How to use Google Analytics, step by step
- Google Analytics
- Before we begin...
- Step 1. Create an account
- Step 3. Analyzing the interface
- Demographic data
- Other menu options
Step 4. Testing Metrics
- Exhibit 2: Check last month's visits from the city of Buenos Aires.
- Step 5. Other Public Menu Options
- c) Mobile
- (d) Flow of visitors
- Step 6. Acquisition metrics
- Overview and Channels
- (a) All traffic
- (b) All references
- c) Keywords
- d) Campaigns, cost analysis and Adwords
- e) Social
- g) Search engine optimization
- Step 7. Behavior
- (a) Overview
- You may be interested:
As Community Managers one of the most important things we have to do is to use metrics to evaluate our work.
It is useless to carry out actions that we consider more or less successful if we then do not have tools that tell us effectively how they are working or if we must modify our strategy to reach our objectives.
In the end, we must not lose sight of the fact that one of the main objectives of the Community Manager is to bring traffic to the web (so that it translates into both positioning and objective sales) and therefore it is absolutely critical to analyse the evolution of the visits a web receives in maximum detail in order to make the right decisions.
Within the tools and applications that show statistics, Google Analytics is undoubtedly the queen of the place.
It is Google's solution for obtaining web statistics, with three fundamental advantages: it is free, it is easy to use and it is tremendously detailed.
The raison d'être of google analytics is therefore to get feedback to make decisions and modify our online business strategy.
Google Analytics offers us a wide variety of information about the contents in which more people stop (which gives us clues about what interests our users), whether the page we have is a good showcase, whether it has sufficient resources and mechanisms to encourage the public to act, and so on.
Google Analytics is focused on the traffic of web pages both off-site (what happens on the internet as a whole) and on-site (route of a visitor once he enters a website).
Despite its ease of use, for those who are not accustomed to it, this tool can be somewhat complex a priori. So let's take Google Analytics step by step so we don't get lost in so much choice.
Before we begin...
Not all accounts can be analyzed with Google Analytics
Websites and blogs that are open and hosted on wordpress.com are excluded from this possibility, as WordPress does not allow the installation of external elements on its pages.
On the other hand, on pages that use wordpress.org it is very easy to do this process, since it is enough to download the specific Google Analytics plug-in, install it and activate it (we will see how).
In the rest of the pages it's also simple: just insert in the code (inside the <head> the tracking code (we'll see where) and you're done.
- To open a Google Analytics account before we need a gmail account
It's a prerequisite that you're going to apply to us. If we don't have it, we'll have to create it for ourselves.
- Google Analytics will allow us to manage from our gmail account all the accounts that we want (web pages that we are managing), each with their reports of visits, visitors, conversion of visits if they are profitable or not, and so on.
As a previous step, we analyzed some basic terms that we will see along the post, to be done with them:
- VISITS: Total number of visitors to the website. Note: Cookies insert a chip and in google analytics our cookie works half an hour. That means that if we access again after that time will tell us as a new visit.
- UNIQUE VISITORS: Visits from different IP (different people who visit us, non-repeated users)
- PAGES VIEWS: Total number of pages or articles viewed or number of times the pages have been shown. Its number is always greater than the number of visits, since a user can go through 3 or 4 pages in the same visit.
- PAGES PER VISIT: Average page views per visit or user to the website
- REBOTE PERCENTAGE: Users who only consult one page per visit and leave. This percentage is usually quite high (70% approx) as there are many people who can get to the blog by other means, or access the web and realize that the content is not what they were looking for. The lower it is, the better.
- MEDIUM DURATION: time users are on our blog
- PERCENTAGE OF NEW VISITS: Number of new visits that we have with respect to the recurring ones (it gives an idea of the fidelity that we generate).
Step 1. Create an account
As always, the first step in analyzing our statistics will be to create a Google Analytics account and link it to the web for tracking.
We entered http://www.google.es/analytics and found the following entry screen:
Clicking on the upper area (Create Account button) asks us to provide you with the details of our gmail account. As we have commented before, if we don't have one, we must create one in order to have everything interconnected.
