To many, analytics and analysis are interchangeable terms. People often hear these words and think of one thing: numbers. But at Praxis, we know there’s a lot more to it than that – there’s actually a significant divide between these two seemingly synonymous words. Understanding the difference is a big step toward extracting the greatest insight from a given set of data. To make it easier to understand this difference, below we’ve defined and outlined some of the key factors that set these two terms apart.
Analytics – Your Numbers
Analytics refers to the true numbers side of data analysis. If you think of any analytics platform, when you open it up, you’ll likely see several dashboards filled with different metrics, numbers, performance indicators, etc. A spreadsheet could even be considered analytics. Ultimately, an Excel spreadsheet is just a dashboard, or database, filled with numerical values organized into some structure. With this in mind, analytics is just a fancy term for data entry. Most workaday people can – and regularly do – create dashboards or spreadsheets filled with row after row of numbers, but the value in data analytics comes from the analysis piece of the puzzle. At Praxis, we rely on a bevy of tools to gather analytics: PraxisDirect, Google Analytics, Google AdWords, Facebook, DoubleClick, Sysomos, and so on. The importance of these tools does not come from the tools themselves, but rather from the proper understanding and utilization of the data they gather, which requires dedicated analysis.
Analysis – Your Numbers Explained
Data analysis requires both a left-brained, analytical mind frame and a right-brained knack for storytelling. If analytics is the numbers, analysis is the story, or meaning, behind these numbers. Why are the numbers important? Which metrics should I pay attention to? How can these key performance indicators improve or guide my business strategy? These are the types of questions that analysis answers. Analysis provides direction in times of uncertainty and can provide confirmation following times of intuitive decision-making. Praxis utilizes many different tools to conduct analysis, including Excel, SPSS, Tableau, R, and many more. To use these tools effectively, however, the right questions need to be asked: What visualization do I want to see? How can I best communicate my findings? The key – and challenge – to any analysis is the ability to filter through the noise to find what’s relevant. With the amount of data available to marketers, this makes it critical to assemble a competent team of trained analysts to climb through a mountain range of numbers and develop a story worth telling.
Being able to clearly differentiate between analytics and analysis seems like a straight-forward concept, but in practice, it’s surprising how often marketers simply “look at the numbers” without understanding their significance. Having trouble finding meaning in your data? We can help.