In many industries, the businesses are drowning in the wide expanse of data and are unable to use it effectively and to drive business value or insights.
|Asking Vague questions||vs.||Asking specific questions|
|How to raise my ROI?||What are the channels we should focus on to raise revenue while not raising the cost?|
|What channels lead to bigger profit margin?|
|Which marketing campaign worked best?|
It is key to ask the data analysis questions from the start. They lay the foundation to your BI framework.
|How was sales last year?||vs.||What is the average Revenue Per Unit (ARPU)?|
|What is your Customer acquisition Cost (CAC)?|
|What is your Customer Lifetime Value (CLV)?|
Your data analysis questions are designed to give a clear view of reality. If the data is incorrect, you may get distorted view of the reality.
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Knowing the end user will help you decide, what data and report you should focus on. Each type of end users, whether it is members of staff or someone from the management/governing body, has different needs and expectations. Some of the questions that you could focus on are as below:
Most valuable insights, if presented poorly can leave your target audience, without the impact you are hoping for. It is important to convince the end user that your data is accurate, reliable, important and urgent to act on.
|Data in a spreadsheet||vs.||Drawing a picture with data|
|Data in a table||Telling a specific coherent story|
With this information, you can outline questions that will help make key business decisions and set up a data driven infrastructure, teams and culture in a consistent basis.
Companies that have successfully cultivated a data-driven culture reap a multitude of benefits, from better employee understanding of the value of data and how to apply it to decision-making to a widespread commitment to backing up ideas with data and measuring outcomes across the board.
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