Find why users don’t take a certain action.
Depending on the data we use for the analysis, we can break down every analysis into two main categories:
- Analysis of qualitative data
- Analysis of quantitative data
When we talk about qualitative data analysis, we usually mean such data sources as:
- Surveys
- Polls
- Interviews
- Heatmaps
- Others
This is essential information to understand why something is happening that you see in quantitative data.
The analysis of quantitative data usually includes working with big datasets. For instance, the most popular web analytics tools that collect quantitative data are:
- Google Analytics
- Mixpanel
- Tableau
- Amplitude
- Others
The analysis of these two types of data requires different methodologies.
When I work with quantitative data, I run some statistical tests to analyze the differences in the data more carefully and report only insights that have statistical support. This allows me to run experiments and reach 30% and higher improvements more often.
Whenever I work with qualitative data, I need to keep other things in mind that are relevant to this specific data source. For instance, you need to collect the same proportion of each user’s segments. If the users consist of retired people and business owners and retired people state for 20% of your audience, your survey results should follow the same proportion. Otherwise, there is a bias.
Therefore, it’s highly important to find a reliable data analyst and make solid data analysis without a rush. If you are interested in working with me, don’t hesitate to get in touch with me through this page.
“We loved working with Ihar who was with us for nearly 6 months. He helped us develop new strategies by analysing the traffic on our website and integrated new tools to further understand our data – resulting in more leads and sales. His communication skills are also excellent and was always available on Skype when needed. I highly recommend using Ihar.”
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