10 Google Analytics mistakes – Are you making these?
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10 Google Analytics mistakes – Are you making these?


– 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.

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