Once we have entered the data, we see the following screen asking us to register in Google Analytics (in the upper right area we see the gmail account with which we entered):
If we press the button "Register" we will get the screen where to fill in the data for the account configuration (web or blog) that we want to manage: URL, time zone, etc..
Step 2. Activate the tracking code
If we have a web out of wordpress, we will copy and paste the code in the header. If instead we have a website made with wordpress.org will suffice to download the plug-in google analytics (we download a zip) extract the folder "google-analytics-for-wordpress" and take it to the ftp of our website by placing it in the folder "wp-content => plugins" (to manage transfers between our hard drive and our ftp we can use free programs such as Filezilla.org)
Once placed in the Ftp, we will return to the administration panel of our web/blog of wordpress.org and activate the plug-in:
In the upper zone we will be informed that the plug-in is activated but that Google Analytics is not active. To activate it we must select the Analyzer Profile in the link that indicates us and takes us to a screen where we must place the UA of our page (tracking code previously seen with format UA-XXXXXXXXX-X).
Once placed gives us the ok and if we now log in to the google analytics account with our gmail account, we can see the data (NOTE: if we have more than one account registered, we must choose which one by clicking on it):
As it is a new web page the data will appear to us to zero:
NOTE: If we already have a page and we want to know its tracking code, we can always do it in the Administrator tab (in the top menu) > Tracking Information Section > Tracking Code
Step 3. Analyzing the interface
Since a new account with zero data is not the best option to show all the options of this tool, we will use an existing account with a certain path.
The first thing we see when accessing our account is a summary panel called "Public Overview. In it we see at a glance the main general metrics obtained in the last month, such as unique and recurrent visitors, page views, number of pages per visit, average duration, rebound percentage, etc.
In addition, in the upper right zone we will see the period referred to by the metrics
Both in the lower part of the Overview panel and in the Geographic Information section we will have access to the Geographic Demographics, i.e. where our visitors come from and in what language they speak.
For example, if we click on Country/Territory in the Overview panel we will normally get the first 10 countries of origin, but if we click on View all the report in the lower right area we will get the whole report.
The location can appear in the form of a map in the tab "Graph of visits by location" or as a list in the tab "Explorer" (in the lower right we will modify the number of entries to be displayed on the page to expand the list).
Other menu options
Acquisition => Where my visitors come from (organic search, direct search, links from external pages, social networks, etc.).
Behavior => How people act on my website (new visitors, frequency, interaction, pages viewed per visit, length of visit, etc.)
Conversions => It is a zone linked to the objectives. For example, in a blog we want them to know us and contact us or spend a certain amount of time reading the content we publish, or fill out a form (subscription by mail), etc..
In Google Analytics we can define our objectives and the tool will give us both in % and in economic value an estimate of the value of the data (WARNING: this valuation is only approximate and serves to help graphically to see everything better, but it does not have to be real unless it is very defined, which is not usually usual).
The key to the data is to see if the objectives are being met.
Step 4. Testing Metrics
The first step in analyzing our metrics is to select an analysis period as a benchmark measure.
GA by default takes us out the last month, but we may be interested in the last year, the last quarter, the last week, yesterday's day ... The recommendation is that the metrics do not expand much in time and for this in the calendar will mark the ideal dates.
Test 1: Check the number of unique visitors from 1 September 2013 (date page was created) to 1 March 2014.
To do this we select the dates in the previous calendar or write them directly in the boxes (this last option does not always work properly, better to do it in the calendar)
Press the Apply button and the corresponding graphic will appear:
This graph shows us for example how the page is progressing upwards, with a valley at the end of December/beginning of January due to the Christmas holidays, in which users connect less.
Exhibit 2: Check last month's visits from the city of Buenos Aires.
To do this we set the period, we go to the Demographic Data zone, then to Location and in the Search field, we look for Argentina and in the lower zone of the map, clicking on it we get the different cities (we can see it in the form of a map, or in the form of a graph by pressing the tab "Explorer").
