I have in the past built websites where I assumed that Part A would be the most popular part and so put a lot of effort and work into Part A. Less effort was put into Parts B, C, D etc.
When I launched it and let it run for a while, it turned out - thanks to analytics - that Part B was the run-away success that was getting lots of search-engine traffic and 90% of the visits to the site.
Had I not had analytics then I'd not have known that and would not know which parts of the site people valued. As a result I put the larger part of my focus into Part B instead.
It allows optimizing many things such as the UX, the speed and size of your product, and your own time.
Examples:
* If you see that a button is used 10x than an other button, you can re-order buttons.
* You can remove buttons that are never used (=faster load times, less bytes)
* You can drop features that are never used, focus on features that are often used, saving your own time.
The other approach is "I already know what is best, I don't care about how other thinks". This is also useful because it can allow you to break out of local optimum.
Improve conversion rates.
Create a better user experience for all the users.
Understand which traffic sources are valuable so you can take better business decisions.
Know if something is broken on your site.
Are you implying that all analytics used in the world are implemented just to boost the site owner's ego?
hk__2|5 years ago
What are those other purposes?
mattlondon|5 years ago
When I launched it and let it run for a while, it turned out - thanks to analytics - that Part B was the run-away success that was getting lots of search-engine traffic and 90% of the visits to the site.
Had I not had analytics then I'd not have known that and would not know which parts of the site people valued. As a result I put the larger part of my focus into Part B instead.
Jyaif|5 years ago
Examples:
* If you see that a button is used 10x than an other button, you can re-order buttons.
* You can remove buttons that are never used (=faster load times, less bytes)
* You can drop features that are never used, focus on features that are often used, saving your own time.
The other approach is "I already know what is best, I don't care about how other thinks". This is also useful because it can allow you to break out of local optimum.
XCSme|5 years ago
Are you implying that all analytics used in the world are implemented just to boost the site owner's ego?
boomlinde|5 years ago