Our most popular piece of content is easily the ebook about the differences between customer data platforms and data management platforms. It’s in the weeds and perhaps more exhaustive than some marketers want when they’re asking, “What’s the difference between a CDP and a DMP?” So I thought I’d make the contrast a little more direct and succinct, because in our humble opinion:
- Losing data after 90 days is stupid. Picture it: you’ve spent all this time figuring out what data you want to collect about your customers and your campaigns, etc. and you’re running all these great analyses. It’s awesome. Until…day 91. When you start losing data because the cookies expire. Suddenly, that historical analysis? Less potent. That customer journey you’re trying to construct? Way fragmented. That unified customer view? Not so much. User profiling is a marathon, not a sprint.
- Black boxes of data suck. There’s a really annoying commercial on TV where people whine, “But it’s my money and I need it now!” Marketers should feel the same way about data: if you’re collecting it, you should have full and total access to it. That way, if you have questions about reports, for example, you can go in and understand the analysis rather than just cross your fingers and trust that what the DMP is spitting out is right. If you can’t trust your data or know what’s going on with it, what’s the point?
- It’s crazy to wait two weeks (or more) for a segment. Need we say more? If it takes your DMP 2+ weeks to build a segment, there’s virtually zero chance that segment is still accurate. So much happens in the consumer’s decision journey in two weeks that attributes describing them change after two hours, nevermind two weeks. A segment definition that isn’t updated in real time is old. Two weeks is just pointless.
- Engagement and interests matters even more than age and gender. They say love is blind – to age, gender, race, etc. But love is definitely not blind about whether or not you have traits in common or share passions. So why as a marketer would you limit yourself to more or less static attributes when it comes to understanding your audience? Things like their level of engagement, interests, and typical behaviors. Nuggets of information that paint a much richer picture of the individual and how best to engage with them.
- Data shouldn’t have an artificial shelf life.
- Unfettered data access is non-negotiable.
- Real-time segments, full stop.
- Know the individual, not the categories that they fit in.