In any case in the lower zone we will see the list by cities:
Test nº 3: Check the percentage of rebound of February with respect to November to know if we have improved or not.
As always, first place the range of dates and then click the box Compare with and in the dropdown select "previous period" (if we choose a month, take the previous month, if we choose a quarter, take the previous quarter).
If the website has been running for more than one year, select "previous year" in the drop-down menu and it will compare us with the same period of the previous year's calendar (e.g. the month of February of this year with the month of 2013).
We press the Apply button and the graph will give us the data in two colored lines, one for each month.
This screen tells us that the rebound percentage is -45% than the previous month, which is positive, because the lower the rebound percentage, the better (implies that people who access the page more than in the previous month, do not reach the page and go).
If we choose to see the rebound percentage metric in the upper left dropdown list, it will also appear graphically (in the previous screen the graph only referred to visits):
If we select metrics such as Age and Interests, the data will be set to zero, because they are data privacy sensitive.
This information is very useful but to get this data we must do so through the Google Adwords tool that we will see in future post.
If we go down the same page we can see some additional information, such as geographical indications (language and location), and so on. However, we can also click on the menu options in the left column for specific information.
Step 5. Other Public Menu Options
It gives us three kinds of data:
- New vs. recurring visitors (users who visit the site more than once)
- Frequency (number of visits and days since last visit, in 2 tabs)
- Interaction: duration of the same and number of pages viewed after the session, in 2 tabs
We see how if we have selected two periods, GA will get all the data on both of them to make better comparisons.
Tells us where they're looking for us (mobiles, etc.)
- Browser and S.O. (why browser and operating system find us)
- Network (which phone company they use, really uninteresting data)
If we check it for one period only:
(Going down with the cursor we will be able to visualize the whole list enlarging the number of entries as it is habitual)
These data tell us for example which browser we should take more care (especially if there is one in which our website fails or looks worse ...)
Today the design must be what is called Responsive so that our content can be read comfortably both on computers and mobile phones. If the visits to mobile phones go down a lot the same our design for mobile phones is not very optimized.
This menu option gives us information on two topics:
- Overview (how many people see us by desktop, by mobile and by tablet)
- Devices (what type of tablet or mobile phone users see us on)
(d) Flow of visitors
This option gives us a visual graph where we can check the interactions of the page (where they come from), if they stay on a single page, if they visit several, and so on.
It's just a visual way of giving us the information:
Step 6. Acquisition metrics
This menu area basically tells us where our visitors find us from, how they do it and how much our traffic turns into real money.
Overview and Channels
The first two options give us the information in a more summarized form:
It is the result of our SEO positioning. It is very interesting that this value is the highest possible, as they will mean visits that arrive "effortlessly", ie without social networking work or link building (links to other websites), etc..
- Direct is
the number of visitors who find us by directly typing our URL
from links from social networks
coming from other pages or that have linked to us post (that's why they thank us so much for the references in the blogs)
Visits coming from other pages or that have linked us in their post
Clicking on the title of any of the options will give us more information. The problem is that in the organic search (the most interesting to know which keywords they find us by) the breakdown is minimal, entering most in the category "(not provided)", so we are left without that information:
(a) All traffic
This submenu is very interesting because it tells us exactly where we are from (whether specific web pages or link references, etc.):
(b) All references
It tells us in detail where the visits come from through links:
If we get into each of them (clicking on the title) will give us the detail of the information (if linked from the Home "", etc.).
Here GA distinguishes between payment and organic keywords. As in this case no paid campaigns have been made, this one goes to zero and instead the totality will appear in organic:
This option is similar to clicking on "google/organic" in the Overview. Again we find ourselves with the problem that Google does not provide us with information on most keywords.
d) Campaigns, cost analysis and Adwords
Both refer to payment campaigns that we will not explain yet. The Adwords option will ask us first of all to link both accounts (Google Adwords and Google Analytics).
