There’s been a lot of buzz lately around the topic of cross channel attribution or offline attribution, as marketers try to figure out how to better measure the performance of their media campaigns. However, many marketers only look at offline attribution in a very narrow sense, which is strictly defined as attributing conversion events happening outside of media to an online media event. As a result, they miss out on the greater campaign optimization opportunities brought along by their offline attribution processes.
Some forward thinking marketers have been using their offline attribution processes as opportunities to fine-tune their campaign attribution models, which lead to significant performance improvements. The reason behind this is the offline attribution processes allows advertisers to insert their own analytic and conversion filtering processes into the media buying cycles, resulting in flexible and effective attribution models.
To get more value out of offline attribution processes, advertisers need to do the following:
- Understand the main objective of their campaigns and identify the converters or the type of conversion events that would drive the most ROI.
- Filter conversion events accordingly. For example, a retailer can group their converters into multiple categories based on the amount they spend in store, and only bring those converters who spend more than $100 into the media buying platform as conversion events for attribution.
Intelligent media buying platforms use machine-learning algorithms to find more prospects with similar characteristics as these high value converters, target them online, and result in higher ROI for the advertisers.
The attribution model is extremely crucial to campaign optimization and performance. Please consider your offline attribution process as a golden opportunity to build a custom-tailored attribution model to extract the most ROI out of your media buys.