Google is collecting data. Facebook keeps getting in trouble for the data it is collecting. Maybe you are collecting data? Or, you're pretty sure you should be collecting it, but are not quite sure what you'd do with it if you did? The truth is, data is the foundation for good decision making and how you turn your data into action makes all the difference. Read below to learn how to turn data into information and information into action.
A data point is an observation or measurement, say the temperature or the date. When data points are organized into a consistent structure they form a dataset. A well-structured dataset is the basic building block of information, containing data points collected in a consistent manner. To collect good data, define and standardize the data you capture. For example, ensure you capture data with a consistent unit of measure. Additionally, design your collection process, including when and how you capture and record data, to collect your data in the same way each time. By ensuring you capture data consistently, you will be able to build a dataset that yields meaningful information.
For example, say you want to measure your social media presence. One data point you might collect is the number of people who view your posts. Since that number changes over time, you need to define when you will collect the number of views on a post and then do that consistently for each post. One approach would be to record views one day, one week, and two weeks after each post is made. At a minimum, your record would include the date the post was made and then the number of views at each collection point. You will want to record these data points in an easy-to-analyze format, like a spreadsheet or a database.
The characteristics of your dataset are the information you will need to determine action. These characteristics are typically statistical calculations like the average, standard deviation, range, and median. Taken together, they begin to form the story that your data is telling you, guiding your analysis and helping you make better decisions.
Going back to measuring your social media presence, you might calculate the average number of views across all of your posts to understand your typical reach. You could also calculate the standard deviation in the number of views to understand the variability in your views per post. With just these two calculations, you have new information that you can use to gain insight into your social media presence and inform your social media approach.
Insight and Action
Information is the bridge to action. To make the most of information, you must consider it within your business context -- your strategy, goals, and business requirements. By analyzing the information you've gained from your dataset, you learn what it means for your business, which allows you to decide what actions to take.
Returning to our social media example, your goal might be to increase the reach of your social media posts and increase brand awareness. The number of views on a post indicates the reach, so you want to see your average number of views increase over time. Let’s take a look at two possible scenarios: one where the standard deviation for the number of views is low and another where it is high.
If the standard deviation is low it means that your posts have a consistent reach. That is, each post reaches about the same number of people as the others. To increase views, you need to get your posts in front of more people. So, you would need a strategy to get your posts in front of more people. One possible strategy is to pay the social media platforms to promote your posts. Another could be to encourage people to share your posts.
Alternatively, if you have a high standard deviation, your posts are receiving inconsistent views. Some posts may have a lot of views while others have relatively few views. Knowing this, you can analyze the difference between posts with many views and those with fewer views and develop a plan to write posts that embody the characteristics of the highly viewed posts.
In either situation, you can make changes, gather the data, analyze it, and see whether your changes are having the desired impact. Continuously working through that cycle empowers you to take control of improving your business based on data rather than gut feelings.