Multi Touch Attribution (MTA): What is the Right MTA Model, and How Can Your Team Measure Success?

Digital audience tracking – once considered avant-garde – has become a critical component of media measurement for media agencies and advertisers. Those failing to make this transition are under pressure from advertisers and media platforms and have even been stripped of Media Rating Council (MRC) accreditations.

According to Axios, Nielsen’s recent acquisition by Evergreen Coast Capital is directly related to the company being “…under extraordinary pressure to modernize its media measurement capabilities as dozens of new firms launch to take its market share.” They are a mix of newcomers and established companies like Catalina, which have aggressively expanded their capabilities.

Why you should trust a vetted solution like Catalina

Catalina was founded 38 years ago and transformed the retail landscape with its Shopper Intelligence Platform, which provides a deep reservoir of anonymized household transaction and behavioral insights for personalized marketing.

But this was only the beginning of our quest to revolutionize CPG marketing. Three years ago, Catalina developed the fastest, most granular attribution measurement products in the industry. And in 2021, our number of measured campaigns increased by 55% versus 2020 due in large part to our MultiTouch Attribution (MTA) product, which measures multiple media channels, ad creative, and audiences at the UPC level to optimize total campaign conversion while in flight.

What is MTA and how is it leveraged to find and convert your most relevant shoppers?

Catalina’s MTA measurement product helps answer the marketer’s age-old question, “What in this campaign is or is not driving a purchase?” MTA works by tagging a mobile, digital OOH, or CTV ad with a pixel or by ingesting an exposure file, which is anonymously matched to buyers via Catalina’s ID map. That UPC-level tracking reveals buying behavior patterns that are reported daily to the MTA dashboard.

Classic attribution methods (like first-touch, last touch, linear, time decay or linear) rely solely on conversion data and are biased toward channels delivering the most impressions. This does not work well when high volumes of impressions from digital channels mix with OTT/CTV channels, typically leveraging fewer impressions.

In contrast, Catalina’s Markov model considers the paths to conversion and non-conversion to calculate which channel differentially provides the best probability of conversion.

Catalina’s MTA also includes a comparison to competitive brands and analyzes new and existing buyers. The most popular benefit, however, is its ability to measure ad creative, giving marketers the ability to understand which messaging resonates more so they can quickly shift budgets to maximize results.

For example, one of Catalina’s clients used MTA to conduct A/B testing of a specific set of psychographic segments with two :30 TV spots featuring different product variants. The brand discovered one target audience was 50% more responsive to advertising. It optimized its TV impressions after five weeks and the campaign ultimately delivered a 4.3% sales lift.

To learn more about how your brand can benefit from our real-time measurement solutions, reach out to us.