Google Analytics reports are not easy to understand for an average Joe.

For example, look at the following data table

Unless you already know Google Analytics really well, you may have a hard time figuring out what this report is all about.

Following are some of the common questions asked by non-geeky clients:

• What is google /cpc?
• What are sessions?
• What are new users?
• What is bounce rate?
• Why there are two entries for Facebook?
• What is t.co? Is it a spam?

The only terms which look familiar to a not-so-Google-Analytics-savvy person (like your client) are Google and Facebook. All others are alien terminology.

So even after having all of the website usage data, such GA reports are pretty much useless for an average website owner. He would most likely need the help of a web analyst to translate these reports for him.

The traffic report above could have been made simpler something like the one below:

Much easier to understand.

Isn’t it?

We are going to do something like this for our GA reports to make them easier to understand especially for our clients.

By the way, did you know, Google Analytics can report the performance of a marketing channel via several traffic sources? 

For example, Google Analytics can report traffic from Google Ads as:

So if you are not very careful, you may just take the traffic from google /cpc into account while reading reports and can draw the conclusion that Google Ads sent 9,244 visits to the website in the last 1 month.

When in fact, Google Ads sent 21,737 visits (9,244 + 11,891 + 602) to the website in the last 1 month.

Now how many marketers and/website owners go through the trouble of consolidating all of the marketing channel’s data before interpreting it?

Not many.

This scenario is quite common and occurs mainly when the ad campaigns were tagged without any proper thought/planning i.e. when there is no consistency maintained in naming the various campaign tracking parameters and/or when the campaign tracking parameters do not match the GA predefined channel rules.

For example:

Someone could first choose to tag their ad campaigns with ‘CPC‘ as traffic medium and then later tag the new campaigns with ‘cpc’ as the medium. And then further down the line, tag new ad campaigns with ‘ppc‘ as a medium.

In that case, Google Analytics can report Google Ads traffic as:

Note: In Google Analytics, the names of traffic sources and traffic mediums are case sensitive.

So google / cpc is different from:

1. Google / cpc
2. google / CPC
3. GOOGLE / CPC

But in reality, they still all refer to the same marketing channel i.e. Google Ads.

Many marketers are not aware of this issue and/or do not always religiously filter out such data every time they interpret the traffic reports. Many take only those traffic source(s) into account which appears as top 10 in the GA acquisition reports.

Google Analytics is not going to automatically consolidate the traffic data from google / cpc, Google / cpc, google / CPC, and/or GOOGLE / CPC and then report it to you as “Google Ads” traffic. This is something you would need to do it, yourself. And if you don’t do it then you will get poor analytical insight from your GA reports.

So the first step is to identify all the traffic sources which are basically Google Ads Traffic. Then you need to consolidate the data from different Google Ads traffic sources into one custom Google Ads channel.

To accomplish this task, you will need to create a new custom channel for Google Ads via custom channel grouping.

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Follow the steps below:

Step-1: Navigate to the ‘Admin’ section of your main reporting view in GA.

Step-2: Under the ‘View’ column, click on Channel Settings > Channel Grouping:

Step-3: Click on the ‘+NEW CHANNEL GROUPING‘ button:

Step-4: Name your new custom channel grouping (say ‘Marketing Channels’) and then click on the ‘Define a new channel’ button:

Step-5: Define the new Google Ads marketing channel as shown below:

Step-6: Click on the ‘Done’ button and then on the ‘Save’ button.

Note: It can take up to 24 hrs for your changes to take effect and be visible in your GA reports.

Step-7: Navigate to Acquisition > All Traffic > Channels report and then select ‘Marketing Channels‘ as a primary dimension from the drop-down menu:

Note the total number of sessions from Google Ads. It is 21,737 which matched our previous calculation.

This proves that the new marketing channel we created for reporting on Google Ads traffic is consolidating the data correctly. You would need to do such tests every time you create a new marketing channel in GA.

Example #2: Traffic from Facebook

Google Analytics can report traffic from Facebook via the following traffic sources:

So if you are not very careful, you may just take the traffic from facebook.com / referral into account while interpreting reports and can draw the conclusion that Facebook sent 965 visits to the website in the last 1 month.

When in fact, Facebook sent 1,009 (965 + 19 + 13 + 10 + 1 +1) visits to the website in the last 1 month.

