Engagement is the next big thing, which is why so many website owners track their performance with user engagement metrics.
Once you have developed an engagement model appropriate to your website, you can define which metrics are important and which are not.
Which Metrics Should You Use?
Different user engagement models come into play on different types of websites:
- Content-rich websites should focus on user activity and user loyalty. Time spent on site, the number of pages viewed, and the return rate are examples of metrics that will be useful to content-heavy websites. Media outlets, news sites, and similar publications should strive to keep users on their sites as long and as often as possible.
- Commerce sites should focus on their on-site sales funnel. Can users find what they’re looking for? Or do they abandon at specific points during the sales cycle? A website’s usability data, such as the shopping cart abandonment rate and page view statistics can tell you whether or not engagement is up to par.
- Specialized sales sites should focus on the conversion. When visitors come once and never leave, the entire focus of your engagement efforts should revolve around the conversion. Return rates won’t apply, but time on site and conversion rates would.
15 Essential User Engagement Metrics
Once you’ve chosen the right user engagement model for your site, it’s time to look at metrics.
Though app developers and website owners use slightly different metrics to track user engagement, there is some overlap and many of the same concepts carry over.
This list covers the most common and useful:
- Bounce Rate – Bounce rate refers to how often users leave a site.
- Conversion Rate / Goal Conversion Rate – Conversion rates measure the completion of a goal, such as opting in to an email list or making a purchase.
- Click-Through Rate – Click-through rates measure clicks on ads, hyperlinks, and so forth.
- Abandonment Rate – Abandonment rate, or shopping cart abandonment, refers to the frequency that people abandon a shopping cart.
- Revisit Rate / Return Rate / Stickiness – The return rate defines how often a user returns after an initial visit, while return rate defines the ratio of users that return over a set period of time, usually a month.
- Time on Site / Time in App – This is the amount of time that an individual user spends on a site or in an app, respectively.
- Session Length – A session in Google Analytics ends after 30 minutes of inactivity, while in apps it refers to the period of time between app open and close.
- Time on Page – This is the amount of time a user spends on a single web page.
- Pages Per Visit – The pages per visit indicates the number of pages a user views per visit to the site.
- Number of Sessions Per Day/Week/Month – The number of sessions started in a given time frame can help gauge popularity, value, and engagement.
- Number of Actions/Events Per Session – First, the specific event or action must be defined – such as hover-overs, clicks, and so forth – and then it can be referenced to each session.
- Daily/Weekly/Monthly Active User – A user who comes back each day would be a daily active user (DAU). The same definition applies to weekly active users (WAU) and monthly active users (MAU).
- Visits Per Day/Week/Month – The number of visits that a user executes per day, per week, or per month.
- Retention Rate – This is the ratio of users who stick around versus those who leave for good.
- Week 1 Retention – Users who stick around for a week are more likely to stick around for the long haul, so the first week is the most important.
There are countless secondary metrics that are useful to the website owner or app developer. Though they may not be directly related, some secondary metrics can offer insight into user’s engagement level.
On-site comments, reviews, or feedback, for instance, aren’t always included in analytics platforms. But these numbers can be included alongside other data to add more dimensions to the picture.
Likewise, offsite signals, such as social interactions, can also indicate engagement levels of content, user segments, and so forth. Social analytics, advertising analytics, and other data from the multichannel content funnel can contribute to a deeper engagement picture.
Finally, financial metrics can also help build a better picture of the customer. The customer’s lifetime value and the average revenue per customer are two examples that can indicate the success or failure of engagement programs.
Whether you use a few metrics or hundreds, it’s important to tie these measurements to the right engagement model for your site or product. Once you have the right model in place, develop a set of metrics to gain a holistic view of your customer and their engagement rates.
While it’s sometimes useful to tie results to a single key metric, this approach risks offering a one-sided picture. Expand your understanding of your marketing and your audience by going granular.
This list should be plenty to give you an accurate picture of your engagement rates and how to improve them.