Why You Need Mobile-Grade Measurement Before AI Can Deliver on ROI

UK marketers are entering a decisive phase. Digital advertising investment keeps growing, retail media and connected TV are becoming increasingly central to media plans, and artificial intelligence (AI) is moving from experimentation into everyday campaign operations. Yet, the basic commercial question has not shifted. Can marketers prove that each pound spent is generating measurable value?

That question is becoming more pertinent than ever. Digital ad spend is expected to reach £45 billion this year, with mobile accounting for over two thirds and online retail media emerging as one of the fastest-growing channels. The same research points to measurement fragmentation as a major industry concern.

AI and automation is reshaping how campaigns are planned, bought, and optimised. AI may accelerate decision-making, personalise creative, optimise bids, and expose recent pockets of demand. But if the underlying measurement framework is weak, AI does not solve the problem; it simply scales it. 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.

Mobile’s measurement edge

It is time to look at the mobile measurement playbook. Mobile advertising was forced to confront privacy constraints, fraud, cross-platform identity, and signal loss a few years ago. The result was a more disciplined method for attribution. Cleaner signals, stronger validation, privacy-safe methodologies, and a willingness to combine deterministic, probabilistic, and referrer-based approaches depending on the quality of the available data.

Those principles now require to be distilled throughout the whole UK media mix. Retail media may sit closer to the point of purchase, but it nevertheless requires transparent standards if brands are to compare outcomes fairly across networks. 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 too frequently those signals remain trapped in channel-particular reporting structures.

Blind spots cost growth

When marketers cannot connect exposure to outcomes with confidence, they hold back from channels that may be profitable. Research we undertook with EMARKETER found that nearly six-in-ten (58.6%) marketers believe their organisations are likely underinvesting in profitable channels because those channels require better measurement. 

In this environment, marketers must treat measurement as infrastructure, not as a reporting layer added following campaigns running. That means aligning definitions throughout teams, removing data silos, validating traffic quality, establishing privacy-compliant identity and enrichment processes, and measuring incrementality instead of relying solely on last-click or platform-reported attribution.

AI raises the stakes 

AI makes this shift more urgent. Our research showed that almost half of organisations (49.7%) said they were under significant pressure to demonstrate clear ROI across all channels, while a further 29.9% reported extreme pressure. That creates a new accountability challenge. Marketers must understand not only what an AI system recommends, but also whether the data feeding it is trustworthy.

That trust gap is already showing up in how marketers use AI. Poor data quality, driven by fragmented, incomplete, or unreliable signals, was the top-cited barrier to extracting more value from AI in the marketing stack, cited by 22.3% of respondents. AI-ready marketing data needs to be clean, deduplicated, consented, connected, and governed to be useful. If customer interactions across app, web, retail media, CTV, and CRM cannot be stitched together responsibly, AI will optimise against only a partial view of the customer journey. 

Lead with measurement

Marketers need to define measurement standards prior to scaling any AI investment. Marketers should agree which outcomes matter, how they are to be attributed, where incrementality testing is required and which data sources are approved for optimisation. 

Next, brands should assess partners on transparency. Publishers, retail media networks, ad tech vendors, and agencies all need to explain how they validate signals, reduce fraud, manage privacy constraints, and connect upper-funnel activity to commercial outcomes. In a market where regulatory shift and economic uncertainty keep shape planning cycles, vague measurement promises are no longer enough.

Thirdly, marketers should maintain human oversight where decisions carry material commercial risk. Automation may enhance speed, but human judgement continues to be essential when interpreting anomalies, challenging assumptions and deciding whether a recommendation fits broader business strategy. The goal is not to slow AI down, but to ensure it is acting on the right evidence.

Turn measurement into growth

The next phase of growth in UK digital advertising is expected to not be won simply by adopting more AI tools or shifting spend into emerging channels. Rather, it will be won by businesses that can prove what works, understand why it works and act on that insight rapidly. Mobile-grade measurement offers a practical blueprint: privacy-safe, fraud-aware, cross-channel and created for imperfect data.

The message is clear. AI may transform marketing execution, but measurement is expected to determine whether that transformation develops notable value. With budgets beneath scrutiny and digital media becoming further complex, the brands that create stronger measurement foundations now will be best placed to turn automation into accountable growth.

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Bio: Alex Grach is General Manager for EMEA at AppsFlyer, where he leads the company’s commercial strategy across the region. An INSEAD graduate with over 20 years across global enterprises, startups, and scaleups, Alex joined AppsFlyer at a very early stage and helped build it into a market leader. Over more than a decade, he has worked with some of the region’s most sophisticated marketing and product organisations across Financial Services, eCommerce, and Gaming, including Revolut, King, and Booking.com, helping them make better decisions, faster, at scale.

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