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Do You Even Data

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Why Data and Analytics Initiatives Fail

Recently, I attended the ANA Master of Marketing Week in Orlando, a super event.   But as I listened to speakers and participants, I heard “we implemented a data driven strategy, but it did not work”.

In a few of these sessions I was able to ask questions to explore why it failed. Here’s what I found.

Non-Discriminating Data for Desired Outcome:

There was a failure to discover the data that defined the human audience behavior—no primary research was conducted.   The firms simply grabbed the most convenient (read: path of least resistance) data.  There was no measurement of its actual ability to segment the audience, so it did not.

Poor data hygiene and data integration:

In most instances, the data was processed in its raw condition.  Best practices requires a series of steps to standardize, validate and correct the raw data (many marketers believed their vendor had completed this important step but later realized it was incomplete).  Data integration was inaccurate due to A.) lack of data structure—individual, household, address, plus B.) antiquated match code methods that can not link offline and online datasets necessary to personalize the customer experience (some best-known industry solutions consistently mismatch consumer records).

Black-box analytics approach utilized by untrained staff

For the past few years, many firms have offered a “Magic Wand” tool.  “You only have to input data and you will get the answer.”   This is not entirely correct.  You will get an answer, and not necessarily the right one.  In reality, you must have the education and experience to understand the first-party and third-party data needed to facilitate a good analytic outcome.   It’s important to delivering a transparent, defensible analytical method that can be evaluated by the non- analytically trained market experts.

Data Driven Marketing requires…

  • Primary market research to define the target audience
  • First- party or third-party data aggregated per the research findings
  • Analytical tools that can deliver the transparent conclusions with the speed and optimization required to serve the customer
  • Practitioners who can develop the appropriate analytics and deliver via the execution platform

Yes, I wish I could buy or license a Magic Wand.   But my experience has been that I must plan for the requirements I noted above. For more information, lets talk.

Mike Hail
Mike Hail
Mike Hail serves as CEO of Data Decisions Group. Previously, he has been CEO, Web Decisions Group, CEO, Yankelovich, CEO, Knowledgebase Marketing. With 41 years of marketing experience on both sides of the desk, Mike acts as the professional listener and interpreter for our client engagements. He focuses on the data and analytical aspects of our solutions.