Data Management and Marketing Automation - Video

In order to successfully move beyond the most basic drip marketing, it’s crucial for B2B marketers to effectively manage the data that they are working with. There are two main reasons that data has become more critical than ever before. First, it is with us for longer. As we engage with our prospective buyers earlier in the buying cycle, and nurture them throughout it, we are using the data for longer than ever before. Secondly, as we work to use marketing automation software to understand buyers, and then communicate with each buyer based on his or her unique needs, we end up using the data for various rules and automated systems.

When data is used by a marketing automation system for rules or automated systems, it needs to be clean and consistent. For example, in building a lead scoring algorithm, defining a target segment, or reporting on results, it is crucial that a title, an industry, or a country is represented in a consistent way so no contacts are missed.

In this quick but instructive video, Chris Petko, Eloqua’s Director of Marketing Operations talks about how we at Eloqua manage data, and how it is captured, cleansed, and analyzed. Chris introduces his 3 C framework and gives some great recommendations on how best to manage data as a marketing organization:



(if the video above does not load, please click here to watch Chis speak about marketing automation and data management)


Chris also discusses the Contact Washing Machine concept that automatically manages each and every data touch-point, and ensures that the data is cleansed and normalized. Chris discusses why this must be done inline, rather than as a one-time manual effort, given the way in that marketing data is continually updated via web forms, list uploads, and data flowing from other systems such as CRM.

I hope you enjoyed watching the video, and found Chris’s experience useful in your marketing operations. As someone who deals with marketing data on a daily basis, Chris has a lot of experience in exactly what aspects of data management matter, and how to approach it.