Data analysis methods are normally used to inspect, clean, transform and model data in a bid to uncover useful details, suggest conclusions and support a certain decision making process. It normally has multiple approaches and facets that encompass a variety of techniques under different names, science, different business and social science domains.
Product managers use this as their tool box where they investigate the data that has been collected, learn from it and use it to create a successful product that will do well in the market. It can be quite easy in theory but is it quite challenging in practice and below are some tips that can help you get the most out of your data analysis methods.
Set up a Clear Research Goal
A clear research goal is required for effective data analysis. This is where you get to understand why you want the work to be done and what you are looking to achieve when it’s complete. Without a clearly defined goal, you may set out to collect the wrong data which will result in drawing the wrong conclusions that can see your product move in the wrong direction.
Separate Data Collection From Data Analysis
As you compare different data analysis methods to choose the one to work with, it is important to understand that you have to study the data that has bee collected very carefully before you make a decision. Do not get into the business of analysis the data when you are collecting it as you need to finish the process first, relax and go through it to come to conclusive decision making. This will increase your chances of making the proper decisions. The new insights you get from the data you get can be used to change the necessary artefacts to ensure that you end up benefiting from the entire process in a huge way.
Have an Open Mind
When choosing the data analysis methods to work with always remember to keep an open mind. This does not refer to the lack of effective analysis of tools or techniques and but the ability to stop clinging to a certain idea you like. Be prepared to change your mind depending on the data you receive even when you feel strongly about your ideas as this could be the best decision that you make for your product. Always relax and take a deep breathe before you carry out any analysis to ensure you make sound decisions when you are well informed.
Clean Data
Don’t forget to clean data that you are using before selecting the ideal data analysis methods. This helps you get rid of poor quality data that cannot be interpreted in the right way. This should be quite a simple process unless it is an idea from a powerful stakeholder or from a valued customer. However keep in mind that saying yes to all ideas does not necessarily mean that you will end up with a great product. This means that you should stay true to your vision and leverage the primary persona to determine what it best for the business.
