Analytics Review

Using the power of analytics should be an integral part of any UX design process. It can not only be utilized throughout the iterative design section - when you design a solution, then measure and test out how it works, then building upon the results modify it -: in many cases our client already has web analytics tools connected to the product or service.

How does it help

Thanks to this method, we can start analyzing the usage data at the very beginning of the UX design process, which contributes in creating a good starting point for research, it helps forming hypothesis, and ask the right questions.

What will you get

We will provide you the summary of our analysis in a document, supporting our findings with demonstrative diagrams.

It is important to know that there are two kinds of data we use during the UX design process: qualitative data and quantitative data. Qualitative data help us answer the “why” questions, and collected during the UX research (e.g. we conduct these: User interviewDiary StudiesOnline SurveyContextual inquiry). On the other hand, quantitative data is gathered thanks to analytics tools. One of the main advantages of working with quantitative data is that it provides a larger sample size (than e.g. User interviews or Usability Testing).

During the kick-off meeting (Stakeholder interview), we will ask if you have any web analytics tool already connected to you digital product or service (like Google Analytics). If you have, we can start analyzing the usage data at the very beginning of the UX design process, which contributes in creating a good starting point for research, it helps forming hypothesis, and ask the right questions. (If you don’t have such tools connected, we will suggest you to start working with them).

What is the process

Thanks to our Analytics Review, you can find out many things, for example you can learn about:

  • What are users doing?
  • What are they trying to achieve?
  • Which pages do user visit, and in what order?
  • What are the entry points?
  • Navigation patterns: From which pages your users come from?
  • User engagement: bounce rates, session durations etc.

To sum up, analytics help determining which points should be improved (e.g. we can identify if the navigation is misleading, or which pages are the most frustrating).

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