misleading analytics data

Google Analytics is a vital tool for evaluating your website’s performance and tracking KPIs (key performance indicators). Like almost any tool, however, it has its limitations. In this article, I’d like to dive into misleading data that often confuses users.

When I say “misleading” I mean that stats or numbers shown may give you the wrong impression about your performance.

The key is here context. Data without context is limited, and that is especially true for these stats. Do not blindly rely on any of these metrics as an indicator of how well your website is performing.

Before we dive into these metrics, we need to define what a session is because a session will determine how each metric is calculated…

Sessions are a period of user activity not interrupted by more than 30 minutes. Sessions will always be higher than Users since a single user can generate multiple sessions…

Example 1: 

  1. John visits your website home page
  2. John takes a call that lasts 30 minutes
  3. John resumes activity on your website and clicks to a new page

That’s two sessions. It doesn’t matter if we took a call or merely read through the landing page for 30 minutes before clicking to the next page. If no 2nd page has been viewed for 30+ min then that’s a 2nd session.

Example 2: 

  1. Jane visits your website home page at 11:59pm
  2. Jane clicks to a new page at 12:01am

That’s two sessions since the visit started on one day and there was activity on the next day.

Can an individual be counted more than once as a User?

Yes. If you’ve visited a site multiple times you will rack up multiple sessions, clearly. As you can see above, you don’t even need to visit multiple times to count as multiple sessions.

I) Bounce Rate

This is typically interpreted as: “a person goes to your website and then leaves without doing anything.” 

While that definition is accurate, here is a better one: a single hit session. In our Sessions/User examples above, both instances show multiple sessions. 

Therefore, the first session in each example would be considered a bounce, since they were “single hits” on one page without any further action before that session ended.

Are Bounces “bad?”

Not necessarily. Following the traditional definition, bounces are not ideal as it implies a person came to the site and then left without taking action. However, we don’t know if that person:

  • Bookmarked the site
  • Wrote down the practice number
  • Reviewed the landing page for 20 minutes before leaving

All of these “actions” by the individual would be considered positive outcomes of their visit.

Furthermore, as noted above, there are many instances where an individual simply gets counted as more than 1 session because of time. They’re still on your website and might even convert into a lead, but since their first session ended in a Bounce, it may be viewed as a negative. 

Bottom line on Bounces:

Watch your metrics over a long period of time and do not compare your bounce rate to another website’s. If your bounce rate is, for example, 60%. That seems a bit high. According to Search Engine Journal, most sites average between 26-70%.

However, if you’ve averaged 60% for 1-2 years and during this time you’ve managed to grow your traffic and increase your conversion rate from 1 to 2.5%, but your Bounce Rate remains 60%, then there’s no huge red flag as it’s not impacting your bottom line metric or KPI (Key Performance Indicator). If your bounce rate has been around 20% on average and it jumps to 40% then that would be much more of a red flag, even though 40% is still an excellent bounce rate.

You might see conversions fall because of this, which would be a sign you need to dig deeper to see why people are Bouncing. If your conversions are not affected, then you’ll still want to identify what change has caused the Bounces to jump.

I’m not advising you ignore Bounces entirely, but be aware the data can be misleading and keep your eye on the main KPIs you’re focusing on, which are: increasing conversions (leads) and increasing conversion rates.

II) Pages/Session

This is the most straightforward metric we’re tracking. Since we now know what a session is, consider this example:

  1. John visits your website home page
  2. John takes a call that lasts 30 minutes *1st session ends*
  3. John resumes activity on your website and clicks to a procedure page *new session begins*
  4. John clicks to a gallery page
  5. John leaves *2nd session ends*

There were two sessions from that single individual. The first session averaged 1.00 Pages/Session while the 2nd session averaged 2.00 Pages/Session. If that’s the only traffic you received during this time period your average Pages/Session would be 1.50, even though the user looked at 3 pages in total. Therefore, the data is off by 100%.

III) Average Session Duration

This metric is tracked per page and it is a little trickier to calculate because one session may end and a new one starts for a variety of reasons that we’ve already covered.

For example:

  1. Bill visits your website home page at 2pm
  2. Bill clicks to a procedure page at 2:01pm
  3. Bill reads through the procedure page for 7 minutes and leaves the site at 2:08pm

In this example, Bill is counted as one Session. However, his time would be calculated as 01:00 on the home page and 0:00 on the procedure page because there’s no timestamp to indicate how long Bill stayed on that second page.

Second example:

  1. Jen visits your website home page at 2pm 
  2. Jen pivots to email or another online distraction for 30 minutes *1st session ends*
  3. Jen is back on the home page 2:30pm (she never left this page so there’s no new click)
  4. Jen clicks to a procedure page at 2:35pm *2nd session begins*
  5. Jen leaves the site at 2:50pm *2nd session ends*

In this example, Jen has two sessions. The first session ends in a Bounce as no action was taken during her first visit. Therefore, her Average Session Duration for the home page during this 1st Session is 0:00.

Jen’s second session doesn’t begin until she clicks to a new page, so by visiting the procedure page she’s started a new session. It doesn’t matter that she looked at the home page again for 5 minutes. She spends 15 minutes on this procedure page before leaving. Again, her Average Session Duration for the procedure page during this 2nd Session is 0:00 because no second action was taken with either session

IV) Goal Value

Goal value is meant to assign a dollar amount per goal (lead) tracked in Google Analytics. I’d avoid using this metric in Analytics because there’s no way you can get an accurate number, for a variety of reasons:

  • the average value of a lead will likely vary wildly, more so if you have non-surgical and surgical leads
  • it only calculates the front-end value and not lifetime value of a lead
  • Analytics sometimes will inflate lead totals due to spammers/solicitors
  • Analytics will sometimes miss out on lead totals that are generated out of your tracking mechanisms

You’re better off using a robust CRM to track your leads along their path from lead to consultation to booked patient. This will give you far more detailed data on the performance and value of your leads in your sales funnel.

Three of the four metrics above are “behavior” stats. The behavior data in Google Analytics helps to paint a picture about the quality of the user experience when they visit your website. In other words, positive behavior stats (low bounce rate, high number of pages viewed per session, high average session duration) would, in theory, help convert more of your traffic into leads.

However, as I’ve noted above, it’s not that simple. Remember that context is everything when you’re evaluating your Google Analytics data. Don’t completely brush off red negative behavior metrics, but do not panic if the numbers seem “bad.”

Lastly, do not compare your stats to another website or “website averages.” Instead, compare your stats to yourself to see how you did this month vs. last month and this year vs. last year.

behavior metrics

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