Session-based and event-based analytics platforms are usually grouped together under the headline “web analytics”. However, lumping them all under the same category is a bit misleading. Both kinds of platforms allow you to track a similar amount of details, yet they measure them differently and require a different set of analytical skills.
Traditional session-based web analytics platforms measure the traffic on your site and allow you to track metrics like page views, exits, and bounces. They rely mostly on session-based data, but allow you to configure events when you need them. So, if you want to collect more specific interactions – like form submissions, video views, and external link clicks – you need event tracking. Google Analytics 3 (GA3), also known as Universal Analytics (UA), is an example of such a platform.
Yet, there are also analytics platforms built exclusively around defining and tracking events. Currently, there are several analytics products based on this data model – Google Analytics 4 (GA4), Mixpanel, Heap, Segment, and Amplitude, to name a few.
In this article, we’ll show you the differences between session- and event-based tracking methods. It will help you to discover which method is better for you.
Many analysts and marketers are used to the session-based tracking method and its event tracking setup, especially if they rely on Universal Analytics (UA). You probably know that Google is sunsetting UA next year to replace it with an event-based GA4. Therefore, all professionals who’ve been using GA3 so far have to face a choice – to learn analytics based on a completely different tracking logic or to look for a new platform based on familiar patterns.
If you decide that event-based analytics is not a good choice for you, we will also tell you what session-based alternatives exist to the soon discontinued UA.
Events in analytics are all user interactions on your website. Any activity that users perform on a page of your website is an ‘event’ or ‘event hit’, for example:
- Button click.
- Click on a link.
- Form submission.
- Video play and watch time.
- File download.
- Page views.
Suppose a user visits your website and downloads a file, clicks a button, and fills out a contact form. These are three separate events on the same page. In that case, in session based-analytics, standard reports will still only count page views within the session. You need to configure event tracking if you want more data on that.
Event tracking in web analytics collects data on users’ interactions with elements of your website. It allows you to collect data like:
- Total events and average events per session.
- Total events based on event categories and individual events.
- Ecommerce data (for example, average order value and ecommerce conversion rate).
- Session data (for example, session duration and pages per session).
When you track events, you can better understand how users are interacting with your website. If you combine it with understanding how they experience your website and why they complete specific actions, it can help you drive more conversions.
The two data analytics systems, session-based and event-based, fundamentally differ in their measurement model. For example, in session-based analytics platforms, such as Universal Analytics, the main focus of data analysis lies in tracking sessions that occur on the website, while event-based analytics track particular actions the website users take.
In other words, the main difference between session-based and event-based analytics is that session-based analytics platforms are excellent at telling you what happened during a given session.
In contrast, event-based analytics platforms like Amplitude, Google Analytics 4 or Mixpanel offer deeper insights into how users who make these sessions actually behave. Event-based analytics focuses on tracking user behavior based on specific clicks, scrolls, and other interactions and discovering insights based on these events.
Session-based analytics uses categories such as session duration, bounce rate, traffic source, etc. It lets you organize all your data into neat dashboards, so you can easily assess your company’s page performance.
In session-based analytics platforms, a session is the foundation of all the reporting. You can think of a session as a container for all user actions performed on your site within a given timeframe.
What is crucial in session-based analytics is how the session started (for example, which channel the user came from) and how it ended (for example, where the user dropped off), average session times, and pages per visit, just to name a few.
Session-based platforms features include:
- Traffic reporting.
- Conversion tracking.
- Third-party referrals.
- Keyword referrals.
For most other user interactions in a session-based analytics platform (such as video views, file downloads, or widget clicks) you need to set an event.
For example, event tracking in Universal Analytics has three descriptors you can use for an interaction:
- Event category (such as video).
- Event action (such as progress).
- Event label (such as 75%).
You can add other descriptors in the form of custom dimensions and values, such as the custom dimension video type with values of corporate, educational, or promotional.
