In the world of digital marketing, measuring the impact of programmatic ads is crucial for understanding the effectiveness of your ad spend. But how do we ensure that the results we're looking at are truly reflective of the campaign’s influence? This is where omnichannel attribution comes into play. In this post, we'll explore what is cross-channel attribution, how to measure attribution for programmatic ads, the key differences between post-click and post-view attribution, and why both types of attribution are vital for a more accurate understanding of your campaign performance.
Programmatic advertising enables advertisers to automate the buying and placement of ads using algorithms and data to target specific audiences. Attribution, in this context, is the process of identifying which touchpoints (e.g., clicks or views) led to the desired outcome, such as a conversion or purchase.
The goal is to understand the effectiveness of each ad impression, click, or interaction throughout the customer journey, so advertisers can optimize their campaigns for better results.
Post-click attribution measures the impact of users who interact with an ad and then convert (e.g., by making a purchase, signing up for a newsletter, or taking any other desired action). This type of attribution is often the go-to metric because it's directly tied to user actions that are quantifiable, such as clicks.
Example: A user clicks on a banner ad and then buys a product. The post-click attribution would give full credit for the conversion to that ad click.
On the other hand, post-view attribution measures the impact of users who view an ad but do not immediately click on it. This type of attribution recognizes that even if a user doesn't click on an ad, it may still influence their decision-making process later, which could result in a conversion down the line. This is especially important for brand awareness and upper-funnel activities, where the goal isn't necessarily immediate conversion but rather influencing future behaviors.
Example: A user sees a display ad but doesn’t click. However, a few days later, they visit the website directly and make a purchase. In this case, post-view attribution would give credit to the impression (ad view) rather than the click.
Platforms like Google Analytics and other web analytics tools often focus on post-click attribution and only give credit to the last click that drove the conversion. Last-click attribution in this case provides a clear connection between a user's click and the resulting conversion and can be tied to UTM parameters used in the landing page of the last traffic source. When users click an ad, the URL typically includes tracking parameters that analytics platforms can follow, allowing them to easily match that click to a subsequent conversion on the site.
However, this approach may overlook the post-view influence of ads. Just because a user doesn't click on an ad doesn't mean it didn't have an effect. Post-view attribution is more challenging to track because the interaction is more indirect, and there’s no immediate action that can be traced back to the ad. This is where ads manager platforms like Google Ads, Facebook Ads Manager, and DSPs come into play. These platforms tend to provide both post-click and post-view attribution metrics, offering a 360-degree picture of how ads are performing.
For advertisers, it's crucial to consider both post-click and post-view reports when evaluating the success of a programmatic campaign. By doing so, you can see how many conversions were influenced by simply viewing the ad, even if the user didn’t click on it.
For instance, while Google Analytics might show you a post-click conversion, your ad platform might show that the same user was influenced by seeing an ad earlier in the process. This dual view gives a more nuanced understanding of how your ads are driving value.
To improve the accuracy of your conversion reports from programmatic ad campaigns, here are a few tips to ensure you're capturing the full picture:
Many advertisers rely on last-click attribution, which gives credit to the final touchpoint before a conversion. However, this doesn’t always reflect the entire journey a customer takes. A multi-touch attribution model (MTA) is better suited for programmatic campaigns, as it considers multiple interactions a user has with your ads before converting, whether that's through clicks or impressions.
Platforms like Google Analytics provide multi-channel funnel reports, allowing you to see the complete customer journey across different ad channels and touchpoints. Combining this with post-view and post-click attribution will give you a clearer picture of how each ad interaction influences conversion.
Programmatic advertising often spans multiple platforms and networks. Using a data management platform (DMP) or a customer relationship management (CRM) system to integrate cross-platform data can help you track the entire customer journey across devices and channels. By consolidating this data, you can better understand how your programmatic ads are influencing users at various touchpoints and optimize campaigns accordingly.
Tracking pixels or cookies placed on landing pages or throughout the website help track users who have interacted with your programmatic ads. These tools allow you to measure both clicks and views more effectively, giving you more granular insight into user behavior. Be mindful of privacy regulations like GDPR and CCPA, as they may impact how you collect and store user data.
Tip: Make sure to capture data layers such as transaction_ID or order_value when tracking conversions in your ads platform. This can help you accurately attribute and measure conversions influenced by your media campaigns.
Oftentimes, the attribution window is set by default to a 30-day post-click and post-view. This may be a long time period for advertisers running performance campaigns. With Display and Programmatic ad campaigns, it’s common to see more post-view conversions and only a handful of post-click.
In order to reduce the discrepancy between 3rd parties analytics tools such as Google Analytics and your Ads Manager, consider adjusting the attribution window for conversion tracking to a shorter time frame (i.e. 7-day post-click and 1-day post-view), and optimize to focus more on post-click conversions vs. all conversions.
After gathering data from both post-click and post-view attribution reports, continuously optimize your campaigns. Use insights from how users interact with your ads—whether by viewing or clicking—to adjust targeting, creatives, bidding strategies, and other campaign elements. A/B testing different ad formats and messages can help you find the best-performing combinations for both immediate and long-term results.
Tip: Growth Channel DSP Conversion report can be used to match each of the attributed conversions to any source and identify post-click and post-view results.
Effective programmatic ads attribution isn't just about tracking the clicks; it's about recognizing the broader influence that ads have throughout the customer journey. By incorporating both post-click and post-view attribution models, advertisers can better understand how ads impact conversions, whether immediately or over time. Ensuring you're using the right tools and metrics to track both types of interactions will give you more accurate conversion reports, allowing for smarter optimizations and ultimately more successful campaigns.
As the digital advertising landscape continues to evolve, making attribution a central part of your marketing strategy will allow you to maximize ROAS and deliver more value to your brand.
