where a single prompt expands into many sub-queries, pulling content from multiple angles rather than a single search result set.
- Google rankings still influence discovery, but overlap is limited, meaning high SERP positions do not guarantee AI citations.
- The implication is a shift from ranking to retrieval and citation optimisation, where structured, extractable content across multiple intents increases the likelihood of selection.
- This reframes SEO into a probabilistic system, where visibility depends on how well content matches the full fan-out of AI queries, not just a single keyword.
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AI in digital
Vector databases fall short for SEO math as hybrid AI + SQL emerges
- An SEO experiment building a vector database from Google Search Console data shows that while AI-driven analysis improves discovery, it struggles with precise, metric-based queries.
- The system embeds 16 months of search data into a vector database, allowing natural language queries and pattern detection, but relies on semantic similarity rather than exact calculations.
- This creates a clear limitation: vector databases cannot reliably handle thresholds, rankings, or aggregations, where traditional SQL remains objectively more accurate.
- However, vector search outperforms SQL in identifying related topics and content gaps without needing predefined keywords, enabling broader strategic insights.
- The takeaway is a hybrid model: vector databases for discovery and pattern recognition, SQL for precision, highlighting that AI-native data stacks will complement, not replace, traditional analytics.
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Platforms
Google tightens e-commerce rules as out-of-stock workarounds are banned
- Google updated Merchant Centre rules, requiring retailers to show a visible but disabled “buy” button on out-of-stock product pages to improve consistency and user clarity.
- Previously common tactics, hiding the button or leaving it clickable, are now non-compliant, with stricter alignment required between on-page availability and product feed data.
- The change raises the risk of product disapprovals and ad disruption, forcing retailers to fix page UX and data consistency across systems.
- This signals a broader shift toward stricter control of product accuracy in Google’s commerce ecosystem, where feed integrity and real availability increasingly determine visibility and performance.
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AI in digital
CATCHES launches AI tool to improve online clothing fit
- CATCHES launched a generative AI sizing tool using physics-based simulation to improve fit accuracy, targeting high return rates in fashion e-commerce.
- The platform models how garments interact with real body shapes, moving beyond size charts and visual try-ons, with AMIRI as its first adopter on NVIDIA infrastructure.
- If effective, it could reduce returns and boost conversions, while shifting competition toward deeper, data-heavy fit simulation.
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AI in digital
Data privacy
Platforms
Perplexity fails first test in agentic ecommerce as judge rules in Amazon’s favour
- A US federal judge granted Amazon a preliminary injunction blocking Perplexity’s “Comet” AI shopping agent from accessing Amazon’s site and making purchases on behalf of users. The court said Amazon showed strong evidence the tool accessed password-protected accounts without Amazon’s authorisation.
- The ruling requires Perplexity to stop using its AI agent on Amazon and destroy any Amazon customer data collected through the tool, though the company has a short window to appeal the decision.
- At the centre of the case is a key question for AI commerce: do AI agents inherit a user’s permissions online? The judge rejected Perplexity’s argument that its bot simply automates actions users request.
- Amazon argues the bot disguised itself as a normal browser and scraped data, posing potential security and fraud risks, while Perplexity claims the lawsuit is about protecting Amazon’s ad-driven shopping ecosystem.
- The case is an early legal test for “agentic commerce”—AI tools that browse, compare products and complete purchases—which could disrupt retail search and the billions retailers earn from sponsored listings and ads.
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AI in digital
Data privacy
Platforms
OpenAI updates privacy policy in relation to ad targeting
- OpenAI updated its privacy policy to support the rollout of ads in ChatGPT, clarifying how ad personalisation, measurement, and data use will work as the platform moves deeper into advertising.
- Advertisers won’t get access to user conversations or chat history. Instead, they’ll only receive aggregated metrics (e.g., views and clicks) while ads are targeted using limited signals and user settings.
- Ads will primarily appear for Free and “Go” tier users, while paid tiers such as Plus, Pro and Enterprise will remain ad-free for now.
