Anna Vintsevska
Karolina BendrykConnected TV (CTV) has become a popular solution helping marketers reach engaged audiences at scale. However, many companies find it challenging to measure the true impact of CTV ad campaigns. Fortunately, there are certain tools, techniques, and strategies that brands can use to understand the conversion and efficiency of their CTV ads.
In this article, we will explore the best ways to measure the impact of CTV advertisements. Here you will find the definition of CTV attribution, an explanation of its key types, core principles, challenges, and tips on maximizing CTV attribution.
What is CTV attribution?
CTV attribution is the process of measuring and analyzing how connected TV advertising influences consumer behavior. It considers desired outcomes, such as website visits, app installs, or purchases. CTV attribution connects ad impressions on CTV platforms to actions taken on other devices or channels. It helps brands understand the effectiveness of the CTV marketing campaigns. This approach involves various tracking methods like IP matching, device graphs, and cross-device identifiers. Brands can use insights on CTV attribution to understand which ads are working, which audiences are converting, and what is the output from media spend.
Why CTV attribution matters for advertisers
Let's define the main reasons why CTV attribution matters in the context of advertising efficiency. Advertisers should consider such a process because it:
Helps companies understand the direct impact of ad spend on sales, sign-ups, app downloads, and other important outcomes.
Allows marketers to determine ads and platforms that drive results when it comes to specific audiences, which helps them optimize campaigns in real time.
Provides insights on campaign performance and customer journey across different devices.
Supports marketers’ data-driven decision-making.
Offer insights on different audiences, which allows companies to enhance audience segmentation.
How does CTV attribution work?
CTV attribution takes a much more sophisticated approach to measuring the success of advertising campaigns, compared to traditional models. Instead of vague correlations, marketers get data that allows them to track direct cause-and-effect relationships between ad exposure and real outcomes.
One of the key aspects of CTV attribution is the "identity graph". Once any viewer sees a CTV ad on one's device, his or her IP address is added to this graph. If this person later makes a purchase with a phone or laptop, you can immediately attribute the sale back to the CTV impression.
Another important aspect of connected TV attribution involves tracking pixels and software development kits (SDKs). This helps companies collect valuable behavioral data, such as information on website visits, product views, and other important aspects of marketing.
It is also important to note that CTV attribution ensures cross-channel integration. Such platforms can collect data from various platforms, allowing marketers to see how their CTV ads work in combination with other channels.
Finally, CTV attribution allows marketers to measure offline campaign outcomes as well. This approach provides insights into store visits and in-person purchases. All thanks to tracking smartphone location data and synchronization with point-of-sale (POS) systems.
CTV advertising often involves sophisticated reporting tools that deliver a comprehensive analytical overview of campaigns and their performance. As a result, companies move beyond guesswork and get enough information to clearly understand the factors that drive their campaign's performance. This results in smarter strategies and reduced media waste.
Types of CTV attribution models
To leverage CTV advertising attribution properly, it is important to understand different attribution models. All such models provide unique perspectives and insights on the customer journey. Let's explore the ones that prove to be the most efficient and commonly used in the industry.
First-touch attribution
This model is quite simple, which is both its advantage and drawback. Such an approach gives full credit for a conversion to the very first interaction a customer has with your brand. This means that if a user sees a digital-out-of-home (DOOH) ad and, later, watches a CTV ad and makes a purchase, the credit goes entirely to the DOOH ad.
Last-touch attribution
This model is the complete opposite of first-touch attribution. It assigns 100% of the credit to the final interaction before conversion. If we consider the previous example, a CTV ad will get all the credit. The key limitation of such a model is that it disregards all the earlier steps that shaped the customer's intent.
View-through attribution
This model focuses on users who saw a CTV ad but did not interact with it directly. Such an approach is based on the assumption that an ad can influence the viewer's behavior within a set time window (typically from 1 to 7 days). For example, if the ad is displayed on Monday and there is a spike in web traffic on Wednesday, the view-through attribution model will connect the increase to the ad. The main limitation of this approach is that it is based on time-based assumptions rather than direct actions. In many cases, it may be hard to truly understand what drove the conversion.
Click-through attribution
This approach is quite straightforward and applies to interactive CTV ads, allowing marketers to track direct clicks from an ad to a landing page. Such a model is not very common due to CTV interactivity limitations. However, with the growing popularity of interactive CTV ads, click-through attribution has become more and more relevant.
