Semalt: 3 Steps To Creating Accurate Google Analytics Reports

23.05.2018

Semalt: 3 Steps To Creating Accurate
Google Analytics Reports

Some companies may experience a period of increased traf c, which then gradually declines. It could raise the alarm
because nobody wants their referral traf c to fall. However, one primary cause for traf c decline is the ltering of
internal traf c from Google Analytics reports. Also, implementing an exclusion lter for referral spam will reduce
the traf c some more.

First of all, companies have many employees accessing their website from different computers on a single day.
These visits may record as direct traf c to the website's analytics. In addition to this, referral spam has become so
rampant that it outpaces the organic searches and skew data in the Google Analytics in the worst ways.

Alexander Peresunko, the Customer Success Manager of Semalt, assures that applying the two lters may result in
a signi cant decline in traf c data. Nevertheless, as much as this is apparent, the company may be doing quite well
in reality.

Importance of creating lters in Google Analytics

Spotting referral spam in Google Analytics is easy. For example, if the website currently has two views: the raw data,
and the ltered views, there are website domains that appear in one and not the other. If you apply lters well in
Google Analytics, referral spam only makes it to the raw data but not the ltered view.

Referral spam was a huge problem between the years 2015 and 2016. The most af icted were small business
owners since their link pro les are not as robust as those of larger companies. The result was that referral spam

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23.05.2018

could take over the top referrals analytics reports.

The reports can record an increase in traf c while it was not in real sense. It is one of the implications of having
referral spam traf c.

What do people know about referral spam?

Referral spam is fake traf c, or what most people call ghost traf c. The
source of this traf c disguises itself as referral links from legitimate sites,
which they are not in most cases, with one goal which is to trick the site's
owner to click on their domain when it appears in the Google Analytics
reports. Google is now ahead of the situation and has included a Bot

ltering option in Google Analytics to make sure that it removes any
known referral spam from appearing in the analytics reports.

Another source of skewed analytics traf c data is the internal traf c from the company itself, especially if it has a
customer service department that has to walk customers through a step by step process on how to navigate,
complete a form, or an application of some sort.

The best way to acquire a more accurate picture of the website data is to create a ltered view in analytics. The
lters should help exclude any referral spam or internal traf c and allow you to view data devoid of misleading data.

Task #1 Creating the new view

Importance: A new view will help in ltering traf c without making any alterations to the raw data.

Description: It is a duplicate of all the analytics data from which you can make modi cations to, and are visible once
you open your Google Analytics account.

The steps to create a new view are as follows:

Log in to your GA account and select "Admin."

Click on "View" in the right column and select "Create new view."

Give your new view a name, then save and exit.

The next step is to change the name of the original or un ltered view. You can see the different views you have
in the Admin overview page. Click on your original view which will open a View settings page. Input the new
name for your original view to something that would make sense to you like "Un ltered view," or "Raw Data
view."

Save the new settings.

Task #2 Turn on Bot Filtering 2/3

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23.05.2018 Importance: This is the view that allows you to exclude the referral spam
traf c.
damaging effect nevertheless.
The process to follow is to head to the Admin Overview page to select the
just created ltered view. Under the View Settings page, scroll down to
"Bot Filtering" checkbox, check it, then save and exit.

The method is an excellent starting point for ltering spam, but some will
still slip through. However, it still serves some purpose as it reduces the

Task #3 Creating the lter to exclude internal tra c

Importance: For more accurate data, you must exclude any traf c coming from inside the company. Employees that
make regular visits to the company website can signi cantly skew your data.

Search for "what is my IP" on Google.com to know what your current IP address is

In the new Filtered view, select Filters

Click on Add Filter

Choose to create a new lter. Input a preferred name for the lter, select "Prede ned" in the Filter Type.
Choose to "Exclude" the "traf c from IP addresses" and then select "that are equal to" from the "Select
expression" box. Then enter the IP address as returned by Google.

Save and exit.

You can now record when you make changes with Google. View any graph data from the analytics report and then
click on the arrow beneath the graph to "Create a new annotation." You can now record the annotation,
remembering to include details for the change as well as the date.

Conclusion

Google Analytics is not 100% accurate when it comes to top-line traf c
data. By creating a new view, you are in a better position to lter out any
traf c and see the implications it has for your data.

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