Goals can help you collect valuable data about important user behavior, such as making a phone call directly from the website using the click-to-call functionality or submitting a contact form. You can report and analyze the conversion rate of each traffic source for each goal. You may use the ‘end session’ point to see where and why people drop off, how many of them convert, and optimize the website to increase the conversion rate.
It is worth noting that in the session-based model, user flows and funnel reports are based on events from one visit (session). They can be less accurate in depicting actual conversion paths when your funnels involve many steps that can be completed during separate visits.
Session-based analytics gives you information such as the number of unique visitors and page views on your website. And if you pair it custom event tracking, you can understand your site’s user behavior better.
Session-based analytics is important when it comes to omnichannel marketing, which involves multiple touchpoints with different sources/channels. Here, it’s impossible to get away from the concept of a “session”. After all, a session is an aggregate, and using aggregates significantly saves time and resources.
Session-based data models offer a rich set of built-in reports like acquisition reports, thanks to which you can get data and insights on how people are finding your website. Therefore, session-based analytics is simple and accessible, especially helpful for digital marketers who aren’t deeply immersed in analytics.
Event-based web analytics uses a measurement model based on events and parameters. This makes a big difference in how data is measured. While things like page views, user timing, and app/screen views are classified as hit types in session-based analytics, here they’re all counted as events.
Event-based analytics platforms allow monitoring visitors and their interactions using behavioral reports. Analytics tracking happens in real-time. With even-based analytics, you get detailed information about how users interact with your business.
It could be a customer selecting a product or service for payment, a customer with a more negative sentiment than usual that a business needs to address quickly, or some misinformation that a company wants to catch before it impacts its stock price. Events can be generated by users, such as strokes of the computer keyboard or mouse clicks, or by the IT system itself, such as program errors.
In contrast to a session-based analytics platform, in platforms such as Google Analytics 4 sessions aren’t limited by time. Since it doesn’t create new sessions for source changes mid-session, your session count might be lower. Due to that, your average session time will drastically change too.
In session-based platforms such as UA, events track actions within your web pages or on the screens on your mobile app. In an event-based data model, everything is sent to your reports as an event, not the interactions you track as an event within the site.
Instead of goals, you now have events and conversions. You can choose which events will count as a conversion.
Events are tracked differently than in the session-based model. For example, GA4 captures four categories of events:
- Automatically collected events.
- Enhancement measurement events.
- Recommended events.
- Custom events – which mean any interaction on your website that is not tracked by default, for example, button clicks, sign-up events, form submissions, etc.
Since the measurement model is different from session-based analytics, the event-based platforms’ structure is quite different as well. Both types of platforms allow you to track the same amount of details. That said, they measure and present them differently. In event-based analytics, you have data streams instead of views you know from tools like UA.
You should be aware that with event-based analytics, it’s harder to get some of the metrics and dimensions. Even though all the data is available, professional web analysts using the raw data might have a hard time creating advanced queries to generate reports based on session data that was tracked as an event.
The new counting method setting for conversion events in Google Analytics 4 properties lets you decide how to count conversions. You can choose “Once per event” (recommended) or “Once per session.” Most users should select “Once per event.” Select “Once per session” if you want your Google Analytics 4 conversion count closely match the conversion count in the corresponding Universal Analytics property.
Event-based targeting allows marketers to create custom lists based on user profiles and actions in order to target audiences similar to past website visitors or retarget past website visitors. This audience targeting can be segmented by users who took certain actions (events) and enable marketers to target customers who, for example, purchased a specific product.
While session-based platforms can accomplish similar targeting, it is usually a bit less detailed with fewer options to configure the best possible target audience.
Focus on the customer
Event-based analytics is more customer-centric because it no longer only measures customers’ actions by individual devices or platforms. Instead, it assesses that behavior by how the customer interacts with your business.
Let’s say you run an ecommerce store. You want to figure out what types of items people check out without hesitation, and what types of items often result in abandoned carts. This can be performed with an event-based analytics tool. If you track two events — when someone adds something to their cart, and when someone checks out their cart — you can figure out which stock keeping units (SKUs) lead to a high checkout rate, and which SKUs lead to abandoned carts.
