In the Loop - September 2025
Welcome to the latest edition of ‘In The Loop’.
This month, Andrew . and Matt Bentley break down the most significant updates and rulings impacting digital marketing, analytics, and data privacy. We also talk about the transition to Google Analytics 4, and the benefits of integrating this data with your core customer data.
Happy reading!
The digital marketing and analytics space is facing a period of rapid regulatory change. From Apple’s privacy moves to sweeping EU laws and landmark court rulings, the message is clear: compliance, transparency, and adaptability are more important than ever. As always, staying informed and questioning vendor claims is the best way to navigate this evolving landscape
In this article, we discuss these changes, breaking down the most significant updates and rulings impacting digital marketing, analytics, and data privacy.
iOS 26: Privacy Changes and the end of GCLID tracking
Apple’s upcoming iOS 26 release is set to make waves in the digital marketing world. The headline change? Safari will now strip out Google’s GCLID (Google Click Identifier) from all browsing sessions, not just private ones. The GCLID is crucial for linking Google Ads clicks to analytics data, so its removal will disrupt attribution and campaign measurement for a significant portion of users, potentially 40–45% of internet traffic.
Apple’s rationale is to protect the privacy of their customers using their devices, but the move has left marketers scrambling for workarounds to continue to evaluate their marketing spend in the future. While some solutions are circulating on LinkedIn, the cat-and-mouse game between Apple and marketers is likely to continue. Notably, Apple’s approach is also impacting other unique identifiers, with some uncertainty around how Meta tracking will be affected or other popular marketing pixels.
The consensus? Marketers should prepare for more restricted tracking and attribution, especially on Apple devices.
Read the full article to know more about the other hot topics:
- Google’s Antitrust ruling: data sharing, not divestment
- Meta’s privacy breach: health data in the spotlight
- Four major EU laws: Data Portability, AI, Cybersecurity, and ESG
- Tag managers and consent
Making GA4 Data Work Harder
With the transition to Google Analytics 4 well established, we’re working with many large organisations to integrate this data with their core customer data.
The benefits are clear. By joining event level digital signals with transactional and customer profile data, Brands gain sharper reporting, stronger predictive models, and the ability to activate personalised experiences across their owned and paid channels. Here are three examples of how we've helped clients:
- eCommerce optimisation: Enhanced digital analytics, including offline events (e.g. cancelled sales) and customer-based filters (e.g. value segments)
- Enhanced ML & AI: Combined contextual digital signals of customer interest and intent with macro models
- New triggered activations: Followed up on specific digital behaviours with targeted email, SMS and app notifications
Integrating GA4 and core customer data sets
We see clients typically adopt one of two approaches:
- Process in Big Query and export key aggregate tables to your core data environment
- Export raw data tables directly to your core environment and process there
There are advantages to both and the right choice will depend on your unique situation. With continued improvements in GA4 feeds, both are increasingly rapid to deploy, with data joined and available to drive benefit within weeks.
Speak to Nicholas Edwards , our Head of Data Engineering & Analytics to find out how you can start seeing the benefits of integrated GA4 data.
We’re always on the lookout for interesting news and articles from across the industry. This month, we’ve been particularly impressed by…
"New research from Contentful surveyed 425 marketing decision makers (including 103 CMOs) to uncover the reality behind AI adoption in marketing. The findings reveal a massive "optimism-execution gap" that's fast becoming marketing's fault line. While nearly every CMO claims to prioritise AI, most companies still treat it as an experiment rather than infrastructure."