When you face an analytical tool for the first time you may feel lost. That’s why in this post we’re going to talk about the basic metrics of Google Analytics, to give you a first orientation of what to interpret and how to do it.
How to interpret Google Analytics
Before entering the subject there is an important point that you have to take into account and that affects all the metrics (basic or not): the figures can only be understood correctly if they are compared and, ideally, they should be confronted with a similar period. That is to say, if you can compare the data of this month with those of the same period of the previous year, it is much better than doing it with the data of the previous month.
This is done to avoid seasonal biases. The month of December is not the same as the month of January, but you should see the evolution of the month of December of one year with respect to the previous one. Is it a lot or a little 100? If you have 4.8%, are you right or wrong? The answer is in the increase or decrease of the metric with respect to what happened at the same time in previous years.
Now we can define what are the basic Analytics metrics. Look at them and you can get an idea of the evolution of your online store.
# 1 – Basic metrics: users
The “users” metric refers to all those visitors who have opened at least one session during a given period of time. Here both new and non-new users are counted.
This is probably, along with the “sessions” metric, one of the most followed metrics. And is that after all are those that quantify the traffic of a particular website in broad strokes.
A large number of users will assume that you are attracting a large audience (that is, a lot of traffic). The important thing is to ask yourself if that audience is converting (buying, subscribing …) and so you will know if your strategy is working.
EXAMPLE: imagine that you have a shoe store on the street. The "users" metric will tell you how many potential customers have entered your store during a month, counting that a person equals a user. From that data, you should ask yourself how many of those users have bought to know if what they find inside your store is of interest or not.
# 2 – Basic metrics: sessions
While the “users” metric refers to unique individuals, the “sessions” measure the number of times those users interact with a given site over a period of time.
The denomination “sessions” has a lot to do with the way in which Analytics performs the measurement: by unique browsers. This means that the same user can perfectly access different times to the same domain during the same period of time from different browsers, and Analytics would count it as different sessions.
If you have a high number of sessions or, at least, it is higher than the number of visits, it means that your users are recurrent and return frequently to visit your website.
EXAMPLE: recovering the example of the shoe store, the "sessions" would measure the number of times that users have entered your store and have been there for a while. This metric would account for each of your users' visits separately. If you cross it with the data of "users" (how many different people have entered your store) you will be able to know if those users are recurrent. That is, if your store has 10 users in a month but 30 sessions, it means that those users have entered your store 3 times on average each.
# 3 – Basic metrics: number of page views
It is about all the pages within your site that users have seen during all sessions. That is, we talk about the total number of page views.
The main difference between “pages” and “sessions” is that a user who accesses a website can see different pages during the same session, in such a way that pages and sessions are not equivalent.
A large number of page views is a metric to interpret with care. It will be positive for a medium that sells advertising space, but in an online store it is very likely that you want fewer page views and that users go directly to close a purchase.
EXAMPLE: Many people have entered your shoe store for a month and each one has been inside the store for a certain time. The number of visits would indicate the amount of shoes that all users have tried during those 30 days. Surely you would be worried that your users tried many shoes but bought few.
# 4 – Basic metrics: pages per session
The “pages per session” are the number of pages that, on average, users see during each session. It is important to emphasize that we speak of an average and not of an absolute data since a user A can see 29 pages per session and one user B only one.
The interpretation of the pages per session is very similar to the number of page views: it should be crossed with the conversion data. If your users see many pages per session and do not buy, something is failing, but if they see only one and buy insurance you do not care so much about the data.
EXAMPLE: you have noticed that every person who has entered your shoe store for a month has tried, on average, 3 pairs of shoes. Surely now you will like to cross that data with the total sales data.
# 5 – Basic metrics: average duration of the session
We return to observe a data that is average, in this case, the time that each user uses in a session, and is expressed in seconds. A specific user enters the web and sees 3 pages during a session, dedicating 1 minute to each one. Then, the duration of your session would be 3 minutes. This basic metric calculates the average time spent by all users.
It is another metric that is not enough to compare with the previous period: it is also necessary to know if with that time of stay per session is enough to close a conversion and, from there, ask yourself if increasing or reducing it could have an impact on the business.
EXAMPLE: thanks to this metric, you know that this month in your shoe store your customers have been looking at shoes for 6 minutes on average. The next thing you should value is if that time is enough to seduce them and make a purchase.
# 6 – Basic metrics: bounce rate
It is one of the most controversial Analytics metrics. It refers to all users who access a single page of the site and leave without seeing any more. We told you more details about this concept here.
The bounce rate does not value the time spent so that, for Analytics, it would be the same for a visitor to see a page for 1 second than for 25. If those 2 visitors only visited a page, for Analytics it would be bounced in both cases, Although the time of permanence is undoubtedly indicative of the user’s engagement and therefore of their level of interest with respect to our offer.
The rebound rate may seem on paper always a bad figure when it is high, but here we must relativize. For example, if we are measuring a landing page that communicates a specific message and does not require further interaction on the part of the user, entering and leaving that single page does not indicate a lack of interest.
EXAMPLE: 30% of all users who enter your shoe store look at a single pair of shoes before leaving. Analytics counts them all as part of the rebound, but does not take into account the time they spend observing and testing that unique pair of shoes, which may be indicative of their real interest in the product.
And up to here the first basic metrics of Google Analytics that you must follow to know the status of your eCommerce, webpage, Blog… Is there any more that you want to know about?