If you deliver personalized content or offers, and no one sees it, did it ever really happen?
Whether you're investing in A/B tests, multi-variate tests, targeted ads/offers, or cross-channel decisioning, you'll find that the technologies driving these experiences struggle with the "last mile" of personalization. The "last mile" refers to the time from when a decision to deliver content is made and ultimately that content or experience change is presented on the digital device.
Back in the day, there was a lot of chatter about flicker, which would happen if the content was replaced after the default content already loaded. In today's world, given the complexity and speed of digital, this challenge extends beyond the flicker and into two main questions:
This might seem like a simple thing to keep track of, but it is quite difficult in traditional marketing technologies. The impacts of poor data quality in this arena can be quite far reaching as typically your tests or decisions are not static but will instead adapt based upon the updated information.
So, if you have models being trained based on whether offers are working, but the offer was never seen, then you may wrongly train the models to believe that offer isn't working when it could be for a completely different reason as outlined above.
Visibility Detection 2.0 is the latest upgraded feature in the Celebrus CDP designed to provide protection from bias in the machine learning models as mentioned above. Visibility Detection 2.0 generates the most accurate insights into how visitors interact with targeted content, including:
If you are not sure whether your customer experience enhancements are hitting the mark, then reach out to us to learn more about how Celebrus can enable more accurate analysis and insights for your most important investments.