Very interesting menu option for the Community Manager, since it gives us complete information about the origin of our traffic derived from the networks:
If we click on any of the networks (e.g. Facebook in this case) we will get the full detail:
This gives us information such as which post have interested more or had more visits, etc.. It is therefore useful to know the tastes of users and to test the improvements.
NOTE: If we are interested in using Twitter, it is better to do so from this section (Acquisition > Social) than from Acquisition > General overview, since in this case both the visits coming from Twitter and from Buffer are counted, while in the first case they are not.
However, if for example we look for twitter visits from Barcelona yes, because we can access the primary dimension and then the secondary, etc.. (visitors => city) getting data (higher rebound, lower visits, conversion, etc.), which does not happen from this section.
g) Search engine optimization
This is a tool for Webmaster Tools and therefore we will leave it for another occasion 😉
Step 7. Behavior
This menu option with several sub-options basically tells us which are the destination pages visited by users on our website, which work better or worse, etc..
As always, this option shows us a basic summary according to the chosen period:
This screen gives us information of several metrics, among others, of the percentage of exits (the last of the basic data), that shows us which page the users use to exit having been before in other contents of our site.
This data is different from the rebound percentage, because although both say where users leave, the output indicates that they have visited another page of the website (not just one and have left, as in the rebound).
If for example we click on the best article (the most visited) we'll see everything more summarized.
b) Content of the Site
Here we will obtain detailed information of the content of the web visited by pages, destination pages, exit pages, etc..
c) Site Speed
Shows us general information about the average page load time (from clicking to full load), average redirect time, average page download time, etc.
In this case we will see a very high average full load time (basically because the website contains many photos) and gives us information to try to improve it.
In addition, in the same submenu we will be able to consult the times for each page of the web, as well as suggestions of speed (a very interesting option for the developers). For example:
d) Searches on the site
It is also interesting because it shows us information about the use of the "Search" bar within the page (if it is used too much or too little, and if it is used, what words find us):
Shows the events or outputs of the page through widgets, etc. (it would be like actions or clicks of users out through banners, blogrolls, etc.).
f) AdSense / Experiments / Analytical
The first has to do with google advertising campaigns and therefore we will not see it at this time.
The experiments allow us to experiment with various options to improve the page (perhaps better with soda) and the Analytics gives us a redirection error, so we will leave it for another time 😉
A. Find out which page my visitors visit most on a given date.
1) Place the date range,
2) Behavior > Site content > All pages3) Sort them
by average page (if we do not do so the same result is misleading, because a priori we only see the first 10 entries of the list and would order us only about them)
Note: Some of the results refer to wp-admin, previews, etc., which imply the administrator's own time (e.g. uploading the page, keeping it open, etc.). We will have to analyze this page by page to discard some (if we don't know what they refer to we can click on the little square that appears in the name of each page and it will take us to the link).
- Find out which is the page through which they enter our site that generates more willingness to interact
(for example, keep looking, or because it has a banner that takes us to another side of the page, or leads to internal links, etc.) => we invite you to browse our page.
1) Set the date range2
) Behavior > Site content > landing pages3) Sort
by pages per visit (in the middle of the table) and check which one gives us the most visits.
Step 8. Conversions
In this section we will associate economic objectives with certain measurable metrics (e.g. if we know that for every 10 visits to our website, 1 buys from us and an average of 5€ is spent, we can determine this in GA so that we assign a value of 5€ to each 10 visits).
Thus, when analysing the data, GA will use these conversions to give an economic value to its statistics (e.g. if we have obtained 100 visits from Seville and 1000 from Valencia, it will be understood that Seville contributes 50€ and Valencia 500€).
Objectives don't have to be based solely on sales, but we can set them for blog subscriptions, etc.
This section is not at all easy to configure, as it is not always so easy to assign a value to certain metrics and requires a deep knowledge and establishment of constant patterns of our users, which is complicated to define.
If we don't have established conversions (as is the case) Google Analytics will first ask us to configure them:
To do so, click on the "Configure target" button and you will be taken to a screen on which you can click on the "Target Name" button and then on the data we are interested in (depending on the type of website and the target of each one).