From data analysis to salary increases

. Quite often, when studying user experience, my colleagues and I use PostHog, a powerful tool for collecting and analyzing static data from websites and applications. The tool is important and really complex, so I want to put together a mini-course on how to work with it.

But where to start and how to force yourself to study it? In this article, I will tell you how a designer can use the advantages of PostHog for their own purposes. I will try to intrigue you: with the help of this tool, you can even influence the payment for your work. And also get a lot of useful insights that will help in professional development.

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→ Legend: You are Petya
→ Analytics examples from PostHog
→ Conclusion

Legend: You are Petya

Imagine: you are a UX specialist named Petya who wants to get promoted. To do this, you need to show the team leader how your decisions affected the growth of target metrics. And this – not surprisingly – will be helped by “numbers”, because you can't argue with them.

If the result of your work is measurable, then it can be assessed and re-evaluated upwards along with the growth of metrics. And if the metrics do not grow or, on the contrary, fall, then you can correct the situation, which also shows your value. No matter how you look at it, metrics remain an important tool in UX and beyond.

Who builds UX at Selectel

What metrics are useful for Petya

Conversion.

In a general sense, conversion shows the ratio of users who have completed the target action to the total number of users at the start.

Time to complete the target action. This is the time it takes the user to follow the designed path.

Performing key actions on the way to the target action. For example, creating an additional entity to reproduce the required object. Tracking such key events helps to analyze them together when building a user journey map.

Retention rate. It is a statistical measurement of the proportion of users who remain engaged in using a product from one given period to the next.

Life path (lifecycle). Visualizes the behavior of new, returning, resurgent, and dormant users and shows exactly how your audience is growing.

All of these metrics can be tracked using PostHog, a data analytics platform that can help you understand user behavior in your product.

PostHog Features

PostHog — builds its analytics on events that the user performs. A striking example of such an event is a click on a button or banner. In addition, there are events like viewing pages, which are considered automatic.

Events can also be created by users and have their own properties. For example, buttons for adding a service can be at the top and bottom of the page – using the event property, you can find out which one the user clicked.

Additionally, PostHog has other great tools that can help a designer in their work.

Recording sessions — for visual observation of user behavior.
Feature flag — for testing or releasing functionality to a limited number of users.
Built-in A/B testing functionality — to identify the best option by sampling users or testing hypotheses.

Analytics examples from PostHog

Conversion

Your interface definitely has target events, the implementation of which is worth tracking, analyzing and removing blockers on the way to their implementation. Conversion will help you with this, which will show what percentage of users go to the end.

A conversion rate of 40% means that out of 10,000 users who opened the form, 4,000 ordered the service.

PostHog allows you to track conversion over a certain interval, and also shows the average time it took for a user to reach the finish line and order your service.

In addition to conversion over a period, historical conversion is available, which shows the value for fixed intervals – for example, for a month – and its growth can be a reason to be proud of your work, if you are involved in it.

It is also valuable to analyze users who for some reason did not order your service. Let's say the 6,000 users from the example above can be further analyzed via PostHog. The following tool will help us with this.

Cohorts

Different users with common properties, such as the same regions or device types, can be grouped into cohorts and their behavior analyzed. PostHog offers a wide range of variations on how to form such entities.

One such option is to form a cohort of users who ordered or did not order a service according to your target event. It is useful to analyze both.

Working with cohorts in PostHog.

When viewing users, you have access to their session recordings, which will be useful when analyzing behavior and identifying “problem areas.” By saving the desired cohort, you can study the user’s path in your product.

Custom paths

Another great tool in PostHog that will help you assess how well your user flow matches real user behavior. Remember the meme about the rectangular designed path and the path that people have trampled? User paths are exactly that.

Analyzing User Paths in PostHog.

By analyzing the path, you can design it simpler and shorter, which should have a positive impact on conversion metrics. For example, increase the percentage of those who ordered the service and reduce the average time to order.

Such data will perfectly illustrate your value and work in the company during the review and will be a weighty argument for a salary increase. Or will decorate your portfolio when describing cases.
If you're ready to deploy PostHog and get started, you can use Selectel cloud servers. We will ensure 24/7 availability and reliable storage of data for analytics.