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How to make sense of data

For years, marketing experts have made decisions for their respective organizations based upon intuition. With technological advances providing an immense amount of data at our fingertips, how do you sift through and ultimately make sense of it? Let’s find out.

How to make sense of data


The marketing field has changed over the years, with many specialists making decisions with a “gut feeling.” It was once industry-standard as often it was about how a marketer felt, driving them to make instinctive decisions rather than ones with data involved. For the most part, this was due to the lack of statistical analysis companies could conduct, even 20 to 30 years ago. Nowadays, analytics provide comprehensive, actionable insights into what’s working and isn’t. They’re not everything, but they matter.

As much as humans like to take credit for their intuitive decisions, we’re imperfect. Not that data is close to perfection because it can easily be skewed. But it’s often more objective than people, and we want objectivity in a world of biases. Because data is often presented poorly, with too many figures and not enough substance, people are generally hesitant to trust it. It’s easy to draw parallels, but high-level business professionals, such as CEOs, want to know the reason behind them.


Part of the issue surrounding data is how much raw information is involved. If you take the average person and sit them down in front of 20 pages of data, they’re likely to turn and walk away without taking anything useful from it. Whereas, if you break that data down into easily digestible content, focusing on bullet point topics and displaying charts, the odds of your intended audience walking away with practical analytics knowledge increases substantially.

Once you whittle down the data into understandable sections, it’s time to make sense of it. Creating sensible data first involves realizing that it is constantly changing and will never be the same. Because your company had a successful February in 2020 before the global pandemic doesn’t mean it did in February 2021. Many factors go into any business’s success, such as supply and demand, emerging technologies, etc. Yet, there are key variables you can expect to impact your data yearly or even monthly.

Let’s say you’re a hotel chain in a popular Florida city. Well, during spring break week, you’re likely to see a rise in how many individuals stay at your hotel. You can’t compare this period to every other week in March or during the year because the data is innately skewed. But you can expect, not count on, this week in March to spike for your hotel yearly. You can also compare it to other relative years when spring break occurs to measure how you’re performing against yourself. The point is, it’s not about how much data you can collect, but what you do with it.


The point of aggregating data is to provide an organization with key insights into what’s working so they can make the most effective business decisions moving forward. Insights provide tangible correlations between implemented strategies, campaigns, and their results. By analyzing and understanding variables and trends, you’ll be well on your way to producing conversions. Perhaps the most important word in data is conversion. Organizations ultimately want to see if whatever concept they’ve infused into their strategy is working. But they must remember, and you may have to remind them, that there is much to be gained outside of conversions.


Not all data is weighed the same. You want to segment your data to get the most use out of it, which goes back to remembering data is dynamic, continuously altering and developing once you think you’ve figured it all out. Sometimes, a planned strategy doesn’t work the first time around, and it doesn’t mean it never will. It helps to execute well-thought-out, constructive ideas several times before removing them from a plan. The same goes for methods that work the first time around. You want to have consistent results. Only then do you make notes of what works and doesn’t.

That’s the ultimate goal of data, to benefit the entirety of your organization and its success, simultaneously bringing attention to breakthroughs and areas of improvement. The beautiful thing about data is it’s not specific to work, either. You can use analytics from your personal life to become a better version of yourself. For example, you can compare how you’ve reacted under different stressful circumstances. If you’ve noticed an uptick in positive responses and mindfulness during those situations, that’s a personal breakthrough. Accessible, valuable data extends far beyond the walls of your workplace into your life, so be sure to make sense of it.

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