- OpenAI may receive conversion data from advertisers (e.g., if a user clicks an ad and later purchases), helping measure ad effectiveness — a standard practice in digital advertising.
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AI in digital
AI in travel
Platforms
Platforms in travel
Google launches Ask Maps, a Gemini conversational feature for itinerary planning
- Google Maps has launched “Ask Maps,” a Gemini-powered conversational feature that lets users ask complex, real-world questions directly in the app (e.g. finding a phone charging spot without long café queues). It replaces traditional keyword search with natural language queries.
- The tool delivers personalised recommendations by analysing data from Google Maps’ massive database of places, reviews and community contributions, tailoring results to user preferences and past behaviour.
- Ask Maps helps users move from discovery to action, suggesting locations, building custom itineraries, and even enabling actions like restaurant bookings directly within the conversation.
- The feature launches first on mobile (Android and iOS) in the US and India, with plans to expand to desktop and other regions over time.
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AI in digital
Platforms
Google Ads to automatically add AI voice over on your PMax campaigns
- Google Ads is rolling out AI-generated voice-overs for Performance Max video ads, automatically adding narration to videos that don’t already include spoken audio. The system pulls text from your existing headlines and descriptions to create the voice track.
- The feature is opt-out, not opt-in. Advertisers will be automatically enrolled unless they disable “video enhancement control” before 20 March 2026 in their campaign settings.
- When enabled, Google generates a new video asset with the AI voice layered over the original video, which then competes in auctions alongside the original creative.
- Only silent or music-only videos are affected. Ads that already contain narration or spoken audio won’t be modified by the feature.
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AI in digital
Majority of Australians can’t tell if an Ad is AI or not
- New B&T/Ideally research suggests most Australians still can’t reliably spot AI-made ads: only 12 per cent said they were very confident they could tell the difference, based on a nationally representative survey of 400 people.
- For marketers, the key takeaway is that disclosure matters more than detection. While 67 per cent said it would matter at least somewhat if an ad was AI-created, two in five said discovering that wouldn’t change their perception of the brand.
- Trust impact looks fairly limited overall, but not evenly spread. Women, older Australians and lower-income groups were more likely to say they’d trust a brand less if they found out the ad was made with AI, while younger and higher-income audiences were generally more relaxed or even positive.
- The bigger risk for brands isn’t the creative itself, but governance and data use. OneTrust’s Michael Schanker argues the real danger is around privacy, training data and agency-client transparency — particularly in more risk-sensitive categories where brands will want clear disclosure on tools, trade-offs and potential exposure.
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Marketing by numbers
Australia’s finance sector spent big on ads in 2025
- Australia’s finance category went hard on media in 2025, with ad spend up 20% year-on-year to $756 million, signalling a much more aggressive fight for customer attention across banking, credit, savings and investing.
- The big banks are leading the charge, with Westpac the top advertiser, followed by Commonwealth Bank, ANZ and NAB. That points to a highly competitive market where share growth is being driven as much by brand visibility as by product offers.
- Rose Lopreiato, Nielsen Ad Intel’s Australia Commercial Lead, said: "Financial brands are operating in a category where competitive activity and consumer pressure are rising at the same time. Ad Intel shows where advertising investment is increasing and which brands are driving that pressure, while CMV helps explain the consumer mindset behind it, from switching intent and cost-of-living stress through to demand for credit, savings and investment products. Together, those insights help marketers understand not just where the market is moving, but why.”
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AI in digital
Platforms
Update on ChatGPT ads
- OpenAI is rolling out ads in ChatGPT — the company has started introducing ads to users of the free and Go subscription tiers in the U.S. market as part of a broader shift toward monetisation.
- COO Brad Lightcap says this will be “an iterative process” — emphasising that the company wants to get it right, particularly around user trust and privacy.
- Lightcap noted that if ads are done right, they “can be additive to a product experience”, but he also acknowledged it will take time and asked people to “give us a few months” to evaluate how this goes.
- He didn’t discuss plans for expanding ads beyond the U.S. at this stage.
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