It’s not every day you get to chat with the person who coined an industry-defining phrase.
That’s exactly what happened though when I sat down with David Raab, founder of the CDP Institute and the brain behind the term “Customer Data Platform” at this year’s CDP Live. Since David introduced the term in 2013, CDPs have gone through several evolutions, most recently brought on by the influx of AI and the never-ending race to meet consumers' real-time expectations.
In our conversation, David and I discussed the hotly contested debate between composable and packaged CDPs, how consumer behavior is reshaping the industry, and why data isn’t just a tool for personalization, it’s about future proofing customer engagement and loyalty long-term.
Read on for the highlights from our conversation and learn about some of the tectonic shifts happening in the customer data platform industry.
*This interview was originally conducted as part of our CDP Live Event, and has been lightly edited. You can watch the full conversation here.
Key takeaway 1: Composable vs. packaged CDPs debate is more about terminology than functionality
Robin Grochol: Recently, there’s been one conversation dominating the CDP landscape: the merits of a composable CDP vs. a packaged CDP. At Twilio Segment, we don't think it's as cut and dry as choosing one or the other. I'd love to hear your thoughts on this debate – why do you think it's such a point of interest recently?
David Raab: It’s certainly a hot topic in the industry. Composable is a technical term that means a system is comprised of components – not too shocking. But the way it's been used in the CDP industry is a little different: it tends to refer to systems where the data warehouse is built separately from the CDP.
It’s kind of how it was done before CDPs existed, an “everything old is new again” situation. Most people now refer to it as “warehouse-centric” or a “warehouse-based CDP” rather than “composable,” which is just semantics. Even though “composable” may not be the most technically accurate term to use...
The reason CDPs have evolved is that people decided they wanted a piece of packaged software to build that customer database, because most data warehouses weren't doing the job back then. And most IT departments would struggle if you asked them to do it.
But the argument being made is that data warehouses have evolved considerably since 2013. Now, it's plausible that you would have a data warehouse that could do what a CDP would do – which relates to building customer profiles.
So, collecting all the different data sources – not just structured data, which is traditionally what you're limited to in a warehouse – and merging it together to make those customer profiles available to other systems. Then, making it easy to add new data sources, which again, is a typical pain point for the traditional data warehouses.
The reality is that it depends on the company. Some have excellent data warehouses that actually are CDP-capable. Others, the data warehouse is built for analytical purposes, which is typical. But it certainly doesn't have the identity resolution needed to build customer profiles. It’s often missing a few other things as well, like connectors to marketing systems or applications in real time. Or access is another common gap in a data warehouse.
We're not saying it's impossible to construct your own CDP based on the components that you buy. But it isn’t something you should just narrowly assume: oh, yeah, we have a data warehouse, therefore we have a database that will work for us. Often the data warehouse will need substantial work, and then you get into the debate about which is more cost-effective. Is it to modify and enhance your data warehouse, or is it to go out and buy a package CDP?