Monday, May 5, 2014

Why You Are Not Getting The Expected ROI From Marketing Automation (Part 5


Your Data is Dirty

Overview: We have already discussed the “Three Ps” how your undefined process leads to staffing with the wrong skill sets and an automation platform designed without process. Now let’s look at a notorious thief robbing you of your ROI: dirty data.

According to the Journal of Industrial Engineering and Management[1], “Poor data quality can imply a multitude of negative consequences in a company… The implications of poor quality data carry negative effects to business users though: Less customer satisfaction, increased running costs, inefficient decision-making processes, lower performance and lowered employee job satisfaction.”

Not convinced? According to the Harvard Business Review[2], “Studies show that knowledge workers waste up to 50% of time hunting for data, identifying and correcting errors, and seeking confirmatory sources for data they do not trust.”

These articles are only reference technically “bad” data, meaning the data record itself is either incorrect or incomplete to the point of creating an erroneous decision outcome for which the data record was designed to support. In addition to technically bad date, there is also a class of data that, although technically correct - is equally ineffective because it is off-purpose. In our marketing and demand gen world, that could manifest as technically correct records for contacts who are not in our target market(s). For instance, my company sells supplies to restaurants and I have a database full of contacts for hair salons. This might mean I’ve got a great contact record for Judy, who will never buy a Pizza oven from me. Correct, but useless.

Let’s return to our hammer factory for another analogy to our “marketing factory.” (Again, apologies to manufacturers, as these illustrations are definitely oversimplified.)



Our hammer factory requires raw materials to manufacture the two component parts. The hammer head requires steel and the handle requires wood. But will any old steel and any old wood do? Of course not! Nobody wants a hammer that may or may not disintegrate on impact when striking a nail, so a great deal of diligence goes into the specification of those products to insure they meet the requirements of the hammer being manufactured. In fact, there are organizations, such as the American Society for Testing and Materials (ASTM) and American National Standards Institute (ANSI) whose sole purpose is to establish testing systems and grading criteria for materials such as wood and steel.

Your marketing and demand gen raw materials are data. Just like steel and wood in the hammer factory, your data must meet specific criteria to meet an acceptable use standard. You can begin to assess your data quality standards by answering a few simple questions.

·       What are your standards for data quality?
·       Who is responsible for creating and maintaining your data standards?
·       How do you know if your data meets your standards?
·       Who is responsible for enforcing your data standards?

Are you thinking of your Demand Center data in this way? What can you do to course correct if you discover you have no data standards or nobody responsible for those standards?

Notes:

Commit to your process first. Your Marketing Automation Platform can only do what you tell it to do. If your process is not well defined and engineered to accomplish your marketing goals, your platform will only help you make the same mistakes faster and at a higher volume.

Think small (like those extremely successful Volkswagen ads from the sixties and seventies). Your platform should be engineered to follow a process of communicating very defined messages to a very targeted audience. If you are continually sending large batches to broad audiences, you will soon email your database into extinction.

Think like a factory designer. Allow your platform to do the work it does well and let skilled specialists perform those tasks they do well.

DO NOT rely on “best practices.” The best practice for one organization may be the worst for another. I don’t even refer to best practices, but rather “best principles.”

Test, test and test some more. Are you validating your demand generation practices? Think of your optimization process as a never-ending game of “king of the hill.” The current process champion only remains champion if that process can defend against every challenger.

People, Process and Platform – the Three P’s. For the past five weeks, we’ve talked about how to conceptualize your demand center as a “marketing factory.” We’ve used the oversimplified analogy of a hammer factory (my apologies to anyone out there who manufacture hammers – I’m sure this oversimplification doesn’t nearly capture the true complexities of your process) to view the concept in a bit of an abstraction.




[1] Journal of Industrial Engineering and Management, “The Costs of Poor Data Quality”, Anders Haug, Frederik Zachariassen, Dennis van Liempd, January, 2011
[2] Harvard Business Review, “Data’s Credibility Problem”, Thomas C. Redamn, December, 2013

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