In brief
The essence of Lean Market Research is to gather intelligence for taking the best business decisions. On the other hand, gathering information in itself is not enough. It’s vital to be able to transmit that intelligence in the most digestible and actionable way possible. This is where Data Analytics and Visualization comes into play. This post is about The Ultimate Guide to Data Analytics and Visualization for Lean Market Research.
Data analytics and visualization is all about how to extract the core knowledge about the gathered data and how to present it in a plain and comprehensive way.
Introduction to Data analytics and visualization
After this high level overview of lean market research, it’s time now to take a closer look at one of its backbone and vital components: This is Data analysis and data visualization.
This post aims at going through data analytics and visualization in the framework of lean market research in a practical and concrete way.
What is data analytics
First, what’s data analysis ?
Data analysis stands for using statistics and data visualization tools in order to extract the essence of the gathered data.
It can be applied to qualitative and quantitative data.
It can be applied to primary and secondary research.
What is data visualization
Second, what’s data visualization ?
Data visualization stands for representing the final post processed data in a highly digestible and comprehensive way.
Researches with outstanding data visualizations give immediately higher credibility and bigger perceived value to the conducted research.
Messages and conclusions conducted through clean visualizations are one of the most impactful pieces of the conducted research.
How to perform data analytics and visualization
Now that the definitions of both data analysis and data visualization are set up, let’s take a look at how to perform concrete data analysis and data visualization.
Actually, there are numerous solutions for doing so.
First is Do it yourself software.
For example : Open source: Google sheets, R, Python etc.
These solutions can also be paid solutions like: Excel, Tableau, M Power BI, Super metrics etc.
Indeed, there are today a bunch of new great tools that make it possible to perform high quality data analysis and visualizations even for non-statisticians.
Second solution for performing data analysis and visualization is hiring statisticians.
This can be done by hiring them among the team.
It can also be done by hiring Online freelancers on freelancing platforms like Upwork.com, Freelancer.com etc.
Pros tips – The Ultimate Guide to Data Analytics and Visualization for Lean Market Research
- All the time spent manipulating the data and testing hypothesis can only be a beneficial time for the conducted study
- Data analysis should not be left only to quantitative data since it can also be applied to quantitative data eg to open questions post processing
