Metrics Explained: Some of the Most Misunderstood Terms

Metrics. We know we’re supposed to be measuring them and putting them to good business use. However, many of them are hugely misunderstood.

Not understanding how to study your metrics is potentially as bad as having no metrics to measure at all.

At the very least, a metric that is not well understood is of little use to your business. Take for example Facebook “likes.” Most people have caught onto the fact that you need a bit more than “likes” to indicate success, but for a while, companies honed in on getting more likes.

But do “likes” translate into sales or business goals? By the time you weed out likes from your friends, college roommates, and your mom, are you left with people who are your ideal customer? Not necessarily…

Worse still, misinterpreting metrics could even hurt your business. For example, what if you focused on new customers, and used that as a measure of growth, ignoring churn? It’s possible to find that your churn outweighs your growth, meaning your business is losing ground.

Metrics need to be meaningful, and they need to be interpreted correctly. Here are some of the most misunderstood metrics:

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Bounce rate vs. Exit rate

Bounce rate and exit rate are completely different metrics, although they often seem to end up conflated or confused. Let’s first look at what they mean:

Bounce rate is defined by Google Analytics like this:

“A bounce is a single-page session on your site. In Analytics, a bounce is calculated specifically as a session that triggers only a single request to the Analytics server, such as when a user opens a single page on your site and then exits without triggering any other requests to the Analytics server during that session.

Bounce rate is single-page sessions divided by all sessions, or the percentage of all sessions on your site in which users viewed only a single page and triggered only a single request to the Analytics server.”

Exit rate, on the other hand, is defined like this:

“For all pageviews to the page, Exit Rate is the percentage that were the last in the session.”

Put simply, bounce rate is measured from the only page the visitor went to, while exit rate is measured from the last page they visited.

Both metrics are commonly seen as “bad” things. A company will see a high exit or bounce rate and decide that those pages must be terrible. Sometimes they’re right, but this isn’t always the case. Consider these points:

  • What if exit rate was high on a page, but the user found what they needed? The intent of each user will vary, but exiting might mean they’re satisfied, have the information they need, and will be back later to make a purchase.

  • What if you have a page with high bounce rate, but this is entirely expected? For example, the visitor lands on the page, gives some kind of information as per the intent of the page, then exits.

In examples such as these, you need more information than just the face-value of exit or bounce rate. For example, you might look at customer segments and the journey they are taking, to put it into better context.

Of course, if you have people exiting half-way through your sales funnel, this is one good case for “exit rate = bad.” Look at pages closely - is their intent being met?

Metrics like bounce and exit rates may not be as “bad” as they appear

Time on site

Time on site (or session duration) often gets confusing for any business owner looking at their Google Analytics reports. What you will find is that there often seems to be a discrepancy between average session duration and average time on page.

When average time on page shows up as much more than session duration, what’s going on? Well, it’s all in the way Google calculates those metrics.

Google doesn’t measure how long a person spent on the last page they visited on your site. They calculate the average time on page by using the time a visitor opened the next page on your site. This means that the last page they visit is recorded as zero time, while session duration will end at the time they opened that last page.

Circling back to bounce rate, consider those “bounces” recorded as zero time. Did they read your webpage? Maybe they did, maybe they didn’t, but that zero time is deceptive. Google doesn’t know how long they spent on the page, because it’s the only one they visited. They may well have found the information they came for, then left.

Is time on site, therefore, a good metric to study? Again, that comes down to intent and the customer journey. If people are landing on one particular page, getting helpful information, then leaving, you could argue that the “zero” time on site means nothing.

Page view, Session, and Unique page view

These terms are also often mixed up and misused. Let’s look at how they are defined and calculated:

  • Page view - This is specific to pages that are set up with Analytics tracking codes. It is defined as a view of a page on your site that is being tracked by the Analytics tracking code. If a user clicks reload after reaching the page, this is counted as an additional pageview. If a user navigates to a different page and then returns to the original page, a second pageview is recorded as well.

  • Unique page view - This is seen in the Google Analytics Content Overview report, and aggregates page views that are generated by the same user during the same session. A unique pageview represents the number of sessions during which that page was viewed one or more times. (So it doesn’t add additional page views if the user goes back during the same session, unlike page views).

  • Session - These represent the number of individual sessions initiated by all users of your site. If a user is inactive on your site for 30 minutes or more, any future activity is attributed to a new session. Users that leave your site and return within 30 minutes are counted as part of the original session.

An important consideration is that your AdWords reports may look different than your Analytics reports. Here’s how Google explains it: “To ensure more accurate billing, Google AdWords automatically filters invalid clicks from your reports. However, Analytics reports these clicks as sessions on your website in order to show the complete set of traffic data.”


Churn is a huge concern, and therefore, closely monitored in SaaS and other digital businesses. The fact that there are multiple articles outlining 40-plus ways to calculate churn doesn’t help!

Probably the simplest view of churn is the number of customers that your business loses every month. Calculate churn by dividing the number of lost customers, by the number of total customers at the beginning of the period.

Some people would argue that you should add in the new customers you take on to that total number. However, the purpose of calculating churn is to analyze the health of your business, right? Adding in new customers might make the numbers look better, but importantly, you want to know how many customers tried your product and weren’t satisfied. Adding in the new customers could appear to balance out the churn rate, making it appear as though there are much better levels of satisfaction.

Calculating churn in this way also allows you to derive other important metrics, such as Average Customer Lifetime, and Customer Lifetime Value. Many companies set goals around improving these two metrics, so it’s important that churn is well-understood first.

Monthly recurring revenue (MRR)

Monthly recurring revenue (MRR) is an important metric for any business, but is especially crucial within the startup world. MRR is what every potential investor wants to know before they will consider injecting funds.

Sounds like a simple concept. However, MRR is often calculated incorrectly and entirely misunderstood. By definition, your calculation of MRR should only include revenue that is recurring, so this means no inclusion of one-off purchases in that figure. MRR may be zero or greater, but it is never negative. It is only the income that your company can rely upon every 30 days.

By this definition, MRR is only appropriate for companies that make their revenue through ongoing contractual relationships with customers (such as subscription-based businesses). It wouldn’t be a metric for say, an ecommerce store where purchases are made as-needed.

For companies with a larger customer base, the most efficient way to calculate MRR is by multiplying the total number of paying customers by the average amount they pay each month. The most common mistake is when people add in those one-off purchases to the calculation.

Another suggestion to ensure accuracy with MRR is to take churn into account. Churn is a leading indicator of problems in your business. What if you dialed back your marketing initiatives tomorrow? Would you find that new customers were outweighed by churn? For this reason, MRR Inflow and Outflow are good metrics to understand as well.

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Final Thoughts

Metrics are important, but if you’re going to do them, make sure you do them right. This means understanding how they are calculated, what their meaning is and where they really fit in your business.

Some metrics that “everyone else” seems to be using may be completely inappropriate for your business model. It’s all about using them within the right context.

This is just a taste of some of the most misunderstood metrics that we come across, but there are plenty of others we can mention. What metrics do you see misunderstood, or find confusing? We’d love to hear your thoughts.