{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Humans of Martech","title":"95: Battle of the CDPs: Packaged vs. Composable, 10 experts weigh in","html":"","width":"100%","height":180,"duration":3627,"description":"What’s up everyone, today we’re taking a deep dive into customer data and the stack that enables marketers to activate it. We’ll be introducing you to packaged customer data platforms and the more flexible options of composable customer data stacks and getting different perspectives on which option is best.\nI’ve used both options at different companies and have had the pleasure of partnering with really smart data engineers and up and coming data tools and I’m excited to dive in.\nHere’s today’s main takeaway: The debate between packaged and composable CDPs boils down to a trade-off between out-of-the-box functionality and tailored flexibility, with industry opinions divided on what offers greater long-term value. Key factors to consider are company needs and data team size. But if you do decide to explore the composable route, consider tools that focus on seamless integration and adaptability rather than those who claim to replace existing CDPs.\nThe 8 Core Components of Packaged CDPs: What the Experts Say\nOkay first things first, let’s get some definitions out of the way. Let’s start with the more common packaged CDPs.\nA Customer Data Platform (CDP) is software that consolidates customer data from various sources and makes it accessible for other systems. The end goal is being able to personalize customer interactions at scale.\nI’ve become a big fan of Arpit Choudhury of Data Beats, he articulates the components of a packaged CDP better than anywhere I’ve seen in his post Composable CDP vs. Packaged CDP: An Unbiased Guide Explaining the Two Solutions In Detail.\n8 packaged CDP components:\nCDI (Customer Data Infrastructure): This is where you collect first party data directly from your customers, usually through your website and apps.\nETL (Data Ingestion): Stands for Extract, Transform, Load. This is about pulling data from different tools you use and integrating it into your Data Warehouse (DWH).\nData Storage/Warehousing: This is where the collected data resides....","thumbnail_url":"https://img.transistorcdn.com/4eBcAi2MlxuVPdaWgcnwbeXVYH5naGhZe-qIuSYOdjU/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9hZGE5/NTRiZjYwMDI0NWM5/MmE4MDQ1NWJlODA3/MjUxYy5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}