Attribution is a mess. Every brand wants a clean, precise way to measure what’s driving conversions. The last decade saw the rise of Multi-Touch Attribution (MTA) models, but as privacy changes and tracking limitations disrupt the landscape, the industry is rapidly shifting.
Matt Bahr, CEO of Fairing, has spent years at the forefront of marketing measurement, both as an operator and now as a SaaS vendor. His view? Different channels demand different methodologies.
The Myth of the One-Size-Fits-All Attribution Model
Marketing is multi-touch. A customer might see an ad on Instagram, search on Google, get an email, and click a retargeting ad before purchasing. So which touchpoint gets credit? Traditional models force an answer where there isn’t one.
This directly challenges the marketing industry’s tendency to seek a silver bullet. Attribution is context-dependent: what works for paid search won’t necessarily work for influencer marketing, and what works for brand awareness campaigns won’t fit direct-response advertising.
Multi-Touch Attribution (MTA) was supposed to fix this. It failed. The model assumes you can track every touchpoint and assign accurate weights. That’s impossible with today’s privacy restrictions and cross-device behavior. The result? A tangled mess of guesswork disguised as precision.
Then there’s Marketing Mix Modeling (MMM). It’s great for high-level budgeting but fails at real-time decision-making. It looks backward, not forward. And Incrementality? It’s a strong tool but fragile — misinterpret the data, and you’re worse off than before.
The Case for Channel-Specific Attribution
Instead of trying to force one methodology on all channels, Bahr advocates for a hybrid approach:
- Surveys for unbiased, holistic measurement. Most attribution models rely on platform data, which is inherently biased. Surveys cut through that noise by capturing self-reported data directly from customers. Done right, they reveal patterns that no pixel can.
- Simplified MTA for creative insights. Rather than trying to track every touch, a stripped-down version of MTA can be useful. Bahr suggests focusing on two key moments: discovery (first exposure) and decision (last touch before purchase). That tells you what’s introducing customers to your brand and what’s sealing the deal.
- Regression-based methods for incrementality. The most exciting shift in measurement is the rise of causal analysis. Rather than just tracking correlations, brands are now running structured tests to measure true lift. This approach, while complex, delivers the most meaningful insights on what’s actually driving sales.
Where the Industry Is Headed
Bahr sees a future where there is rise of causal analysis in marketing measurement.
“More brands are thinking in terms of cause and effect for the first time,” he says.
This means moving beyond correlation and trying to isolate true impact. It’s not easy. Variables must be controlled, and noise must be removed. But it’s the best path forward. Brands that invest in this level of rigor will make smarter, more confident decisions.
Causal analysis, often executed through incrementality testing, doesn’t just track correlations — it measures the true effect of marketing efforts.
This approach helps marketers answer critical questions:
- Would this customer have converted even without seeing my ad?
- Is my marketing spend truly driving additional revenue, or just capturing demand that already existed?
Incrementality testing is complex and easy to get wrong. “Removing all of the noise from an incrementality test is quite difficult,” Bahr warns. External factors — like influencer promotions, seasonal trends, or overlapping ad placements — can muddy the results. However, when executed correctly with right expertise and tools, it provides the most accurate picture of what’s actually working.
As Bahr succinctly puts it, “I think we all have a lot to learn, but it’s definitely moving in the right direction.”
The Path Forward: Smarter, Not Simpler
If Bahr’s insights make one thing clear, it’s this: the future of marketing measurement isn’t about making things easier. It’s about making them smarter.
Teams that cling to outdated, oversimplified models will keep wasting money. Those that embrace complexity — and seek truth instead of convenience — will gain a competitive edge.
In 2025, the choice is simple: evolve or be misled.
This article is based on a recent podcast conversation between Matt and Pranav Piyush, CEO of Paramark—a platform used by modern CMOs and CFOs at fast-growing companies to understand marketing’s incremental impact, run experiments, and forecast results accurately.