Let's Improve Your Google Analytics Data
Google Analytics(GA) should be the lifeblood of your business. So, if you haven't gone through and correctly configured your Google Analytics(GA) account1...Do not trust the data in there for anything. This will lead you down a path of making crucial business decisions based on minimal data that is likely false, misleading, or both.
It's more than a tracking code
Installing the tracking code on your site is important, but you can't stop there and be correctly configured. This critical misstep will cripple your online marketing unless you make some essential adjustments.
Let's Start with SPAM
Just like with email marketing —there is a lot of money to be made in analytics, so with that, spammers and hackers are close by trying to take advantage.
Spammers are often looking for ways that they can infiltrate GA data. Typically, they try to come up as a referral source in your Google Analytics data. Just remember they are relentless, and they’re developing new techniques every single day.
But, wait, why would they care to show up in my Google Analytics data in the first place?
Webmasters, marketers and business owners look at their Google Analytics accounts frequently. Inside of their account, there is a place that lays out the sources and links to their pages. With some strategic referrer spam, their properties can get a significant boost of traffic and increased sales leads.
While spam is the primary destroyer of good data, your website traffic may be skewed for another reason. If you’re looking at traffic reports and think all the sessions are potential customers, you’re dead wrong.
You might be skewing it too.
Your own office may be inflating traffic numbers without realizing it. While this is not necessarily fake traffic, it’s definitely not valuable for you either.
Other sources of bad data can include bots, spiders, and crawlers. Call tracking and chat software often impact the quality of your GA data. All these sources should be wiped out before you can begin to even remotely trust Google Analytics.
How To Fix Your Google Analytics Data
Let's get rid of all that bad data, so you can use Google Analytics without stress. Before, I start any project, these are the first things I look at, and correct.
Step 1 – Create Multiple Views
It is very important to create multiple property views2 because once you start messing with Google Analytics data, there is a high probability that you will modify items irreversibly.
Now, this doesn't mean the data is corrupted or unusable, but inside of the properties, you have the option to configure data based on how you want to retrieve the data. Thankfully, they have views, so you can modify your main data into certain categories based on your marketing goals.
I suggest creating a minimum of 3 views
- Raw Data (the untouched stuff),
- Master Data (the stuff you use day to day), and
- Test Data (the one you... test with).
Please note: 3 views is a minimum — Depending on your industry, you could have a lot more. For example, if you sell items, you might have a view specifically for eCommerce or maybe you write content and have a View just for your articles.
A few other custom ones to use on your site:
- Access-Based View(s) are perfect when you only want to share a limited view of your company's Google Analytics Data.
- Source-Based View(s) includes data from specific traffic sources. This is useful if you’re spending a lot of money, time and effort on a source for traffic. (Facebook, Instagram, Youtube, etc)
- Location-Based View(s) let you focus in on a single location. This is perfect for companies that are expanding into different regions and/or markets. 3
Step 2 – Create Filters
After you've created your view(s), Filters are next.
Filters are used to block data from ever hitting your Google Analytics account. For example, the best filter to setup first is one that will Block Internal IP addresses. Your team, developers, and vendors can all visit your site(s) without contaminating your Google Analytics account.
It is important to understand that Filters apply only to future data and cannot be retroactively applied.
Here are some examples of other Filters you should create:
- Exclude spam referral sources,
- Exclude internal IP addresses
- Exclude partner agencies’ IP addresses
- Include only your Hostnames
Again, once these are applied, the filtered data is gone forever. Make sure to test each filter to make sure it works correctly. (This is perfect for your "Test View", I spoke about above.)
Step 3 – Select “Bot Filtering”
This one’s easy. Google Analytics has an option under View Settings that is called Bot Filtering. It “excludes all hits from known bots and spiders.” Not sure why this isn't clicked by default, but it's a simple one to do and forget, so check the box.
Step 4 – Utilize Segments
While Filters keep your data clean from today going forward, there is still a way to do the same to your spam-filled data from the past as well.
Create a Segment that matches your filters, so it excludes that same "bad" data. You’ll need to use these segments every time you look at your data, but it will give you the same accuracy for your historic data.
Why doesn't Google do this by default?
Google has designed an awesome out-of-the-box product that is customizable for most businesses.
However, There are simply too many industries to please. Instead of creating GA suites for each type of business— They just pack GA4 full of features and leave it up to business owners, marketers, or consultants to custom tailor it.
Does This Fix Everything?
I wish this was the end of it, but Google Analytics is just not a "set it and forget it" software. However, spam sources are always evolving and you’ll need to update your filters and segments regularly.
So, stay on top of your data. Make sure to proactively monitor your Google Analytics data so you can make informed marketing decisions.
Google Analytics is the analytics platform that was developed and continues to be developed by Google. Also referred as "GA"
In Google Analytics, a property is a website, mobile application, or blog, etc., that is associated with a unique tracking ID. A Google Analytics account can contain one or more properties.
Source: About properties
These example Views were paraphrased from an article on Lars Lofgren's blog when Views were still called Profiles.