What Is View-Through Attribution (VTA) And How Does It Work?
by Frankie Karrer
7 Min Read
8 Min Read
Marketing is a dynamic field full of ever-evolving strategies and techniques designed to captivate audiences, spark interest, and drive business growth. For marketers eager to enhance their return on investment (ROI), the key to allocating resources effectively and fine-tuning strategies for maximum impact is a good marketing attribution model.
There are many types of attribution models, guided by just as many philosophies on the best way to measure campaign effectiveness, but they all have the same goal: to accurately assign credit to the various touchpoints or interactions a customer has with a business prior to completing a purchase or another desired action.
A strong marketing attribution model helps businesses understand which of their marketing activities — such as social media posts or email campaigns — are responsible for getting customers to take action.
It can be intimidating to implement attribution models into your marketing strategy — they require both time and resources and getting them wrong can result in misguided decisions and wasted efforts. However, the potential benefits outweigh the initial challenges.
Have you ever struggled to make informed decisions about which marketing strategies to prioritize or which channels to invest in to drive better results?
Attribution models can help by providing clear and data-driven insights into your customer’s journey. You can see which touchpoints resonated best with your target audience and use that information to determine which resources to invest in.
Every dollar counts in marketing, and attribution models can improve your finances by providing insights into which strategies and channels offer the best ROI.
With this insight, you’ll have a better understanding of how to invest your budget.
Attribution models analyze the performance of each touchpoint; when taken altogether, this data should make clear which of your strategies are succeeding and which are falling short so you can proactively avoid pitfalls and overspending.
Plus, as trends and customer behavior evolve, attribution models will highlight emerging patterns that can guide your adjustments and help optimize your campaigns in real-time, ensuring you remain relevant to your audience’s preferences.
As a marketer, understanding how your customers go from being curious about a product to taking action is critical.
Attribution models help you see the full picture of your customer’s journey and how it leads them to convert. You’ll see insights into their specific touchpoints, such as ads they’ve clicked, emails they’ve opened, or social media posts they’ve engaged with.
This is a tricky one, but thanks to attribution models, you’ll get a clearer picture of which marketing efforts are paying off. Your marketing attribution model helps to connect the dots between different marketing activities and the results they bring.
You’ll be able to see which campaigns, channels, and strategies are driving the most impact, enabling you to adjust your approach and invest your resources where they make the most difference.
First-touch attribution models give credit for a conversion (like a purchase or a signup) to whatever the first touchpoint your customer interacted with on their road to pulling the trigger was.
First-touch attribution is easiest to measure, as it focuses only on the initial touchpoint that introduced customers to your brand.
Alternatively, the simplicity of first-touch attribution may cause you to overlook later touchpoints that contribute to the full conversion process. (You might not remember the very first time you saw an ad for a brand you recently purchased from, but you probably remember a few other spots in the middle.) First-touch often lacks important insights into a customer’s overall journey and undervalues long-term customer relationships.
Last-touch attribution models focus on the final touchpoint or interaction in a customer’s journey of either making a purchase or following through with a desired action.
Last-touch, much like first-touch, is easy to implement and understand, making it suitable for straightforward attribution needs. It also helps allocate resources efficiently by focusing on touchpoints that are closest to the conversions themselves, which means they may be tipping the scale.
Alternatively, last-touch overlooks earlier touchpoints and may miss out on vital stages of a customer’s journey. It provides an incomplete picture of the conversion path, limiting understanding of customer intent.
Linear attribution models assign credit equally to all touchpoints during a customer’s journey, regardless of whether the interaction occurred in the beginning, middle, or end.
Linear attribution provides a fair representation of the entire customer journey and acknowledges the multifaceted nature of customer decisions by considering all touchpoints.
Because equal credit is assigned to all touchpoints, the customer’s journey may be oversimplified and cause misrepresentation of any one touchpoint’s impact.
Lead-conversion touch attribution models are more complex. They identify and assign credit to specific touchpoints that are believed to play a specific, decisive role in converting leads into customers.
Lead-conversion touch attributions provide a better understanding of interactions and when they happened along a customer’s journey. This tailored view highlights touchpoints that drive actual conversions.
