Digital news to watch: Google introduces updates to PMax
John Readman 🚴♂️ 🎙💻
🤖 AI Reporting and Forecasting for Ecommerce, B2B & Marketing - Agencies, Brands & Retailers
In this week's digital news, Google introduces new reporting to Performance Max to give you insights into your channel performance. AI-powered intention models are reshaping advertising, exploring their real-world impact across industries, and the future of advertising in a privacy-first world.
Google's updated QRG now includes fake EEAT content and other deceptive practices, signalling the importance of authenticity. A study analysing Google vs ChatGPT traffic finds Google keeps users on its site longer, but sends the most traffic overall.
LinkedIn dominates the employee advocacy landscape with employee posts reaching an average of nearly 900,000 impressions every month. Agencies are developing their own AI services to help with the complexities in their interactions with clients.
Google introduces updates to PMax
Google has introduced several updates to Performance Max aimed at improving transparency and campaign optimisation. A key addition is channel level reporting, which provides performance data across individual Google channels such as Search, YouTube, Display, and Maps. This includes a new visual summary and a detailed channel distribution table covering metrics like clicks, conversions, and cost. Full search terms reporting has also been added, allowing advertisers to analyse and manage search performance in greater detail. Additionally, asset level reporting now includes impressions, clicks, and cost, enabling more precise evaluation of creative performance. Diagnostics features highlight potential issues across specific channels.
Read more here.
How AI-powered intention models are reshaping digital advertising
Contextual targeting is evolving from basic keyword methods to AI driven models that incorporate user intention. These systems assess content not just by topic but by intent informational, navigational, or transactional to identify users closer to decision making. AI models trained on intent labelled data can score content accordingly and align ads with both high intent and campaign relevance. This approach improves targeting precision without relying on third party data, aligning with privacy first strategies. Case studies show strong performance gains across industries, with significant cost reductions and better engagement. Intention based targeting is emerging as a key tool in privacy conscious, outcome focused advertising.
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Google’s updated Raters Guidelines target fake EEAT content
Google have updated their Quality Raters Guidelines to expand on multiple forms of deception that Google wants its quality raters to identify, including fake EEAT content, signalling the importance of authenticity. Guidance around fake EEAT content includes:
All of this indicates the importance of building up your EEAT over time, naturally, so that Google trusts your website.
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Google’s walled garden: Users make 10 clicks before leaving
A new study shows that Google keeps users on its own site longer with it’s new in-platform features, whereas ChatGPT sends them out to external sites, but Google still sends the most traffic overall. Users are now found to visit 10 pages within Google’s own platform before leaving or clicking out which signals that website owners need to ensure their SERP listings stand out as much as possible as it becomes harder to get organic clicks.
Read more here.
Using employees as influencers is on the rise
An increasing number of companies are turning to their employees to help raise brand awareness via social media. The 2025 Employee Advocacy Benchmark Report, presented by platform SocialPubli, analyzed employee data from the insurance, telecom and tourism industries. The results revealed that employee-shared content isn't just expanding reach, it's significantly outperforming traditional brand communications.
Read more here.
Agencies are building their own AI services
Agencies are developing their own AI services to help with the complexities in their interactions with clients. As agencies integrate AI into their offerings, questions arise about billing practices and the readiness of these AI products for client use. Client side leaders expect agencies to have AI capabilities, but making these tools client-facing is often a lower priority compared to other integration methods.
Read more here.