Prophet has released MMM101, a practical guide to Market Mix Modelling and how marketing teams are moving from reporting the past to rehearsing the future.
In one recent Prophet analysis, a consumer retail brand discovered a broader screen strategy spread across multiple digital video environments was 2.5-3x more efficient than television alone. Without modelling, that budget difference would have been invisible until after the campaign closed.
These gaps are not uncommon. Industry estimates suggest more than $6.1 billion of digital advertising spend in Australia is wasted annually on ineffective media, and almost two thirds of marketers say proving marketing’s financial impact is their biggest challenge. The data exists. The measurement frameworks most organisations rely on simply aren’t built to surface it.
Prophet also computes one of Australia’s leading financial services organisations – who spent upwards of ~$11 million in media in a group of campaigns to acquire roughly 40,000 new customers. But Prophet’s state of the art causal models revealed something attribution reporting had completely missed. That same marketing investment had also prevented the loss of up to 33,000 existing customers who would likely have churned without continued investment into both their brand and their delivered customer experience.
Without a full MMM, half the commercial impact would have remained invisible. And that’s exactly the problem that Prophet’s new guide addresses.
You can download the Ultimate MMM Guide here.
The measurement problem no one talks about
Marketing has never had more data.
Dashboards update in real time. Platforms report impressions, clicks, conversions and return on ad spend. Every channel arrives at planning meetings armed with metrics explaining why it deserves next quarter’s budget.
The problem is that most of those systems were built to answer a much easier question. What contributed? Not what actually created demand… and how?
Attribution models tend to reward the final digital touchpoint in a journey. Search gets the credit. Retargeting looks brilliant. Brand investment quietly disappears from the story.
Over time this creates a strange gravity inside marketing teams. Budgets drift toward the channels that are easiest to measure rather than the ones doing the heavy lifting.
Your best performing channel probably isn’t what you think
Real marketing journeys rarely follow a neat path.
A customer might see a TV ad on Friday night, hear a podcast ad during the Monday commute, scroll past a social campaign later that week and only search for the brand days later before finally converting. But by the time that conversion appears in a dashboard, most of the activity that actually created the demand has disappeared from the data.
In one automotive analysis by Prophet, modelling of more than 300,000 test drives found that over 37 per cent were directly influenced by marketing activity, rarely by a single interaction. Demand tends to build gradually across multiple channels before a customer ultimately converts.
It’s important to note that Marketing also is not the entire story.
The remaining demand often comes from forces dashboards rarely capture. Long term brand investment shapes preference well before someone enters a purchase journey. At the same time, broader market conditions quietly influence when people decide to buy.
Changes in consumer confidence, energy costs or global events can all shift category demand in the background.
Most attribution models cannot see those signals. Prophet’s model library incorporates more than 100,000 macroeconomic variables, covering everything from CPI movements and consumer confidence to weather, illness cycles and competitor activity.
The goal is simple. Separate what marketing drove from what the broader environment was already doing to demand. Because by the time the sale appears in a report, the marketing that sparked the intent, the brand investment that built trust and the market conditions that accelerated demand are often invisible.
The CFO question most dashboards can’t answer
This is where marketing and finance often begin speaking different languages.
Marketing conversations revolve around campaigns, channels and platform metrics. Finance conversations revolve around investment, risk and return. Those worlds collide during planning cycles when someone inevitably asks the question most dashboards struggle to answer… did this investment actually grow the business?
If the only evidence available is attribution reporting, the answer becomes complicated. Marketing can show platform performance. Finance is looking for commercial impact.
Brand investment often sits awkwardly in the middle of that conversation. CFOs are naturally cautious about spend that cannot be easily quantified, and brand rarely appears clearly inside attribution dashboards.
The channels that capture demand tend to get the credit, while the activity that created the demand in the first place becomes harder to see. That gap is where marketing credibility quietly erodes. Not because marketing is not working, but because the measurement framework cannot demonstrate how it works.
More complete measurement begins to close that gap by connecting marketing investment to commercial outcomes in a language finance teams understand.
The most misunderstood acronym in marketing
This is usually the point where MMM enters the conversation.
For years MMM has carried a reputation for being complicated or mysterious. In reality, the principle is straightforward.
MMM is maths. It’s that simple.
It’s a statistical model that isolates variables, quantifies their contribution and separates signal from noise. Instead of tracking individual user journeys across platforms, it analyses the entire marketing ecosystem and measures how changes in investment influence business outcomes over time.
Crucially, it also accounts for the external forces shaping demand. Economic conditions, seasonality, promotions and competitor activity all influence performance. When those variables are included in the model, organisations can begin separating what marketing actually drove from what would have happened anyway.
From explaining the past to rehearsing the future
The real value of MMM isn’t just analysing what already happened. It’s what happens next.
Advances in AI, machine learning and statistical modelling have made something new possible: simulating decisions before budget is committed, before campaigns go live, before the quarter even starts.
Instead of simply explaining the past, organisations can begin simulating the future.
- What happens if budget moves between channels?
- Where do diminishing returns begin?
- How does brand investment influence the entire system?
MMM alone was never designed to answer those questions. That required a new instrument.
Rather than producing static reports months after campaigns finish, Prophet is the simulation engine that allows marketing leaders to run the future before committing budget, testing scenarios, stress-testing assumptions and optimising investment before a dollar moves.
In practice, marketing planning starts to look a lot more like financial modelling.
Unsure about MMM? Good.
For many organisations the hardest part of MMM is not implementation. It’s recognising where the blind spots exist in their current measurement framework.
- Which channels are under credited?
- Which ones are over credited?
- Where might budget decisions already be drifting because reporting is incomplete?
- And what would change if you could simulate those answers before spending a dollar?
To help marketers navigate that shift, Prophet has released MMM101: From Measurement to Rehearsed Reality.
The guide explains how evolved measurement frameworks are helping marketing teams move beyond reporting and into simulation.
Download the guide to see how marketers are moving from measuring the past to rehearsing the future.
