What Are the Basics of Attribution?
As marketers, we use the word attribution in many ways. Attribution quite simply is applying appropriate or earned credit to the marketing touchpoint that led to a conversion. Typically, attribution is attempted through one or more methods such as first-touch, last-touch, and Multi-Touch Attribution (MTA).
Attribution, at its core, is the process of assigning credit for a conversion, such as a purchase, subscription, or lead, to the marketing touchpoints that influenced it. Marketers have long relied on attribution to understand which campaigns, channels, and tactics are working, and to make decisions about where to invest budget.
Historically, attribution was handled through simple rules-based models such as first-touch attribution (credit goes to the first interaction a customer had with the brand) or last-touch attribution (credit goes to the final interaction before conversion). These models are easy to implement but provide only a narrow view of the customer journey.
To improve on this, MTA emerged as a more advanced approach. MTA attempts to assign fractional credit across all observed touchpoints leading up to a conversion. The promise of MTA was appealing: a detailed map of the customer journey and precise allocation of credit across channels. However, while this method worked reasonably well in a cookie-based, click-driven digital world, its effectiveness has declined sharply as the marketing landscape has evolved.
Today, consumer journeys span multiple devices, browsers, and channels. Privacy regulations, third-party cookie deprecation, and the rise of Walled Garden platforms (such as Meta, Google, Amazon, TikTok, and Snap) mean that complete user-level tracking is no longer possible.
As a result, MTA now paints an incomplete and often misleading picture. It tends to over-credit measurable clicks and under-credit media that builds awareness or drives conversions indirectly. This is why MTA, on its own, is no longer sufficient for modern omnichannel marketers.
What Are the Basics of Incrementality?
Incrementality measurement takes a fundamentally different approach to answering the attribution question. Instead of trying to stitch together individual customer journeys, incrementality aims to determine the true causal impact of a marketing activity.
The methodology relies on experimentation. Audiences are split into test and control groups, where one group is exposed to the marketing treatment (such as ads in a particular channel) and the other is not. By comparing the conversion behavior between these groups, marketers can isolate the incremental lift attributable to the media.
This answers the key business question: How many conversions would not have happened if we hadn’t run this campaign or spent in this channel?
Incrementality provides clarity where MTA struggles most: channels where impressions are difficult or impossible to map at the user level. These include Walled Garden social platforms (Meta, TikTok, Pinterest, Snap), as well as offline channels like TV, direct mail, and streaming audio. Unlike attribution models that rely heavily on trackable clicks, incrementality captures the real contribution of both impressions and clicks, giving a more complete and unbiased picture of performance.
Another advantage is that incrementality is not constrained by user-level data availability. Even as privacy restrictions limit tracking, incrementality experiments can be designed using aggregated data, making them future-proof compared to older attribution techniques.
Why is There An Attribution Challenge?
The attribution challenge arises from the widening gap between what marketers want to measure and what data they actually have access to.
For most channels or platforms, MTA cannot measure views or impressions, so you’re essentially just measuring clicks. Incrementality measurement, however, accounts for the impressions and clicks within each of the platforms under test and therefore gives marketers a more accurate view of the true contribution of their media across their entire portfolio.
- Limitations of MTA: Most MTA models are blind to ad exposures that do not involve a click. For example, a customer might see multiple ads on Instagram and then search for the brand on Google before converting. Traditional MTA will often give full or disproportionate credit to Google Search, undervaluing the role of Instagram impressions. As marketers invest across an expanding mix of digital, offline, and emerging channels, this problem only compounds.
- Fragmentation and Privacy: The modern media ecosystem is fragmented across dozens of platforms, many of which restrict data sharing. Privacy regulations (GDPR, CCPA) and the decline of third-party cookies make user-level tracking increasingly unreliable.
- Shifting Consumer Journeys: Consumers rarely move linearly from awareness to conversion. Their paths are messy, nonlinear, and spread across multiple devices and platforms, further challenging traditional attribution models.
Incrementality measurement addresses these challenges head-on. Because it relies on randomized comparisons, it inherently accounts for the effect of impressions, clicks, and brand influence across all channels, without needing to observe every touchpoint. This allows marketers to move beyond directional “best guesses” toward evidence-based insights into what’s truly driving growth.
The Modern Takeaway
In today’s environment, MTA alone is no longer enough to guide budget decisions. It can provide directional insights for digital channels with clear click paths, but it fails to capture the bigger picture. Incrementality is now the gold standard for determining causal impact.
At Measured, we recommend that marketers take a triangulated approach, combining incrementality testing with advanced Media Mix Modeling (MMM) and selectively using platform-reported attribution. This integrated measurement framework provides both the breadth (portfolio-level view) and depth (channel-level causal impact) needed to make confident, data-driven decisions in a fragmented, privacy-first world.
To learn more about incrementality measurement, please read "The Essential Incrementality Playbook for Marketers," and get in touch with a Measured expert for a demo.