Multi-Touch Attribution
Here is one of the most sophisticated CTV advertising attribution models. Multi-touch attribution (MTA) offers a more nuanced view by spreading credit across multiple touchpoints in the customer journey. For example, marketers can assign 30% credit to the first exposure, 20% to mid-funnel engagement, and 50% to the final click or purchase driver. The main drawback of such an approach is that it might be complex to implement.
Key challenges in measuring connected tv ad impact
Connected TV offers powerful ways to reach audiences, but measuring the efficiency of such an approach is quite problematic. Even though CTV advertising attribution models aim to solve this problem, there still remain significant challenges preventing marketers from evaluating the impact of their campaigns efficiently.
Fragmented ecosystem
The CTV landscape is highly fragmented. There is a significant number of platforms, devices, apps, and publishers. This leads to the lack of uniformity that makes it difficult to aggregate data across campaigns.
Limited clickability
CTV ads are, typically, not clickable. Without direct action from the viewers, it may be challenging to directly track engagement.
Cross-device attribution
Consumers often view ads on one device (like a smart TV) and convert on another (like a smartphone or laptop). Therefore, it may be challenging to understand which ad medium brings the impact.
Delayed conversions
CTV ads often serve as upper-funnel brand awareness drivers. This means that the actual conversion may happen days or even weeks after exposure. Delayed actions can be missed if attribution windows are too short or tracking methods aren't comprehensive.
Privacy and data restrictions
Privacy concerns continue shaping the domain of digital advertising. Various limitations that shape consumer privacy can also limit access to user-level data. This makes attribution more complex and less granular.
Lack of standardized metrics
There is no universal standard for measuring the outcomes of CTV campaigns. Some companies rely on impressions and completion rates, but there are not enough metrics for tracking viewer attention, engagement, or influence.
Lack of reporting consistency
The previous challenge leaves issues with reporting consistency. The point is that different publishers and platforms can focus on different definitions and methodologies while evaluating CTV ad campaigns. As a result, many marketers face challenges in evaluating campaign efficiency.
Best practices for accurate ctv attribution
Now, let's proceed with some tips that will help you overcome common challenges of CTV ads attribution. Here are some practices that are, from our experience, especially useful.
Rely on IP-based household mapping
Make sure to capture the IP addresses of households exposed to your CTV ads. Later, you will be able to match user activity to the IP addresses where the CTV ad was served. This will allow you to link household-level ad exposure to cross-device actions.
Use incrementality testing to measure true lift
Incrementality testing will allow you to divide the audience into two groups: one that views the CTV ads and another that doesn't. By comparing behaviors between these groups, you will be able to isolate the impact of your campaign and inform smarter budget allocation.
Treat CTV as a companion, not a replacement
If you want to ensure a broader campaign reach and better insights, do not focus on CTV as your primary channel. It should not work as a standalone strategy because it, typically, works much better as a complementary channel. You can find the gaps associated with other advertising channels and use CTV to fill attribution gaps and optimize overall campaign performance.
Use better tools to prioritize brand safety
Sometimes, it may be challenging to control where your ads appear. If you want to mitigate the risks of having your ads placed inappropriately, rely on adtech tools with robust filtering capabilities. This will help you ensure that your ads are displayed within brand-safe environments. This will also help you get more trustworthy attribution tracking.
Consider TeqBlaze as your trusted partner
Finding truly reliable adtech tools tailored to your specific needs can be a challenging task. One of the best options is partnering with a company that has a proven track record of successful adtech projects. Teqblaze is ready to help. Our team has solved many challenges for adtech companies, including the optimization of CTV marketing.
For example, engineered a white-label SSP+Ad Exchange platform that allows a U.S.-based company that specializes in CTV advertising to optimize their workflows. Our solution helps them establish, manage, and track their personalized advertising network.
We are ready to deliver CTV attribution solutions tailored to your needs or create a product from scratch. All to provide you with next-level campaign manageability and analytical features.
Final word
To understand the impact of your connected TV marketing campaigns, you must get into CTV attribution. This process might present unique challenges, but there are certain ways that will help you gain clarity. This list includes IP-based mapping, incrementality testing, multi-touch attribution, and reliance on tailored adtech solutions.
Suppose you want to get such software,partner with Teqblaze, an experienced adtech company. We will help you unlock the full potential of CTV and get powerful tools that allow you to track the impact of your connected TV campaigns.
