By devtodev analysts, Vera Karpova and Vasiliy Sabirov
Currently, product analytics reached a sufficiently high level of development. Many analytical systems are equipped with a variety of tools that will tell in detail how users behave in the application: when they buy, where they live, how much they cost for the company and how they leave.
These tools have become a part of daily life, regular monitoring; assistants in the decision-making process – now it is a must-have for any project.
Funnels and segments don’t surprise anybody anymore, and as in any other business, having reached the top of one reveals a will to go further and improve.
In this regard, the sphere of analytics is no exception, and in the past few years a new kind of data analysis – predictive analytics – began to develop.
You’ll also have an idea of predictive analytics, if you monitor the metrics on a daily or even hourly basis.
For example, you know that usually at 12 a.m. there are about 20,000 users in your game, and today this indicator is much lower. It equals 15,000 users. You understand that there is a trend for decline, which means that it is necessary to find the cause as soon as possible and improve the situation before the indicator falls even more.