Those who work in marketing are fluent in the language of attribution, meaning the assigning of credit for responses to ads and touchpoints that lead up to the point of sale. However, little time is spent discussing attribution in the context of CTV.
A CTV attribution model serves the purpose of crediting Connected TV advertising for ensuing actions. Also referred to as CTV, Connected TV is a device that embeds within a TV or connects to a TV to support streaming video. Everything from gaming consoles to sticks, set-top boxes, and smart TVs allows for CTV functionality.
CTV ads digitally appear within streaming video content including ads displayed on livestreams and even TV programs watched on streaming devices. Below, we provide a look at the logic in using CTV attribution models and highlight a couple of attribution models for reader understanding.
The Purpose of CTV Attribution Models
The different CTV attribution models tell the story of how CTV content sparks interest and drives sales. Data is used to calculate the efficacy of specific CTV ads to gauge the return on investment (ROI).
Use the right CTV attribution model and you’ll succeed in accurately monitoring viewer engagement to maximize interest and conversions. Savvy marketers alter CTV ad campaigns to bolster the impact of messages presented to the viewing audiences. Strategic alterations to CTV ads please customers and also enhance the return on marketing investment.
Proper CTV attribution facilitates narrowed targeting, making it easier to better understand viewer needs and desires. Effective CTV ads also enhance communication with viewing audiences.
However, no two CTV attribution models are exactly the same. The different attribution models empower businesses like yours to transmit the optimal messages at the perfect moments in time for maximum impact on the viewing audience.
The Basics of CTV Attribution
CTV attribution uses information from third parties and first parties to define the target audience and the IRP. IRP is an acronym that stands for Identity Resolution Provider. The target list is then transmitted to inventory sources such as OTT publishers and redirected to specific devices.
Information pertaining to ad exposure stemming from publisher logs and ad servers along with data detailing outcomes of both offline and online traffic is transmitted to attribution specialists for analysis. Once the report is prepared, it is transmitted to the inventory source for quality control before the transition to the marketer.
The workflow detailed above is symbolic of that used for the CTV environment yet the video ad is presented to homes through targeting criteria established by advertisers. Everything from viewer preferences to viewer demographics, behaviors, and geographic information matters a great deal.
Information such as viewer IP addresses, device identification, and the details of authentication are collected by third parties. The more information available for review, the easier it is to accurately match such “exposure data” to individual homes.
CTV attribution is made possible with the use of specific software and tools. The goal is to identify specific sources of traffic that function the best and then alter video advertising strategies for optimal results. Marketers rely on specific attribution platforms to gauge viewer visits along with ensuing actions then alter the focus as necessary.
Attribution modeling empowers advertisers to better understand the amount of money spent and earned on individual customers. In-depth analytics empower advertisers to better understand viewing audiences including their responses to individual ads.
The best part is today’s attribution software is developed ahead of time, meaning advertisers merely need to sign up for a specific attribution method, generate appropriate tags, and access informative reports with relevant analytics. An understanding of the merits and weaknesses of ad campaigns including the spend invested in those ads paves a path toward ensuring optimization and heightened conversions.
Examples of Attribution Models
The multi-touch attribution model is revered for accuracy. Employ the multi-touch attribution model and you’ll gauge users’ activity in the context of touchpoints that eventually move prospects toward the finish line of a purchase. The linear approach to multi-touch attribution credits all touchpoints along the buying journey.
The W-shaped model of multi-touch attribution highlights the last and first touchpoints, giving each equal credit. However, the W-shaped model also gives credit to the interactions that help identify sales opportunities in the first place.
The U-shaped multi-touch attribution model gives more weight to the first and last touchpoints while crediting midpoint results. The first and last touchpoints receive 40% of the credit while other touchpoints receive the remaining 20%.
Alternatively, the single-touch attribution model consisting of first or last-touch attribution credits the initial or final touchpoints for purchase. Though single-touch attribution sometimes unfairly credits one touchpoint, some advertisers insist those individual touchpoints are the most important in shaping prospect psychology.