So if you are taking only facebook.com / referral traffic into account while trying to understand Facebook performance as a marketing channel, you will draw wrong conclusions, you will misinterpret the data.

The traffic from all of these traffic sources is basically Facebook traffic. But Google Analytics is not going to automatically consolidate all of this data for you and report it to you as Facebook traffic. This is something you would need to do it, yourself.

So the first step is to identify all of the traffic sources (referrers) which belong to Facebook. Then consolidate the data from different Facebook traffic sources into one custom Facebook channel.

To accomplish this task, you will need to create a custom channel for Facebook via custom channel grouping.

Follow the steps below:

Step-1: Navigate to the ‘Admin’ section of your main reporting view in GA.

Step-2: Under the ‘View’ column, click on Channel Settings > Channel Grouping.

Step-3: Click on the ‘Marketing Channels’ link:

Step-4: Click on the ‘Define a new channel’ button:

Step-5: Name the new channel ‘Facebook’ and then define it like the one below:

Step-6: Click on the ‘Done’ button and then on the ‘Save’ button.

Step-7: Now navigate to Acquisition > All Traffic > Channels report and then select ‘Marketing Channels‘ as the primary dimension from the drop-down menu:

Note the total number of sessions from Facebook. It is 1,009 which matched our previous calculation of 1,009. This proves that the new marketing channel we created for reporting on Facebook traffic is consolidating all of the Facebook traffic data correctly.

Example #3: Traffic from Twitter

Google Analytics can report traffic from Twitter as follows:

So if you are taking only twitter.com traffic into account while trying to understand Twitter performance as a marketing channel, you will draw wrong conclusions, you will misinterpret the data.

Now people can also access Twitter via different apps like Hootsuite, TweetDeck, Twitterfeed, etc. So traffic from all of these traffic sources is basically Twitter traffic.

But Google Analytics is not going to automatically consolidate all of this data for you and report it to you as twitter traffic. This is something you would need to do it, yourself.

So the first step is to identify all the traffic sources (referrers) which are basically Twitter traffic. Then consolidate the data from different traffic sources into one custom Twitter channel.

You can define the new Twitter marketing channel as shown below:

Example #4: Traffic from Google Translate services

Here is how the traffic from Google Translate services can show up in Google Analytics:

Here you would need to consolidate the traffic data from different Google Translate services into one custom channel which is meant to report on Google Translate:

Example #5: Traffic from private networks

Here is how the traffic from private networks can show up in Google Analytics:

Whenever a person visits your website from a private network, GA reports a private IP address as referral traffic.

10.10.55.60 / referral => Here 10.10.55.60 is the private IP address.

Sometimes Google also reports the port number along with the IP address. For example:

10.10.55.60:15871 / referral => Here 10.10.55.60 is the private IP address and 15871 is a port number.

Whenever you see a number separated by a colon in an IP address, that number is a port number.

There are two types of IP addresses:

#1 Public IP addresses

#2 Private IP addresses

Public IP addresses are assigned to all of the computers on the internet.

Private IP addresses are assigned to computers on private networks (local area networks).

Private IP addresses are found in the following IP ranges:

From 10.0.0.0 to 10.255.255.255
From 172.16.0.0 to 172.31.255.255
From 192.168.0.0 to 192.168.255.255

So whenever you see IP addresses that fall in the aforementioned range, they are from a private network. You should exclude the IP addresses that belong to your company from your GA main reporting view via custom exclude filter.

However, for your unfiltered view, you should create a new custom channel which reports on traffic from private networks:

Here ^192.168|^10|^172 is a regular expression.

Example #6: Traffic from emails

Here is how the traffic from emails can show up in Google Analytics:

Here you would need to consolidate the traffic data from different email referrers into one custom channel which is meant to report only on the email traffic:

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Segment referral traffic

You must have noticed it by now, that Google’s predefined definitions of marketing channels are not accurate and 60 to 70% of marketing channels are labelled and reported as referral traffic, even when the visits are coming from social media, email, private networks, Google Image search, Affiliates, etc.

Referral traffic is polluted.

So you need to segment the referral traffic via custom channels in order to understand the true performance of your marketing channels.

Other articles on Google Analytics Channels which you will find useful

#1 Understanding Channels in Google Analytics

#2 Understanding Channel Grouping in Google Analytics

#3 Understanding MCF Channel Groupings in Google Analytics