Multi-Touch Attribution: Key Terms to Know for Successful Adoption
Once brands have gone through the significant effort necessary to implement a multi-touch attribution (MTA) solution, they are sometimes surprised to realize that adoption can easily be hampered by a lack of alignment among internal and agency teams around MTA-related terminology and KPIs—and how and where these concepts should be implemented in the day-to-day workflow. We find that early in the adoption process of multi-touch attribution, there’s often a longer-than-anticipated period of education required across brand marketer and agency groups.
Maybe the brand marketer is struggling with the overall concept of base propensity or feels like their particular brand doesn’t fit the approach because of various factors. (Examples include time in market, geographical limitations, investment in branding initiatives or lack thereof, and known obstacles in the customer purchase journey.) Or perhaps agency teams are frustrated by the new KPIs that come with MTA, when many of the more familiar, automated DSP optimization tools are built to maximize performance on last touch attribution, click rates, engagement, or video completion rates.
We often hear clients asking the same questions over and over as they get started, after their multi-touch attribution tool has been deployed.
If a brand marketer or agency team member is asking the same questions repeatedly and struggling with the overall concept of multi-touch attribution, the incremental value of marketing dollars, or how the statistical model works to assess and assign credit, it’s probably time to take a step back, define your terms, and dig in to specific questions using real numbers. Some learners are perfectly happy understanding just the theory behind how attribution works. But tactical and activation-focused teams often benefit from real examples using their own media and campaign data to dig in to attribution concepts. Incorporating incremental conversions, fractional conversions, incrementality percentage, and cost per incremental conversion into existing campaign and channel reports helps media buyers contextualize these new terms. Doing a deep dive on terms is a great start to help this adoption process.
Must-Know MTA Terminology:
Multi-Touch Attribution: A person-level attribution model that divides the incremental credit for a conversion across multiple digital media touchpoints, in an effort to more fully recognize the impact of all marketing touchpoints—including non-addressable factors (see below)—in a customer’s conversion journey.
Base Propensity: A customer’s inherent likelihood to purchase, independent of marketing exposure. Historical search, site visitation, and past conversion behaviors are measured and incorporated into the Neustar MTA statistical regression model. Then, they’re used to calculate the incremental lift in conversions after a customer is exposed to marketing, in order to assign only the incremental conversion credit to media. This differs from other MTA providers who ignore base propensity and assign all conversion credit to media, such as in fractional attribution or variations on last click or last view attribution.
Conversions: A conversion can be any offline or online action taken by a customer, and that’s valuable to a brand marketer because it impacts financial outcomes today or in the future—such as a sale, signing up for an email newsletter, visiting specific pages on a website, submitting personal data to get more information (e.g., lead generation), making an appointment for a visit, clicking to call, and talking to a customer service representative.
Total Conversions: All the conversions collected from whichever platform or platforms brand marketers uses to track conversions.
Non-Addressable Factors: Offline media or non-media influences that impact a customer’s likelihood to purchase are “non-addressable.” This refers to media that is not targetable to a specific audience, such as traditional linear TV, radio, and magazines, but also includes non-media elements like seasonality, competition, pricing, and weather.
Unattributed Conversions: Conversions that cannot be associated to a media touch are not assigned credit within the Neustar MTA model, since these converters were not touched or impacted by media.
Fractional Attribution: Assigns all credit for a conversion to media touches that occurred in the conversion path and does not assign any credit to the existing base propensity of a customer. Fractional conversions are all conversions that can be linked to a media touch.
Fractional Conversions + Unattributed Conversions = Total Conversions
Using fractional attribution to measure the performance of marketing will lead to incorrect and inefficient ROI and media allocations, as base propensity and non-addressable factors differ by customer and by conversion and can’t be averaged across all conversions.
Incremental Attribution: The Neustar MTA model aims to identify the impact of media on a customer’s conversion journey and assigns credit only to those conversions that were truly influenced by marketing. As such, incremental attribution within the Neustar MTA model refers to all marketing-contributed conversions.
Base Conversions: In contrast to incremental conversions, base conversions are those that were linked—but not attributed—to a media touch within the Neustar MTA model. These are conversions that would have happened without a marketing exposure, due either to the customer’s existing propensity to buy or due to offline and non-media impacts like linear TV, print, out-of-home (billboards), or the economy, pricing, and competition.
Base Conversions = Fractional conversions – Incremental conversions
Incrementality percentage: This is the percentage of media-touched conversions that are considered incremental and truly impacted by your marketing investment (and that would not have occurred without marketing exposure).
Incrementality % = Incremental conversions / Fractional conversions
Spending an office-hours session digging into reporting, defining terms, and showing how the MTA model assigns credit using a brand marketer’s actual data will build a strong foundation for adoption. It also encourages teams across both brands and agencies to dig into the data on their own by giving them the confidence to understand the true value of multi-touch attribution tools like the Neustar MTA solution. Once teams understand the value of multi-touch attribution and of using a common KPI across all channels, they are then ready to use these tools to plan, allocate, activate, optimize, and reallocate marketing budgets—with the end goal of increasing the returns on their marketing investments.