Friday, July 12, 2024

5 steps to stop the marketing data hypnosis

Are you sitting in the same weekly metrics meeting staring at your data, or are you using it? These five steps can take you from observation to action, and results.

The tools that are available to the average multidisciplinary marketer do not make this easy. Dashboards and platforms are data-fragmented and immature. By trying to be comprehensive, analytics vendors have made applying the data they generate difficult. Dashboards tend generally to trend toward repetition, complexity or ‘ignorant’: they don’t prioritize or connect data points so that action *can* be taken.

And complexity is the enemy of action; in environments where multiple platforms generate different data sets that essentially compete for attention, data can’t just support decisions, it must also *identify* decisions that need to be made.

This inhibits and slows action. Without a specific outcome focus it is almost impossible to act. Outcome focus means getting rid of data distractions and getting tunnel vision. Data is highly distracting and can lull us into dashboard hypnosis or analysis paralysis; the most useless data can be mesmerizing and so interesting you can almost be convinced there’s a way to apply it.

There isn’t. Like any strategy, marketing data strategy is about what NOT to do.

And there is much measured today that does not need to be. I love Twitter, but does anyone need a Twitter impressions metric? What action can you take once you know it? What affects it going up or down? If you can’t influence an outcome or take action from data, then it’s just data masturbation. (not that there’s anything wrong with that, but it won’t help you improve your programs.) Always ask yourself: why am i looking at this number? What am I going to do with it? And if there is no good answer, stop collecting it. Tunnel vision when it comes to managing marketing programs is not a bad thing, and there’s a reason why racehorses wear blinders.

These steps are goal-oriented but tactical and can get any program past the initial hurdles of going from observation to action underway. They can also roll up into an overall benchmark and performance dashboard, but don’t need to start that way. Also, this is an approach that doesn’t require an actuarial degree; the stats are subject to the goals and not the other way around. The focus makes the variables and outcomes clear, especially since you’ve set up the subsequent actions up front.

  1. Set 3 goals you want to achieve, why they matter, and define the time period you want to achieve them in. (“more leads from Twitter” “10% more email addresses in three months” or “know what 5 categories of our content get the shares leading to visits”) – it will work best if these are testable in a short time frame and without a lot of complexity to start.
  2. Establish the metrics that you’ll need to understand to see if you’re meeting your goals. (This should be relatively simple to do; if it’s not, you may need to look at your goals again)
  3. Define the data you need to capture to get the metrics. Do you have all the tools in place to gather this now? If not are there manual workarounds you can use until your requirements are defined?)
  4. Establish the action(s) you will take and when ( if scenario a happens we will b. If scenario d happens, we will c).
  5. Run your tests, and presto, you have actionable data- and actions to take!
    Then try a new set of goals. Avoid data scope creep and get you and your organization hooked on the metrics that will help you get better. Seeing actionable data can be addictive. A healthy addiction – one that might even make you a better marketer.

Did you try it? Did this approach work for you? We’d love to hear your experiences with a focused data approach.

Photo by Blue Fountain Media, Flickr


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Jennifer Evans
Jennifer Evans
principal, @patternpulseai. author, THE CEO GUIDE TO INDUSTRY AI. former chair @technationCA, founder @b2bnewsnetwork #basicincome activist. Machine learning since 2009.


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