The “customer” in customer data platform

September 21, 2016 | By

This is part 1 of a series of 3 blogs about the C, D and P of CDP. 

Your probably know this by now but BlueConic is a customer data platform, or CDP. This still relatively new acronym was defined by David Raab in 2013 but has notably gained significant interest over the last year; in fact, Gartner added it for the first time to their Hype Cycle for Digital Marketing and Advertising. We started building our CDP in 2010, way before the concept even had a name. But what exactly IS it about a CDP that makes it what it is? Let’s dive in a bit more!

The first word in CDP is “customer,” so clearly a CDP is about your customers. But taken literally you probably would think that a CDP is just a CRM. After all, data about your customers is stored in your CRM, so why would you use another system for this? And if you have other systems, why not connect all systems to your CRM so you have all the relevant data in the CRM?

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There are two major reasons why there is a need to have another system for this:

  1. Most organizations struggle to realize the holy grail of CRM: storing all the customer data you have in such a system. There are several reasons for this: the explosion of marketing systems that all contain a bit of customer data if you want it or not, quite rigid data structures inside the CRM, organizational misalignment, and the fact that a CRM is not really designed to connect with *all* the technologies out there.
  2. Although David Raab calls it ‘customer’ data, most of the time what CDPs are about is not even about the customer (yet), but about anonymous visitor data. Let me explain: those anonymous visitors might be old customers, or potential new ones, but you don’t know for sure. Still, you want to store data about that individual right away because that currently anonymous visitor might be an incredibly valuable customer later. And storing all that anonymous information leads to an explosion of data, which most CRMs struggle to handle because they are not designed to handle billions of records – given that the percentage of your total audience that actually consists of known customers is typically pretty darn small.

That’s why CDPs are not based on a structured (relational) database but rather on a big data infrastructure, which in our case is Apache Cassandra. Big data databases are built to infinitely scale, meaning in the BlueConic case that we’re capable of handling billions of profiles. And CDPs are designed to integrate with any technology out there, have open APIs, and provide as many out-of-the-box connections as possible.

Keep following along for the next in the series:

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