Since the event-based model gives you customer-centric measurement based on data from multiple touchpoints, it might offer a fuller picture of the buyer funnel. Especially if there are many steps in a conversion funnel that can be completed during separate visits. But if customer journeys are less complex and, for example, you need to easily track visits to high-value pages or a successful form submission, this data model might not be suitable for you.
An event-based platform will provide two things: an interface to collect events, and an interface to analyze those events. It is less of a reporting interface where you view your data. It is more like the do-it-yourself tool for your reporting. You may take advantage of advanced techniques that go beyond standard reports to uncover insights about your customers’ behavior. Thus, it provides more customization but requires greater analytical skills and makes the implementation difficult.
While the event-based model is somewhat helpful in modeling complex funnels, it often creates some challenges. The list includes:
- If you are accustomed to a session-based model, event-based analytics might have a steep learning curve. The data model is completely different, the UI is different, and it’s not an out-of-the-box solution as there are few predefined features.
- The data might seem messy, and you may have a minimal set of options to customize dashboards and widgets, so it will be difficult to display data in a presentation style that suits your needs.
- One of the major challenges with events is that they are only useful from the date when you first implemented them. If you want to do an analysis of how someone has gone through your funnel, you won’t have data going back through the beginning of your product’s history. While some platforms are starting to support historical backfilling, normally these processes come at a significant cost, both in terms of price and engineering time.
- You need to put more time and effort into analyzing the raw data, especially if you want to analyze data that by definition is session-based.
- Event-based analytics typically require engineering time and discipline to maintain. If you forget to update an event or don’t have time to implement analytics for a new feature, then you can’t get any benefit out of it at all.
- Event-based analytics platforms seem to be built more as tools for collecting lots of data with much of the analysis taking place outside the platform. Analyzing your funnel can become fraught as you might end up combining data between different data sources. It means that event data is at best directional in nature. You should look at your product data or data warehouse to have the full picture.
Event-based analytics gives more in-depth information about user behavior. But making the transition to event-based analytics can require a shift in thinking, especially if you are used to working with session-based data. It also requires comprehensive analytical skills. You have to understand what data is relevant and what isn’t. On top of that, you would probably need a dedicated team member to guide you. Because of that, it seems to be a good fit for larger organizations. All in all, the event-based data model data capture is much more limited by default and requires customization to make data more targeted. That, in turn, allows organizations to really tailor it to their needs but requires a much greater investment in data strategy and configuration.
Session-based analytics is ‘marketer-friendly’ because of the familiar data model. The advanced dashboards make it simple to retrieve and evaluate web data, and standard marketing reports about channels and campaigns are available. Session-based platforms track and report traffic to aid marketers in understanding their customers easily yet comprehensively.
Choosing a web analytics platform, whether session-based or event-based, is a challenging matter. We have explained the difference between both kinds of web analytics tools so it will be easier for you to decide which one is right for your business.
There are alternatives if you know there are better choices than just event-based analytics.
You could use a platform like Piwik PRO Analytics Suite. The platform is both session- and event-based, allowing you to collect much data by default without custom implementations like scrolls, single-page apps, outlinks, and downloads. And it was built with privacy compliance in mind.
Piwik PRO offers advanced analytics and familiar concepts. It provides modern reporting and key functionalities of Universal Analytics, such as event tracking, ecommerce reporting, session metrics, and custom dimensions. At the same time, it effortlessly handles events. Now, you can use all events in your advanced reports, such as funnels and user flows. And at the same time, take advantage of session-level aggregation and dimensions you know from classic session-based analytics.
We’ve gathered tons of details about various platforms – read our comparison of free web analytics platforms to get the information you need.
Piwik PRO’S Migration tool (GA3 and GTM)
The migration tool lets you quickly transfer your settings from Google Analytics 3 (Universal Analytics) and Google Tag Manager. It enables you to import GA3 properties, settings, goals, custom dimensions, and Google Tag Manager containers, including tags, triggers, and variables.