- Are you making these Google Analytics mistakes?
In this video I'm gonna go with you
through 10 checkpoints to ensure
you're using Google Analytics correctly.
All and more coming up right after this.
(upbeat music)
Hi there and welcome to another video
of MeasureSchool.com where we teach you
the data-driven way of digital marketing.
My name is Julian and on this channel
we do marketing tech reviews, tutorials,
and give you tips on better Google Analytics use
just like this one.
So if you haven't yet consider subscribing.
Now Google Analytics is a very complex tool.
You have a lot of configurations,
you have a lot of businesses that work with this tool,
but often times you find yourself
that your Google Analytics is just not working out for you.
Maybe you are making some mistakes,
and today I want to give you 10 checkpoints
that you can go through with me and see
if you have done them correctly
or configured your Google Analytics correctly
to take those points into account
so you can do your analysis with Google Analytics.
Now we've got lots to cover so let's dive in.
Number one, not setting up goals.
Now once you have Google Analytics installed,
you should set up goals right away.
Goals are basically what gives meaning
to your data in Google Analytics.
So you can tell Google Analytics specifically
that this action or this outcome is desired
in your Google Analytics installation,
and it will carry throughout the interface.
So when you look at your page views
you will be able to see if they are good or bad
because you will know how they relate
to your actual outcome, to your goal
that you want your users to achieve.
So goals are very important to set up.
Now there are different types of goals.
You can tag a page view as a goal conversion,
you can tag certain events as a goal conversion,
or use e-commerce tracking to track revenue
that is generated on your website.
All types of goals are indicating to Google Analytics
that this is the desired outcome
that you want your users to take on your website
and then track that in Google Analytics as well.
Number two, not using UTM parameters.
Now if you ever looked into your sources
or acquisition report, you probably asked yourself
how does Google actually know
where the user is coming from.
Now it's pretty easy.
If he comes from another website, Google Analytics
can actually pick that up automatically.
But there's also a column often times,
or a row often times, called direct/none,
and this is for people who Google couldn't really identify.
And that's where UTM parameters come in.
So if you have a source where you explicitly know
that the user is coming from, for example, Facebook
or your Bing advertising, and you want
to tell that information to Google Analytics,
you need to be using UTM parameters.
Now if you don't know what UTM parameters are,
then check out our video right over there.
But it's basically a way to explicitly tell
Google Analytics this is where the user just came from,
and you should definitely be using them
if you have any kind of outside sources
that you want to attract with Google Analytics.
Mistake number three, not having clean data.
Now data quality and Google Analytics
doesn't take care by itself.
You constantly need to look through the data
and see if it's plausible
and if there are any tracking mistakes.
Now that starts with:
is the data actually correctly tracked,
do you have the JavaScript code on all the pages,
and is it executing actually correctly.
Second thing, if the data is coming in,
do you want to block some data out.
For example, spam referrals, or your colleagues,
or yourself that is surfing on the website.
That is all data that you need to ensure
that it doesn't enter your Google Analytics account
because you can't take it out later on.
Now there're more configurations within Google Analytics
that you can ensure data quality with.
So for example, if you have different domains,
you might be eligible for cross-domain tracking.
I would definitely recommend to always look
through your account, see if the data is still plausible,
and ensure data quality on a regular basis.
Number four, collecting personal identifiable information.
Now PII is something that Google Analytics
doesn't allow you to send into the system itself,
that's because of privacy reasons,
and you need to make sure that you are not
accidentally sending that information over.
Now what is PII information.
That's, for example, the email address, the phone number,
or first name and last name.
That's information that Google Analytics doesn't want
to send and to have in your system,
in their system, basically in their database,
because they don't want to be liable for that.
And that's why they actually prohibit
to send it in their terms of service.
Now if you are sending that information,
you are in danger of your Google Analytics account
basically being shut down
because you've violated the terms of service.
So ensure that you're not sending this information in,
and that can actually happen quite often accidentally.
So for example, Google Analytics is tracking page views.
So if any kind of page view, or the URL of the page view,
has any kind of PII information
that needs to be filtered out
before it actually goes to Google Analytics.
So if you want to check this,
go into your all pages report
and type in email or @ sign and see
if there's any email address in your URLs.
That can happen, for example, when somebody types
in a form field and puts in an email address
and that gets captured in the URL somehow.
Then you need to go back and change the form around
in order to not send that information
over to Google Analytics.
