If you have been in a marketing conversation recently, chances are MMM came up. IAB Australia published its first dedicated market mix modelling landscape report in 2025. The conference circuit is packed with measurement sessions. Mi3’s end-of-year roundup named MMM one of the defining topics of the year, with one CMO describing it as ‘flavour of the month, although we don’t really know what it is.’
That last quote is more honest than most. There is genuine momentum around MMM in Australia right now, but also genuine confusion. Understanding why this is happening, what has actually changed, and whether your business should be moving is what this article is about.
Three Things Happened at Once
The resurgence of marketing mix modelling is not the result of a single breakthrough. It is the convergence of three trends that, taken together, have made traditional measurement approaches increasingly inadequate for the way Australian marketers now work.
Privacy: Third-party cookie deprecation, iOS tracking restrictions, and the tightening of the Australian Privacy Act have steadily eroded the individual-level tracking that digital attribution was built on. When you can no longer reliably follow user journeys across the open web, aggregate measurement approaches like MMM become substantially more valuable. This is not a theoretical future concern. It is already affecting the reliability of measurement data in most Australian marketing operations.
Channel complexity: A marketing strategy that spans free-to-air television, YouTube, Meta, search, podcasting, out-of-home, and retail media cannot be accurately measured by any attribution model. The number of touchpoints and the complexity of how they interact exceeds what click-through tracking can capture. MMM, which analyses investment at an aggregate level, handles multi-channel complexity in a way that attribution structurally cannot.
AI: The traditional constraints on MMM, the time it took to build a model, the data volume required, and the specialist expertise needed to run it, have been substantially reduced by machine learning. What used to take three to six months of external consulting engagement can now be delivered in hours or days using AI-powered platforms. This changes the economics of MMM entirely.
The three forces reshaping measurement in Australia: privacy legislation reducing tracking signals, channel complexity outpacing attribution, and AI making MMM accessible to more businesses than ever before.
What the Australian Numbers Show
IAB Australia’s Market Mix Modelling Landscape Report 2025 is a useful benchmark for where the local market sits. It profiles twelve active MMM vendors operating in Australia and identifies accelerating adoption as a direct response to reduced attribution signals and the impact of privacy legislation. IAB industry engagements point to increased usage of both MMM and experimentation across major Australian advertisers.
WARC’s Future of Measurement 2025 adds global context that is directly relevant here. The proportion of marketers using experimental measurement techniques doubled in a single year, from 18% to 36%. And yet only 2% of marketers are using the full combination of attribution, experiments, and MMM together.
That 2% figure is important to sit with. It tells you that while awareness has grown sharply, most businesses, including most sophisticated Australian businesses, are still in the early stages of building a measurement capability that actually matches the complexity of how they market. There is urgency and opportunity in that gap simultaneously.
Source: IAB Australia, Market Mix Modelling Landscape Report 2025; WARC, Future of Measurement 2025
What Has Actually Changed for the Businesses Using It
The version of MMM that most people have heard of, the expensive, slow, consultant-led annual project, is not the version that exists today. The practical experience of using modern MMM platforms is meaningfully different across three dimensions.
Speed: Traditional MMM was periodic. A consulting team would gather 18 to 24 months of data, spend weeks building a model, and deliver a report that reflected market conditions from three to six months ago. By the time insights reached the marketing team, the campaign was long finished. Always-on AI-powered MMM updates continuously from live data sources. The insights are current, not retrospective.
Accessibility: Historically, meaningful MMM was the preserve of Australia’s largest advertisers, the Telstras and ANZs that could justify the cost and sustain the data infrastructure. AI-native platforms have changed both the cost structure and the data requirements enough that growth-stage businesses, not just enterprise advertisers, now have a genuine path to useful modelling.
Actionability: Older MMM outputs were often too abstract to drive immediate decisions. Modern platforms are built around scenario planning and forward-looking simulation, not just historical analysis. The output is designed to answer ‘what should we do next quarter’ rather than ‘what happened last year.’
What Businesses Are Getting From It
Beyond the methodology, it helps to be specific about the practical outcomes.
The most immediate benefit is usually in budget allocation. Understanding marginal returns by channel, and the exact investment level where a channel stops generating proportionate results, enables allocation decisions that gut instinct or dashboard data cannot support with confidence. ANZ’s marketing team describes mix modelling as the tool that enabled genuine investment trade-offs across its newly unified marketing centre of excellence.
Scenario planning is a close second. Simulating the revenue impact of different allocation strategies before committing a budget removes a significant element of guesswork from the planning process. The conversation in a budget review changes when you can present a modelled forecast rather than a historical assumption.
For many CMOs, the most strategically significant benefit is the ability to properly measure the contribution of brand advertising and upper-funnel channels. These consistently show the softest numbers in traditional attribution because their effects are diffuse and delayed. MMM captures them directly, and that is often precisely what is needed to defend brand investment in a conversation with the CFO.
ADMA’s 2026 outlook makes this point from a different angle: ‘Performance marketing has become table stakes. Brand differentiation is the real ROI.’ That is a strategic claim, but it is also a measurement claim. You cannot defend brand investment in a room with a CFO using click-through data. MMM gives you the commercial language to do it.
Source: AMI, ANZ commercial mix modelling; ADMA, Future Ready: 5 Forces Shaping Marketing in 2026
So Should Your Business Be Using It?
Let’s be straightforward about this.
If you are spending meaningfully across more than one or two channels, making budget decisions that would benefit from better data, and have at least 12 to 18 months of marketing and sales history, then yes, some form of marketing mix modelling is worth exploring seriously. The barriers that historically made it inaccessible, cost, timelines, and specialist expertise, are no longer what they were.
If you are very early stage, running a single channel, or have limited history, the timing may not be right yet. The value of MMM scales with the complexity of your marketing and the significance of your allocation decisions.
What is clearer than at any previous point is that the conversation has shifted. IAB Australia has published a vendor landscape. Twelve providers are actively competing for the Australian market. Telstra, ANZ, and Domain are among the brands that have committed publicly to mix modelling approaches. Mi3 named it one of the top marketing stories of 2025.
The question is not whether MMM is relevant to the Australian market. It clearly is. The question is whether your business is positioned to use it well, and what kind of platform suits where you are right now.
Find out what Mortar AI’s always-on MMM platform can reveal for your business. Get in touch today.
