4 steps to better data for better marketing decisions

As a Marketing specialist and data-driven mind, I am constantly seeking data and validation for my marketing and business activities. And probably you're doing the same. Analytical tools are everywhere, and they are inbuilt in the tools you use. There's no effort in using beautiful reports to prove your point. But that's all you're doing with that report: prove a point.

We all come with biases in our factory settings. The one that makes us use data to prove a point is the confirmation bias, defined as "the tendency to process information by looking for, or interpreting, information that is consistent with one's existing beliefs". Data is raw information, and your perspective will shape it and give it meaning.

Often, when marketing professionals are engaging with decision markers, they are using data just as a tool to craft consent, rather than a rational tool to analyze the market and consumer behaviour. It would be much more honest to admit you run that campaign based on a gut feeling, which would make it for a better explanation. It's unfortunate 'gut feelings' are not recognized as valid reasons to test ideas, so I understand in part the need to exploit data. The trouble begins when we believe that's a legitimate use of data, or when we need real growth in our business or in that of our clients'.

You won't notice your data is biased until you use it to predict customer behaviour, sales, or some other measurable activity and it turns our you were wrong. To make sure your data gets you closer to the truth, and allows you to craft meaningful marketing activities do this:

1 Minimize assumptions based on previous knowledge/experience/results. Look for context and avoid propagating the current state.. unless your data shows your current state is alright.

2 Use double-blind studies or any other tool you come across with to avoid confirmation bias or other cognitive biases in your research process.

3 Avoid analyzing data without a context. Business is always in a constant feedback loop. Analytics must?operate in real time, which means the data has to be business-ready to be analyzed and re-analyzed due to changing business conditions.

4 Don't get fooled by outliers: remove them from your survey to get more meaningful results. You would not consider Jeff Bezos when considering American mean income..

The amount of data we can have access to as marketers, is staggering. We can do incredible things and provide a real contribution if we pair marketing skills to data literacy. You can work on your data skills by taking less than $25 courses on Udemy. Check out this one.