By Dan Richardson, director of data and insights, Asia Pacific at Yahoo
Marketing measurement has always been a challenge, but never more so than today. While digital measurement was never strictly straightforward, it was a lot simpler as we had cookies, clicks and conversions to fall back on.
I only have to think back to my own personal experiences in the early days of search marketing, programmatic and trading desks to realise just how quickly our technology, and ability to measure, has changed.
Now signal loss from privacy changes, platform fragmentation, and an ever-expanding range of measurement methodologies have made measurement one of the most complex and resource-heavy areas for marketers. Agencies, publishers and tech platforms are all racing to keep up, but the reality is that no single solution fits all.
Dan Richardson
A perfect storm of factors has led to this untenable landscape of measurement complexity. Privacy-first changes from Google and Apple have diminished traditional tracking, while the rise of the multi-channel, multi-device and multi-platform world have meant attribution is a bigger question mark than ever.
At the same time, marketers have more measurement methodologies than they know what to do with. There’s marketing mix modelling (MMM), the rise of attention as a metric and privacy-enhancing technologies (PETs) like Google Privacy Sandbox. Data clean rooms are also gaining traction, enabling safer collaboration with data.
The result? Brands are overwhelmed. Yahoo’s own Pop Quiz research found that data knowledge is often siloed within a select few in organisations, meaning that the responsibility of understanding measurement – and data best practices more generally – is not shared within a team. This creates internal resistance to change, which is a significant drawback when things are changing so frequently.
This is an interesting phenomenon, especially when we consider new research from Skeleton Key which found that Australia is actually quite mature when it comes to data. However, we are held back due to a potent mix of weaknesses in organisational structures, tech stack implementation, challenges around privacy concerns, internal resistance and measurement methods.
The same research found that while Australians are willing to experiment, we are unsure of what solutions are available.
In other words, we are at a crossroads – where there’s an appetite to learn, but too many different paths and consequences to consider. But the simple truth is, if brands want to make sense of this new measurement landscape, simplification is key.
The cost of complexity
The explosion of measurement solutions has created an unintended consequence – many brands are prioritising quantity over quality. Some are collecting every data point possible, layering on multiple solutions in an attempt to gain clarity. But more data doesn’t always mean better insights.
The real challenge isn’t a lack of tools – it’s a lack of focus. Without clear business objectives, brands risk drowning in data without extracting meaningful insights. The most successful companies aren’t the ones adopting the most measurement tools, but those refining their approach based on what truly matters to their business.
So, how do brands cut through the noise?
1. Start with objectives, not tools: Too many marketers begin with the tools available instead of focusing on business needs. Instead, start by defining what success looks like and work backwards to determine the best measurement approach.
2. Prioritise data best practices: The urgency to adopt new measurement strategies has, in some cases, come at the expense of data hygiene. Privacy, compliance, and first-party data governance should remain a top priority for any marketer.
3. Avoid constant switching: The measurement landscape will continue to evolve, but jumping between strategies too frequently can dilute long-term effectiveness. Instead, invest in a framework that allows for flexibility while maintaining consistency.
4. Demystify measurement internally: Knowledge should not be locked within a select few in an organisation. Investing in education and cross-team collaboration can help businesses make better, more informed decisions.
At this stage, I’d be remiss if I didn’t mention how new AI-driven measurement techniques are becoming more prevalent and how optimisation has evolved. Once upon a time (or more accurately, about a decade ago when I joined Yahoo), it was almost a fireable offence to bore clients with talk of algorithms.
But in 2025, the reverse is now the truth. It’s AI’s time to shine, with algorithms becoming more composable and providing significant cost-efficiencies. It’s no wonder AI has become a real game changer.
Modelled conversions and synthetic data (such as AI panels trained on real human datasets) are also starting to shape the next phase of market research. But as with all new innovations, brands must evaluate these solutions carefully, ensuring they align with business goals rather than adding unnecessary complications.
At the same time, MMM is becoming increasingly prevalent as brands seek a long-term, privacy-safe measurement approach. However, it’s crucial to recognise the distinction between attribution and contribution. MMM offers a high-level view of what’s driving business performance, but it doesn’t replace attribution modelling, which helps track short-term, digital-driven performance. The best approach is a mix – leveraging both to get a full-funnel view of marketing effectiveness.
The old ways of measurement are deteriorating and the new landscape is complex – but that doesn’t mean brands should panic. Instead, this is a pivotal moment to build a solid measurement foundation that will last well into the future.
Rather than chasing every new solution, brands should take a step back, clarify their objectives and invest in a simplified, tailored approach. The future of measurement isn’t about finding the most solutions – it’s about finding the right ones.