I don't like to get into the specifics of customer data platform features as far as defining the entire category. Getting into feature specifics is critical at the use case level, however.
It would be impossible to properly evaluate and then plan for the use of a customer data platform without really understanding how at least some features work. To be a customer data platform, there absolutely must be data collection capabilities. What things might a person interested in data collection want to know about customer data platform features? Here are five!
Thing 1: Some customer data platforms automatically collect a lot more behavioral (event) and experiential (state) data than the rest
All CDP should automatically collect some mobile/web data, but they don't all do it in the same way. Right now the spectrum is skewed to the point where there is a far end of the spectrum with just a couple systems like Celebrus Technologies that automate data collection needs for a variety of auditability, machine learning and other data science applications. It looks like Snowplow is heading there, too.
Most customer data platforms are more like the traditional digital analytics systems when it comes to automated data collection, meaning that if you are not collecting something there is no going back and figuring it out. You just have to start collecting it. For many use cases, you can start using it immediately. For learning use cases, you just have to wait until you get enough information.
It's not that the rest of the field of vendors is the same. Whether you are still searching, or already have a customer data platform, look really close. It may be that there are industry-specific features that you are not taking advantage of, or other capabilities that fit in nicely with the way that you think about customer data. For example, when context and user data is already being surfaced to a data layer, make sure the CDP uses this as a source of truth as opposed to other areas that may be less reliable.