There’s less focus on earlier interactions that may have played a critical role in building the customer’s interest before conversion. As such, it may overlook touchpoints that contribute indirectly to a conversion.
Time-decay attribution models are based on the idea that the closer the touchpoint is to the conversion, time-wise, the more credit it deserves for that conversion.
Time-decay offers a more nuanced understanding of interactions that have impacted a customer’s journey over time. It allows you to recognize how touchpoints significance change as they get closer to conversion and helps you understand the evolving dynamics behind a customer’s decision-making process.
Alternatively, time-decay downplays the importance of earlier touchpoints that initiate a customer’s interest in your products and services.
U-shaped, or position-based, attribution models assign most credit to the first and last touchpoints in a customer’s journey. Some credit is assigned to middle points as well.
U-shaped attribution offers insights into the entire customer journey, recognizing the significance of different stages of engagement and providing a complete view of impact and intent.
Though it takes into consideration the customer’s whole journey, u-shaped attribution still puts significant credit on the beginning and end touchpoints. Interactions between those points may be neglected. (What if the final touchpoint, for example, is a banner ad that just reminded the customer of the hilarious CTV ad they saw a few days ago that they’ve been meaning to look up? With u-shaped attribution, the banner ad may get more credit than your clever commercial.)
W-shaped attribution is like u-shaped attribution with one extra emphasis. It assigns credit to three touchpoints in a customer’s journey ― the first, middle, and last touchpoints. The first touchpoint is considered the “introduction,” the middle is the “consideration,” and the final is the “conversion.”
W-shaped attribution emphasizes brand exposure, consideration, and conversion by crediting the first, middle, and last touchpoints.
While w-shaped attribution models look at the whole picture of a customer’s journey, there may still be some neglect for interactions that happen outside the initial, middle, and last points.
No two businesses are exactly alike, which means no two attribution models need to be identical, either. Custom attribution allows businesses to define their own rules for assigning credit to different touchpoints, enabling a better focus on personalization and specific business goals.
With custom attribution, you can tailor your model to fit your specific business objectives and customer behavior. Custom attribution is flexible and offers insights from different models.
Custom attribution requires more analysis and resources when implemented and may present unique challenges to strike the right balance among different touchpoint credits. It’s complex, which means it’s easy to misunderstand or miscommunicate results.
Choosing the right attribution model depends on a few factors. Consider your business objectives, customer journey complexity, how many marketing channels you use, and the nature of your products and services. Compare your business structure with each attribution model’s strengths and weaknesses, and choose one that best aligns with your goals.
Choosing and implementing a marketing attribution model isn’t always clear-cut. There are a few common mistakes that can hinder the effectiveness of a chosen model. You might:
There are two other commonly used attribution models in marketing, cross-device attribution and cookieless attribution.
Cross-device attribution refers to the process of tracking a user’s interactions across multiple devices, including smartphones, tablets, and computers.
Cookieless attribution is the practice of tracking user interactions without relying on traditional internet cookies, which can be helpful where privacy is concerned.
Multi-touch attribution is a method of tracking and assigning value to multiple touchpoints along a customer’s journey to understand their combined impact on a conversion or sale.
View-through attribution is a measurement method that credits a conversion to a display ad that was seen, but not clicked on, by a user before taking a desired action or making a purchase.
Traditional TV advertising often relies on the linear attribution model. Unfortunately, there are some downsides.
For example, the linear model assigns equal credit to all touchpoints and lacks accuracy in representing airtime, content, and audience engagement. This can lead to an oversimplified understanding of TV ad performance.
MNTN is changing attribution modeling on Connected TV (CTV) with Verified Visits™. Unlike traditional linear models, Verified Visits™ relies on automated source validation and refuses credit for site traffic from other sources. This means all measurements come from a viewer’s interactions with a CTV ad and subsequent visits to the advertiser’s website, typically within a specified timeframe.
Verified Visits™ is perfect for performance marketers eager to precisely measure the direct impact of their CTV advertising campaigns on driving viewer engagement and subsequent website visits. Where linear models fail, Verified Visits™ succeeds by offering a complete solution to utilize source validation and ensure accurate credit allocation.
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