Number five, not using a tag management system.
Now it's pretty old school to install
the actual JavaScript onto your page
unless you have a very good reason to do that.
Nowadays you normally use a tag management system,
such as Google Tag Manager, Adobe DTM, or Tealium,
to manage your tracking codes
but also your other marketing codes,
like the AdWords conversion tracking
and the Facebook pixel, for example.
Now this is not a must-do, but definitely
a good practice to keep in mind to put all your codes
into a tag management system and handle them from there.
That way you can also delegate
a bit of the responsibility of these codes
of keeping them up to date
to the tag management system itself.
And it's definitely something you should be taking care of
if you are installing Google Analytics on a new website.
Number six, not segmenting your data.
So if you go through Google Analytics
and you are analyzing and coming to a conclusion,
have you actually segmented your data beforehand?
Now data in aggregate doesn't really make sense.
The classic example is users
who are prospects to your website
and actually already customers to your website
who have bought something before,
they tend to use your website completely different.
And therefore you should be segmenting your user groups
in order to be able to have a correct analysis
and ensure that you are deriving the right insights
from this user group and the behavior that they're doing.
So always segment your data
when you are analyzing within Google Analytics.
Mistake number seven is something that I don't see
that often anymore but it sometimes happens still,
using UTM parameters for internal links.
So some people actually use the sources report
to track internal links because they want to know
how many people actually came from the home page
and bought my product.
And so they start tagging the links internally
on their website, on their internal links,
and that's a big mistake because you are screwing up
your source data and overwriting
the actual last known source in Google Analytics.
So actually later on you won't be able
to attribute your conversions to the last known source
but only that internal link that was clicked.
A better idea is to actually use
event tracking for that purpose,
built-in events to track your internal links
and what interactions the user has done on your website.
Number eight, not using annotations.
Now annotations are really about giving context
to your data and the manual form
of just writing notes into your data.
There's this little functionality within Google Analytics
that you can click under the chart
and add an annotation to your data.
This can be something like "we launched this week"
or "we changed platforms" or "Facebook advertising
"was switched off for a day or two".
And when somebody looks into that data later on
and analyzes it, he can take those annotations,
those notes into consideration in his analysis,
and that might help him to do better analysis
and draw to right conclusions with those notes in mind.
So definitely use annotations
if you haven't made use of them yet.
Number nine, misunderstanding the Google Analytics model.
Now Google Analytics is heavily used
on the JavaScript code that is installed on your page.
Now the way Google Analytics tracks
is just a model of how they think it should be
and we have all gotten used to it.
But once you start comparing data
with other system, with other tracking systems,
or even your backend system, how many orders came in
and how that actually relates to Google Analytics,
you will notice very quickly
that the data doesn't stack up.
And that's because Google Analytics has
a very specific model that they deploy on their data
and that's something you need to be aware of.
So what are actually sessions,
what does a user actually mean within Google Analytics,
how is bounce rate defined,
all these different definitions actually shape
the model of Google Analytics,
and you need to be aware of that
in order to understand your data correctly.
So if you want to brush up on that
I would definitely recommend
the new Google Analytics course from Google themselves
that you can check out in the description below.
And finally number 10, not taking action.
Now this is something I have already mentioned
in our 10 Skills to Master within Google Analytics video,
but this is very an important one:
what do you do after you analyze your data
within Google Analytics.
You actually not just puke out reports and give it
to people that don't do anything with it.
You need to go to the step of actually
recommending stuff, taking action on your data.
There're great tools for doing this.
For example, the Custom Audience feature
within Google Analytics to re-target people on AdWords,
or Optimize, which is an A/B testing solution
of Google, that you can utilize
in combination with Google Analytics.
But also taking that data, presenting it
to your stakeholders, but also recommending action.
And only if that data actually changes behavior
within the company or the people
who are using the website, then you are going
full circle with your Google Analytics use
and you get the most out of the tool.
Alright, so there you have it.
These are my 10 mistakes that you shouldn't make
within Google Analytics.
Now I would love to hear from you
if I forgot anything or if you're a consultant
and you actually have clients on Google Analytics
and see mistakes very often.
I'd love to hear from you in the comments below,
if you have anything to add.
If you like this video I would greatly appreciate it
if you could share it to a friend or colleague,
or maybe a client who might find this useful.
And if you haven't yet, then consider
subscribing right over there,
because we bring you new videos every week.
Now my name is Julian.
Till next time.