What is Cross-Channel Attribution and Why is it Difficult?

Cross-channel attribution is the process of measuring the impact of a marketing campaign across multiple channels and attributing that impact to specific channels. In order to maximize ROI and allocate spend effectively, marketers need to be able to measure cross-channel attribution. Unfortunately, this isn’t always an easy task. 

What is cross-channel attribution?

Cross-channel attribution is the process of splitting credit between different channels when a user converts. For example, if you have a user who clicks on an ad and then installs your app through the Play Store, where does the conversion point occur? Is it with the click? The install? Maybe it was just because they were already planning to download an app from that category. Or maybe they would've never tapped on your ad if it weren't for a friend mentioning how neat your product is in passing conversation at work. It's difficult to say for sure which channel was responsible for bringing these two events together—but one thing's for certain: we are all getting better at attributing conversions across multiple channels as marketers become more sophisticated with their analytics tools (and as consumer behavior continues to evolve).

Why is it important?

Now that we’ve covered the basics of cross-channel attribution, let’s discuss why it’s so important.

• Cross-channel attribution helps marketers allocate spend across channels and optimize campaigns based on results. In other words, it lets you see which channels are working best for you, and where to focus your efforts in order to get the best results.
• Cross-channel attribution helps marketers understand the impact of campaigns across multiple platforms. This means that if someone saw an ad on Facebook but ended up buying your product on Amazon later that day, you can attribute sales directly to those initial ads—not just to Amazon as a whole (which would be a very bad thing). In addition, if they visited your site or watched one of your YouTube videos before making their purchase decision—and did not buy anything—you can also attribute this action back to digital advertising as well as other offline activities like word-of-mouth referrals and store visits.

Why is it hard?

The difficulty comes from the fact that:

• There are multiple channels, touchpoints and data sources to account for.
• There are multiple metrics to consider.
• There is no standard for which channels and touchpoints should be used in a cross-channel attribution model.
• There are few tools that support this type of modeling effectively.

The lack of standards results in companies having to develop their own models, which can then lead to inconsistent results across different brands' campaigns (and those of even the same brand).

Cross-channel attribution helps marketers better allocate spend and maximize ROI across their channels.

Cross-channel attribution helps marketers understand how different marketing channels affect customer behavior. It provides a mechanism for measuring and analyzing the impact of multiple channels on a customer’s journey.

When you think about cross-channel attribution, it’s important to remember that one of your goals is to better allocate spend across channels by understanding their value and ROI.

The key to cross-channel attribution success

So, what does it mean to be “good” at cross-channel attribution? There are a lot of different ways to define this. But we think that the best way is by looking at how well an attribution model handles the challenges described above and others related to them (such as high latency). If you can use a system like Rockerbox, that handles these problems well—for example, by making sure that your data is always up-to-date so you can accurately measure what people are doing across all channels—then you’ve got yourself a good model! 

With Rockerbox, you can piece together the entire customer journey. Rockerbox helps you to execute better in-channel optimizations and stop wasting money on channels that aren’t performing. We take the frustration out of constructing clean, actionable data, empowering you to accomplish your goals without the need for additional technical resources.