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.
AI in digital
Platforms
OpenAI is sharing user data signals with advertisers
- OpenAI has enabled marketing cookies by default for free users, allowing it to share identifiers like cookie and device data with advertising partners to promote its products
- The move supports a broader push into advertising, with OpenAI building out ad infrastructure and testing ads inside ChatGPT to monetise its large free user base
- OpenAI maintains that user conversations remain private and are not shared with advertisers, with partners only receiving aggregated or non identifying performance data
- Users still have control, with options to opt out of tracking and ad personalisation, while paid tiers remain largely exempt from these changes
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Platforms
Google Tells Developers To Build For AI Agents, Not Just Humans
- Google is advising developers to treat AI agents as a new type of user, as more tasks are being completed by AI instead of people browsing directly
- It recommends building agent friendly websites, since many current design patterns do not translate well for AI interacting with pages
- AI agents understand websites through visual rendering, HTML structure, and accessibility signals, which developers need to optimise for
- This reflects a broader shift towards task based experiences, where AI completes actions on behalf of users rather than users navigating sites themselves
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Platforms
Snapchat launches loyalty badges for Snap Map locations
- Snapchat has introduced “Place Loyalty” badges that show when users are among the most frequent visitors to a location based on activity over the past year
- Users are ranked into tiers such as gold, silver, and bronze depending on how often they visit a place, adding a gamified, competitive element similar to Snap Streaks
- Badges are private to each user but can be shared via stickers, encouraging social sharing without publicly exposing rankings by default
- The feature is designed to drive repeat visits and engagement with Snap Map, while also creating potential value for brands through aggregated location data
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AI in digital
Platforms
Google introduces AI qualified call leads
- Google Ads is shifting from measuring calls by duration to using AI to assess actual lead quality, analysing conversations to detect real purchase intent
- The system filters out low value interactions like spam, robocalls, and wrong numbers, improving the accuracy of conversion data
- Higher quality signals are fed into Smart Bidding, helping campaigns optimise towards more valuable leads rather than just longer calls
- Call recording is enabled by default (with some industry exceptions) so AI can evaluate conversations, with summaries and tags added for better reporting transparency
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Marketing by numbers
Social overtakes search as advertising market declines in March
- Australia’s ad market fell more than 5 per cent in March, largely due to last year’s federal election inflating comparisons and ongoing economic uncertainty impacting budgets
- Social media ad spend overtook search for the first time, pushing search into third place behind social and programmatic in the digital mix
- Digital bookings declined overall, though video and streaming continued to grow strongly, now accounting for more than 10 per cent of digital spend
- The broader market remains cautious, with late bookings increasing and brands holding back on committing budgets earlier, making planning more difficult for media owners
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AI in digital
Platforms
Google starts rolling out Gemini in Chrome across APAC
- Google is rolling out Gemini in Chrome across APAC (including Australia), embedding an AI assistant directly into the browser to help users summarise content, compare tabs and complete tasks without leaving the page.
- The move turns Chrome into a productivity hub, with deep integrations across Gmail, Maps, Calendar and YouTube—meaning users can take actions (like sending emails or scheduling meetings) mid-browse.
- New features like AI-powered image editing (Nano Banana 2) and “Personal Intelligence” add personalisation, letting the assistant remember context and tailor responses over time.
- Strategically, this is about owning the AI layer of the web experience, positioning Chrome as more than a browser and competing directly with tools like Microsoft Copilot.
- Google is emphasising security and user control, with safeguards for sensitive actions and protections against prompt injection as AI becomes more embedded in everyday browsing.
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AI in digital
Platforms
Sponsored Stores ad unit in Google AI Mode
- Google’s AI Mode has been spotted showing a new “Sponsored Stores” ad unit, signalling more retail ad formats are coming to AI-led search experiences.
- The unit appears in the right-hand ecommerce sidebar after a user clicks a product in an AI Mode answer, giving retailers another paid visibility option.
- For marketers, this reinforces that AI search is becoming a commercial media surface, not just an organic discovery channel.
- Google also showed “Quick results from the web” above the AI answer, including organic links, suggesting AI Mode may blend paid, organic and shopping experiences more tightly.
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AI in digital
Marketing by numbers
Platforms
Ahref’s study of 1.4M prompts shows ChatGPT only cites 50% of pages
- ChatGPT retrieves lots of pages per query but only cites ~50%—there’s a “gatekeeping” step before content is even read, where titles, snippets, and URLs decide what gets opened.
- Metadata matters more than most marketers think: clear, relevant titles and clean URLs significantly boost your chances of being cited, even before content quality is considered.
- Authority still wins—pages on high-authority domains and those ranking well in Google are far more likely to be cited, showing strong overlap between SEO and AI visibility.
- Content depth and specificity drive citations: pages with concrete data, structured sections, and clear answers outperform generic or fluffy content.
- ChatGPT often uses sources without crediting them (e.g. Reddit), meaning influence ≠ attribution—being cited requires both relevance and “citable” formatting.
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AI in digital
Marketing by numbers
YouGov study shows Aussies want to know when AI is used
- 86% of Australians want brands to clearly disclose when content is AI-generated, signalling transparency is now a baseline expectation, not a nice-to-have.
- There’s a real trust trade-off: 32% would trust brands less if AI is used, while only 15% would trust them more—how you communicate AI use matters as much as using it.
- Concern outweighs hype, with over half of consumers sceptical about AI and 73% worried about misinformation—creating an opportunity for brands to position themselves as credible sources.
- Context is key: AI is more accepted in entertainment and advertising, but far less in news and influencer content, where authenticity expectations are higher.
- Bottom line for marketers: transparency, clear labelling, and thoughtful AI use aren’t just compliance—they’re fast becoming a competitive advantage for building trust.
- FYI: Yes we did use AI to help write this post but all Digital Digest content is chosen, vetted, and edited by a human.
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AI in digital
Survey shows consumers use AI for discovery but still rely on reviews before purchase
- Consumers are embracing AI for product discovery, but trust is still low—nearly all shoppers double-check AI recommendations before buying, typically by turning to online reviews.
- Online reviews remain a critical validation layer, with shoppers relying on peer feedback to confirm whether AI-suggested products are actually worth purchasing.
- Only a tiny fraction of consumers will purchase directly from an AI recommendation without doing additional research, highlighting a major trust gap.
- For marketers, this reinforces that AI may drive discovery, but reviews and social proof still play a decisive role in conversion.
- The takeaway: brands need to optimise both AI visibility and review credibility, as the two now work hand-in-hand in the path to purchase.
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AI in digital
Platforms
OpenAI announces ChatGPT-5.5
- GPT-5.5 is positioned as OpenAI’s smartest, most “agentic” model yet, designed to handle complex, multi-step tasks like coding, research, and data analysis across tools—not just chat responses.
- Big shift: AI that actually “does the work”, with stronger ability to use tools (e.g. spreadsheets, documents, apps), maintain context, and execute tasks over time with less prompting.
- Major gains in efficiency + performance, delivering higher-quality outputs with fewer tokens and retries, while maintaining similar speed to previous models.
- Strong focus on real-world business use cases, from automating reporting and financial analysis to generating presentations—already saving teams hours of work weekly.
- Rolling out to paid ChatGPT tiers and enterprise users, signalling a continued push into workplace productivity and AI-powered workflows at scale.
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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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