Alexia Nakad, from AppsFlyer, discusses why affiliate marketing needs a standardised set of metrics to determine what success looks like.
We’ve seen this before. A fast-growing channel explodes into dozens of touchpoints with every platform claiming credit. Leaving well-meaning affiliate and marketing teams struggling to stitch together incompatible reports to answer one basic question: did it work?
Whenever spend dissipates across various ecosystems, the same problem arises. Each walled garden tells a persuasive story about its own impact. However, affiliates need a single, defensible view of truth.
This isn’t just an analytics problem, but an operating one. If you can’t measure outcomes consistently across channels and devices, you can’t optimise. If you can’t optimise, you can’t confidently budget investment levels. And because customer journeys are now inherently cross-environmental (web to app, online to offline, one device to another), measurement and attribution have become harder than ever.
The problem with incompatible metrics
The problem is structural. Marketing is increasingly distributed across multiple ecosystems (search, social media, streaming, marketplaces, apps, and in-store). Each with its own reporting and definitions of success.
While well-meaning brands are being forced to reconcile apples-to-oranges metrics across tools that were never designed to work together, it is often affiliates that are missing out.
In many ways it reminds me of mobile advertising in 2012. Fragmented channels, competing claims, limited ability to reconcile performance across platforms, and no neutral arbiter of truth. Mobile eventually standardised around independent measurement partners that sat above individual networks to help brands allocate budget based on outcomes, not opinions.
Such a trusted measurement and decision layer is what is needed today, too. Something that can reconcile results across platforms, validate performance against real outcomes, and enable optimisation without forcing anyone to compromise privacy.
This ‘truth layer’ would allow teams to move from reporting to decisioning, and from decisioning to repeatable growth.
Why neutral measurement matters
We all know that AI can be a powerful accelerator. But only when it is grounded in the right underlying signals. AI can be used as an intelligent layer that sits on top of validated measurement. It can ingest high-volume, multi-network performance data, to identify patterns faster than any human, and recommend actions that improve efficiency.
However, to be effective, it requires clean, comparable, and independently governed data. Otherwise, it simply helps teams make the wrong decisions faster.
Neutrality matters. A measurement partner can’t be incentivised to favour one media seller, platform, or methodology. Teams need results that can stand up to scrutiny from analytics, finance, and the board. Independent measurement can provide an objective benchmark for what is working, what is not, and where the investment should go.
Turning collaboration into measurable value
It’s also important to differentiate between measurement and data collaboration.
Measurement answers what happened, when, and why. Data collaboration enables organisations to work with combined datasets to activate audiences, evaluate outcomes, and unlock new revenue streams. But collaboration doesn’t work on goodwill alone.
The preconditions the market assumed, reciprocal data, agreed valuations, mutual trust between brands and affiliates, have often proven harder to meet than anticipated. The real unlock isn’t better infrastructure. It’s measurement that delivers value to both brands and affiliates without requiring either to go first.
This can be seen most clearly in categories where one party influences demand while another controls the transaction.
Consumer brands, for example, often don’t own the direct purchase relationship. This makes it harder to close the loop between media spend and business outcomes. It may be easy to measure impressions and clicks, but much more difficult to prove which investments ended up driving sales.
Retail media is a prominent example of this broader dynamic. Brands may spread spend across multiple retail media networks, each reporting its own ROAS and attribution logic. Yet retailers often run their own offsite campaigns under managed service models.
But, without independent attribution and a shared framework for incrementality, trust erodes on both sides.
Building the operating system for marketing growth
This is where the modern measurement stack becomes key. An independent attribution foundation that can become the truth layer is imperative.
One that is a privacy-centric collaboration mechanism that allows brands and their affiliates to use shared signals responsibly, and an intelligence layer that turns measurement into decisions, and decisions into execution.
Only when the layers stack up can marketers move from reporting after the fact to optimising in real time and be able to shift spending to what works.
The stakes are rising for today’s CMOs. They are responsible for brand and performance, acquisition and retention, and increasingly, for proving commercial impact. In that environment, measurement is no longer a technical detail, but the operating system for decision-making.
As channels continue to multiply, the winners won’t be those teams with the most dashboards, but those with an optimised measurement layer that is neutral, privacy-safe, and built to translate data into action.
Alexia Nakad is the general manager, western Europe and the Middle East, for AppsFlyer.
