Looking at the data while formulating a hypothesis If you look at data without thinking about it, it's just numbers, so to give it meaning, it's essential to form a hypothesis. For example, if the number of conversions has increased this month compared to last month, you can consider a hypothesis for the cause, such as "Is it because of the release of a new product?" or "Maybe it's because we increased our web advertising budget." By forming a hypothesis, you can dig deeper into the data and ask questions such as "So, what is the number of pageviews on the product search and detail pages?" and "How much has the number of conversions via web advertising increased?" Consider ways to improve the issues When analyzing your website, you may discover some issues that concern you.
However, if you feel that "this page has a high uae telegram data bounce rate" or "this page has a low membership registration rate," and do not take any measures, your website will remain unchanged. When you discover an issue, think of concrete measures to improve it, such as "Let's create a path to other pages to reduce the bounce rate" or "Let's review the structure of the membership registration form." Some of these measures may not be implementable immediately, but keep them as potential measures and implement them when renewing or improving your site.
Eliminate subjectivity as much as possible Hypotheses are important in site analysis, but there is a possibility that the hypothesis may be based on assumptions or misunderstandings. In order to eliminate subjectivity as much as possible and interpret the data in a neutral state, try to analyze from an objective point of view by interviewing other employees and users. Improve the site and verify its effectiveness Website analysis is not something that is done once and then finished.