Analyzing data

I have always been fascinated by data. Especially analysis interests me as you can discover patterns that are not immediately visible. While my fellow students in university hated SPSS (statistics program), I could secretly enjoy all the results that I could get out of my datasets with the many options for statistical tests. That is why I also offer this as a service to my customers now. There are so many ways in which you as an organization already collect data but often don’t use it (fully). There are plenty of websites that exist but of which the statistics are rarely checked. Or apps that keep track of activity data but which is not used. And newsletters that are sent out every month but never analyzed. Or those internal company surveys that are only used to a small extent by making a summary of the answers. While you can look at multiple questions simultaneously and discover interesting patterns. It’s a waste not to do it as you invest a lot of time and money to create it. Many people say it is too difficult or it takes too much time. But what’s the point of continuing to do what you’re doing if you don’t know if it works?!

Getting more out of existing data

You can learn a lot from looking at numbers and making connections. For example, in the case of a company survey (fictional example): “Young employees suffer from burnout four times more often than older employees. And of those young employees with a burnout, 70 percent are planning to look for a new job.” That would mean that you could quickly lose a large part of your young staff and therefore have to do something to prevent that. But often the reports only contain a simple analysis with a distribution of the participants based on age, gender and department and then the answer whether they have already had a burnout and whether they are looking for a new job. Those static answers about how many men and women participated are much less interesting than answers you get by crossing multiple questions. Then you can work constructively with data to improve the situation and target people specifically.

But data can also help you with simple questions such as “when is the best moment to publish a blog article?” (for your target audience that is, there is no general answer to this). Your website, app, or newsletter statistics can help you discover if a message is best read at 3:00 PM or 8:00 AM for example. Or you can do an A/B test to find out how more people will open your newsletter. The possibilities are endless.

Let’s do it

So do you have any surveys you’d like to do more with? Apps, newsletters or websites of which you want the data analyzed on a weekly or monthly basis? Or are you looking for someone who can write clear reports and surprise you with new insights from existing data? Please contact me and we will discuss the possibilities.