DIGITAL ANALYTICS MINIDEGREE / CXL — BLOG 4
In the last blog I have talked about audit features of Google Analytics Universal. In GA, we talked about why the audit concept is so important and how it can be used. In this post, we will explore some advanced concepts within Google Analytics in detail with the fourth part of CXL Digital Analytics Minidegree.
You can go to the CXL website from here.
Data can tell many stories about your sales and performance. The premise of any good data analysis and storytelling is to prepare the data for analysis. One of the most important activities to be carried out as part of data preparation will be data cleaning.
Before we start with the items, let’s briefly talk about what data cleansing is and why it is important.
Data cleansing is a process in which you go through all of the data within a database and either remove or update information that is incomplete, incorrect, improperly formatted, duplicated, or irrelevant. Though data cleansing does and can involve deleting information, it is focused more on updating, correcting, and consolidating data to ensure your system is as effective as possible.
Some of the methods for clearing data for Google Analytics Universal are as follows.
1. Removing Internal Hits
Most of the time, Analytics is used to track how external customers and users interact with your website, since internal traffic patterns are typically different from external traffic patterns. When your reporting views contain hit data from both internal and external users of your website, it might become difficult to determine how your customers are actually interacting with your website.
To prevent internal traffic from affecting your data, you can use a filter to filter out traffic by IP address. You can find the public IP address you are currently using by searching “what is my ip address” on google.com.
In order to set up a filter to exclude your own IP address only, follow the process below:
a. Log in to the Google Analytics account and click on the “Admin” tab
b. Select the account and corresponding property
c. Click “Filters” and then click “New Filter” and Provide a name to your Filter
d. Set the drop-down to “Exclude” > “From the IP addresses that are equal to” > Enter your IP address.
2. Filtering Out Spam
Referral spam may show up to administrators as either a fake traffic referral, a search term, or a direct visit. The problem is that marketers have to manually decipher and filter this type of traffic out of their GA data to make proper sense of it.
Referral spam, also known as referrer spam or ghost spam, is created by spam bots that are made to visit websites and artificially trigger a page view.
To filter bot traffic from Google Analytics, you need to go in the Admin settings and then in View Settings which you will find under the View panel. Toward the bottom of the options, there is an option for Bot Filtering with a checkbox that reads — Exclude all hits from known bots and spiders. This is the setting that can be applied within Google Analytics in order to filter the bot traffic.
Besides from this Under Property > Tracking Info, we can use the “Referral Exclusion List” option as well which can be particularly helpful for filtering Ghost spam.
3. Cross Domain Tracking
Cross-domain tracking is a term we use to describe the act of tracking multiple domainsin a single Google Analytics property. The most important purpose of cross-domain tracking is to centralise the data from multiple domains which implies that cross-domain tracking is only required when you have more than one domain.
If you want to learn about domain and it’s parts below you can find.
https://www.example.com/blog/?utm_source=medium
https: = Protocol
www.example.com = Hostname
www = Subdomain
example.com = Root Domain
/blog/ = Path
utm_source=medium = Parameter and the Value
Cross-domain measurement makes it possible for Analytics to see sessions on two related sites (such as an ecommerce site and a separate shopping cart site) as a single session. This is sometimes called site linking. This can be more effectively done using Google Tag Manager which would provide more control and flexibility.
After data cleaning methods, I would like to talk about conversions, which is our last topic about GA for now.
Google Analytics — Conversion Opportunities
In Analytics, a conversion is the completion of an activity that is important to the success of your business, such as a completed sign up for your email newsletter (a Goal conversion) or a purchase (a Transaction, sometimes called an Ecommerce conversion).
Once you’ve set up Goals and/or Ecommerce tracking, you can use the Multi-Channel Funnels reports to see how all your channels worked together to create sales.
A completed activity, online or offline, that is important to the success of your business. Examples include a completed sign-up for your email newsletter (a Goal conversion) and a purchase (a transaction, sometimes called an Ecommerce conversion).
A conversion can be a macro conversion or a micro conversion. A macro conversion is typically a completed purchase transaction. In contrast, a micro conversion is a completed activity, such as an email signup, that indicates that the user is moving towards a macro conversion.
Source: the origin of your traffic, such as a search engine (for example, google) or a domain (example.com).
Medium: the general category of the source, for example, organic search (organic), cost-per-click paid search (cpc), web referral (referral).
Source/Medium is a dimension that combines the dimensions Source and Medium.
Conversion Opportunites:
With GA, you can look at many different areas and create goals according to your strategy. When we look at the conversion opportunities in general, paying attention to the following areas in GA will save you time and results.
1. How user aarrives at your site
2. Where user lands
3. Structure of landing page
4. Each step along the sales funnel
5. Identifying shopping cart problems
Next week, I will leave Google Analytics features and talk a little more about general topics related to data. Information about what A / B testing is and its details will be on the next blog.
See you next week with a new blog post containing details from the CXL digital analytics mini degree program.
Thanks,
Mert Kolay
