UK marketers need mobile-grade measurement before AI can prove ROI, AppsFlyer EMEA chief says

The article cites an IAB UK forecast that digital ad spend will reach £45 billion this year, with mobile accounting for more than two thirds of that spend and online retail media emerging as one of the fastest-growing channels. The same research points to measurement fragmentation as a major industry concern, while AI and automation are reshaping how campaigns are planned, bought and optimized.

According to the article, weak measurement does not get solved by AI; it gets scaled. A model trained on incomplete, inconsistent or poorly governed data can produce confident recommendations that move budget in the wrong direction faster than a human team can intervene. The piece argues that mobile advertising offers a useful playbook because it confronted privacy constraints, fraud, cross-platform identity and signal loss earlier and more intensely than most channels. That led to cleaner signals, stronger validation, privacy-safe methodologies and a willingness to combine deterministic, probabilistic and referrer-based approaches depending on data quality.

The article says those principles now need to be applied across the UK media mix. Retail media may sit closer to the point of purchase, but it still needs transparent standards if brands are to compare outcomes fairly across networks. Connected TV offers premium, brand-safe environments, but advertisers continue to struggle with fragmented measurement and the link between exposure and sales. Social, search, display and commerce media all produce valuable signals, yet the article says those signals too often remain trapped in channel-specific reporting structures.

The commercial consequence is underinvestment, according to the article. It cites research by AppsFlyer and EMARKETER finding that 58.6% of marketers believe their organizations are likely underinvesting in profitable channels because those channels require better measurement. The article says the finding is highly relevant to the UK, where media fragmentation, privacy regulation and economic pressure combine to make every budget decision more scrutinized. It argues that marketers should treat measurement as infrastructure rather than a reporting layer added after campaigns have run, aligning definitions across teams, removing data silos, validating traffic quality, establishing privacy-compliant identity and enrichment processes, and measuring incrementality rather than relying solely on last-click or platform-reported attribution.

The article says AI raises the stakes further. As AI agents and tools move across ad workflows, from creative production and audience selection to bid optimization and campaign analysis, advertisers are under pressure to prove ROI. The research showed that 49.7% of organizations said they were under significant pressure to demonstrate clear ROI across all channels, while 29.9% reported extreme pressure. The article says marketers must understand not only what an AI system recommends but also whether the data feeding it is trustworthy. Poor data quality was the top-cited barrier to extracting more value from AI in the marketing stack, cited by 22.3% of respondents, followed by explainability at 17.8%. In practical terms, the article says AI-ready marketing data needs to be clean, deduplicated, consented, connected and governed. If customer interactions across app, web, retail media, CTV and CRM cannot be stitched together responsibly, AI will optimize against a partial view of the customer journey, potentially improving a platform-level metric while weakening overall business performance.

The article's first recommendation for marketing leaders is to define measurement standards before scaling AI investment.