Data analysis can seem like an impossible task for someone who doesn’t understand it. However, the veil surrounding data can be lifted by taking three steps. First, it’s useful to understand the context of the data and the different types that you can have. Once comfortable with that identification the next step is determining the right analytical methods to use. Finally, you’ll be left with a product to interpret with your new set of skills.
Data Types & Context
Data comes from many different sources such as purchases, movement on websites, and reviews. Data simply represents information from those sources. The source of data is called the origin and knowing the origin is essential to contextualize the data. The totality of data should also be considered because it tells us whether the data is a representative sample or census (interviewing some people or interviewing everyone). It’s helpful to recognize that data fits into 4 types of measurements: nominal, ordinal, interval, or ratio. Identifying these data types is a critical skill to develop and will expedite data analysis. So the process for defining data starts by looking at the origin, followed by its totality, scope, and measurement (which has four types).
Selecting The Right Analysis
Once the data has been defined the next step is selecting the correct analysis, and largely depends on whether the data measurement is categorical or continuous. After that is established you can move on to testing differences in medians and averages to find subgroups within the data (this should only be done with continuous data, however). Using measures of associate (like correlation) is a good way to find patterns that move together in data. Correlation does not necessarily mean causation but theory helps us understand whether there is causation or not!
Core Data Interpretation Skills
The ability to properly interpret your data leads to exponential gains in informed decision making. A good starting point for interpretation is tables and visualizations of the data. Specifically looking at the shape, center, and spread of the distribution. When interpreted correctly, these visualizations can give incredible insights into the customer journey and customer lifetime value (CLV). Building your core skills takes time but the effort leads to wonderful results in all departments of a business.
Continue down the data knowledge path by understanding how to get quick wins with data!