What Is User Engagement & Why Measure It?
Whether you are new to analytics, or just need a refresher, user engagement refers to how an individual responses to a digital experience. That experience may be via desktop, tablet, mobile, or an app. By measuring user engagement, you’ll be able to gain an understanding of what is going on with your business’ digital experience, and then look deeper to discover which aspects of the experience is driving conversion.
There is a direct correlation between how well a business understands their customer and the success of that business. By measuring user interactions with your digital space, you’ll understand where users come from before accessing the site/app, where they go to next, how much time they spend on a page, what page users exit, and much more.
So what’s the result? Through funnel analysis and pathing reporting, you’ll be able to identify various pain points in your funnels. This effort could be very useful in turning more users into customers. The main goal with user engagement is to drive more traffic, increase purchases from that traffic, increase average basket size, and drive repeat purchases.
You’ve Got Data. So What’s Next?
After collecting and auditing your data, an analyst may have a few questions:
- Where are my users coming from? Which traffic sources are converting best?
- Why do some users have an easier time getting through the funnel than others?
- When are users converting the most? When are they converting the least?
- Which pages are more effective?
- Are users bouncing directly after visiting the landing page? Why? What about other pages?
- How can I make informed business decisions from this data to optimize the user experience?
A great way to visualize your user data is to create trending charts. By visually representing your data, you can easily spot patterns, peaks, and valleys that will help in developing hypotheses that explain these fluctuations.
Different Metrics You Need to Compare
With your data available and a plan in place to help visualize it, it’s time to pick some metrics to start comparing. A great example is Total Visits vs Purchases. Check out this example:
By comparing Total Visits vs Purchases, you’ll get a high-level overview of the contrast between peak visit times and how that data compares to conversions. In this example, it’s clear that the peak times for visitors are in November and February. Visits are increasing around Black Friday and Valentine’s Day. There’s a good chance This rise in traffic is influenced by campaigns that ran during those times. In this example, when purchases are trending, this follows the visitors’ trend, so you can infer that the user experience through the funnels is pretty successful.
However, the above example is an ideal situation. For your digital experience, you may have many users visiting, but no purchases. So why are these two metrics indirectly proportional? Again, at this point, you can only hypothesize, so let’s dive in further.
By looking at Visits broken down by Channel, you can begin to gain a deeper understanding as to who’s driving visits. This is more of a second-tier analysis. Here is an example of what measuring Visits by Channel may look like:
Once you identify where users are coming from, it is extremely valuable to organize that data in a visual chart like the one above. By analyzing your visits by channel, you’ll be able to see which channels are influencing most visits, potentially improving content, images, and the measuring of your CTAs.
In this example, it is clear that paid search, direct traffic, and organic search have the most user visits attributed to them. By bringing in your ad spend here vs revenue created by the orders placed, you’ll be able to know which channel brings in more revenue for the least amount of investment.
At this point, some of your questions might be answered, but as any true analyst driven by the “why” question, you dig further. You know that some channels influence more visits, but does that mean those channels are leading to conversions? Let’s take this one step further.
The last measurement I’ll discuss today is Channel Visits, Funnel Abandonment, and Conversion. This will help you determine if that channel is bringing in quality users that are converting. Let’s take a look at this example:
By measuring visits attributed to traffic sources, top and bottom of funnel abandonment rates, and conversion rates, you can get a view of your funnels’ health. For this specific example, we can see that paid search is doing great, and based on my experience, is also influencing both organic search and direct traffic.
On the other hand, in the above example, paid social is not a channel that is doing particularly well. The chart above shows a disastrous 100% abandonment rate at the very top of the funnel. This could happen if the landing page UX is misleading or just not consistent with messaging. If your users are bouncing right away, I have three recommendations for you to help correct that issue:
- Create consistent messaging from ads to landing pages.
- Make sure your call-to-actions (CTAs) are tracked correctly.
- Evaluate UX design via A/B testing.
Whether your own digital experience reflects a similar pattern or not, these principles remain: comparing Channel Visits, Funnel Abandonment, and Conversion will help identify user pain points.
If your business is having difficulty meeting revenue goals, or if you just want to increase your revenue (who wouldn’t?), you need to start measuring user engagement. By analyzing the influencers of your digital experience, you’ll know which actions to take that will lead to a positive impact on revenue.
I hope the above examples give you an excellent starting point, so you can begin making informed decisions to improve your business. If you’re particularly interested in metrics regarding mobile apps, check out our blog post: 10 Metrics to Understand the Health of Your Mobile App. If you have any other questions about funnel analysis, the user journey, or user engagement, Cognetik can help. Contact us today.