The latest SessionStack release includes: User trends and Contextual Filters
We are excited to announce two brand-new features in our application. The first one is User Trends which gives you a quantitative segment analysis with a zero-effort configuration. The second is Contextual filters which allow you to define a feature in your application as a combination of Visited URL & Clicked Element events.
In this article we will cover:
- Introduction to Contextual Filters
- The transition from the Sessions dashboard to the Segments dashboard
- Which major questions do our user trends answer?
- How do I set up visuals for user trends?
- How to get the most out of first User trend charts?
Introduction to Contextual Filters
The first contextual filter introduced to our application is the Visited URL, which can be used in conjunction with the main event — Clicked Element.
The first question you may have is, “What exactly is it about?”
The contextual filter is a filter that can be used only with a combination of the main event. It facilitates you to add additional conditions to the users’ actions — they do that when they are on that page. We will give you a detailed example of how to configure it in the next sections covering also User trends.
The transition from the Sessions dashboard to the Segments dashboard
In our previous blog post, we explained the shift from the session-centric grid to the user-centric one in Sessions Dashboard. Now, we’d like to share with you our most recent transition from Sessions to Segments. Our new primary dashboard Segments include all of the data that you previously had, as well as the new User trends section on the right.
As the saying goes: “One look is worth a thousand words”, so take a glance at the image below for details.
Which major questions do our user trends answer?
The first four charts of user trends provide you with a tool for determining how lively and strong your product is by answering the three essential questions:
- How many users currently meet the searching criteria I have?
- How many sessions do the users have in the searched segment?
- How long do my users’ sessions usually last?
How do I set up visuals for user trends?
No need for the extra effort for chart configuration. Simply log in to the SessionStack app and navigate to the Segment dashboard (which was previously named: Sessions). Once you are there you see three major sections:
- the filter section — where you can define your search criteria and save it as a segment;
- users grid — the list of your users with their sessions;
- trends section — getting information on how your chosen segment is developing throughout the time frame you’ve selected
How to get the most out of our first User trend charts?
Consider the following example to see how the charts can be used in a segment context. You are a company that recently has launched a new feature. Now you want to check if it has been in use at all by your customers. You also want to know how frequently it is used during the day.
To get these answers, follow the next few steps:
Step 1:
Configure a segment by using a combination of Event filter and Contextual filter
Any feature can be described as a combination of the event filters: Clicked Element and/or Visited URL. Yet, the most sophisticated way to do it is to use Clicked Element and its contextual filter “Visited URL“.
To understand better what is the difference between the main event filter Visited URL and the contextual one, we will take a look at both configurations.
When you have a configuration like this one:
It means that your built segment will be matched with all users who have visited the page at least once and have clicked the element. This is not the same as having the following configuration:
The last guaranteed that users who pressed that button were on that specific page at the time. Only users who interacted with the element while on the page will be included in your segment. The graphics up top demonstrate how the user count varies. In the second scenario, only one user meets the filtering criteria.
The first four visuals that we introduced in the Segments dashboard can be used not only when releasing a new feature on production, but also for tracking the usage of the major features in one product.
Let us take a look at the example related to main feature usage. For SessionStack one of the main features is Session replay. A viable definition of a daily active user for us could be a user who has logged in and has watched at least one session for the day. The Session replay feature can be accessed from two main sections in the product. One place is The Segments Dashboard, the other one is the Events and Errors Dashboard. We want to know where the play option is used the most. Of course, we have an assumption, that this is our main dashboard with sessions but we are not sure about that.
Firstly we will define two different search criteria. The first one is a combination of the Clicked Element: play button and contextual filter Visited URL contains our main dashboard URL. The second one has a similar configuration, but the only difference is that the URL points to our secondary dashboard.
Our next step is to save both configurations as a segment with a human-readable description so that each SessionStack teammate understands what it is about without having to check the configurations thoroughly. The benefit of segment saving is that it can be used later by everyone in the team/organization. Next time, instead of creating a new configuration, simply select the previously saved one.
Now we come to the heart of the analysis part — reading the charts.
Step 2:
How to read the user trends
Once you have created your segment, the charts on the dashboard will refresh automatically. If this does not happen, you have a manual option to reload them. Changing the segment configuration or switching to another previously configured one will supply all visualizations.
Our first chart ( Users) and the segment created to filter users of major features (session watch), is giving you the DAU (daily active users).
This metric provides insight into the engagement of your product, service, or feature by determining the number of daily active users. Although the term “active” is interpreted differently by each organization, it typically refers to tracking customer interactions with your website/application.
Another way to track the usage of your product and/or features is to measure the number of sessions (visit frequency). For some products such as accounting software, there will be some peaks with visits during the month (before tax day), for others such as music platforms the visits will be daily, for trading platforms there will be visits during the working days of the week with some peeks on Monday & Friday — when the stock exchange is opened/closed.
Our second chart, Sessions, will assist you in determining the frequency of your visits. It will provide you with the tool to check if there is a decrease/increase in the usage of your product/service/feature.
The third metric, that you can track inside our app is Session Duration. The length of time a user interacts with your product can indicate engagement and the likelihood of churn. The general conclusion is that the longer the session duration, the greater the engagement with the product. However, a short average session time is not always a bad thing. If a visitor to your website is looking for information, finds it fast, and then logs off, it suggests your website was helpful to them. On the other hand, it would be a negative sign if people were spending a lot of time on your website because they couldn’t locate what they were looking for.
Our other two trends — Average Session Length and Average Session Length per User — can be used to track the session duration parameter. You may ask why we have 2 charts for session duration. Normally, users with different visit frequencies — some of them are rarely using the website/app, others several times per day or just once per day but spend an hour and more. If you use only the first chart for average session length this could significantly distort the perception of the typical average session time. To get a more accurate picture of the average session length, use both charts.
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We hope you find these feature updates helpful. We’d love to hear your feedback in the comments below.
