Google Analytics 4 has introduced a benchmarking feature, enabling businesses to compare their performance against industry peers. While this functionality was previously available in the now defunct Universal Analytics, GA4 offers enhanced standardization through the use of reserved and recommended events, providing more accurate and reliable comparisons.
The process for enabling benchmarking in Google Analytics 4 is straightforward: just check the box labeled “Contribute to modeling” option in account settings to authorize Google to use your property’s data to feed the benchmarking model. In return, you gain a comprehensive overview of your position relative to competitors in terms of volume, conversions, and key behaviors.
It’s important to note that the quality of benchmarking results heavily depends on the participation of businesses & brands. The more data and the more consistent it is, the more meaningful the comparisons. Therefore, it’s crucial for businesses to accurately declare their industry, size, and correctly configure their conversion events.
The advantages of this new approach are manifold:
Standardized measurements: Reserved and recommended events allow for comparison of similar metrics across different businesses, reducing bias caused by varying definitions.
Focus on key events: By concentrating on industry-specific events (form submissions, purchases, bookings, games played, etc.), benchmarking provides more relevant insights for decision-makers.
Competitive positioning: The ability to position oneself relative to the industry average allows for the identification of improvement opportunities and the setting of more ambitious goals.
However, certain limitations should be kept in mind:
Dependence on declared data: The quality of results depends on the accuracy of information provided by businesses.
Comparative nature: Benchmarking allows for performance comparisons but does not provide explanations for the reasons behind differences.
Lack of in-depth competitive analysis: It’s not a tool for competitive intelligence but rather a means of obtaining a broader market overview.
In conclusion
GA4 benchmarking is a valuable tool for businesses seeking to assess their market position and identify areas for improvement. Nonetheless, it should be used judiciously and complemented by other analyses to make informed decisions.
What if Google Analytics v4 (App+Web) was the best thing to happen to Google Analytics in the last 15 years? Will it finally give all the insights? Can I get free access to GA360? Will it cure cancer? Will it revive Steve Jobs?
All I know is that my data is going to be a lot tastier and scalable very soon – provided I add my credit card.
In this post, I will show you how to streamline your eCommerce tracking implementation and upload product data to Google Analytics. From a remote CSV file. Over Google Sheets. Automatically.
Hi folks, I just got back from the first ever edition of MeasureCamp Faro, in Portugal. As you may know, I’m a regular on the MeasureCamp unconference circuit.
What is an unconference you ask? It’s essentially a knowledge exchange environment with no pre-arranged schedule. Participants show up and can decide to present on analytics-related topics.
In short, MeasureCamp does away with the format and conventions of usual conferences and allows you to acquire more hands-on experience than anywhere else 😎
Of course, I’m partial to Portugal, having learned Portuguese during my language studies so it was a great occasion to practice!
We had a smaller than usual audience compared to other editions but participants were super motivated 🤩 Among the participants were quite a few contacts I’ve made in the industry over the years and it all feels very much like a family gathering.
I took the opportunity to run two presentations, updated for 2019 from their original versions; one on best practices on how to get a digital analytics project off the ground quickly; one on Tag Management and its limitations.
The networking portion of MeasureCamp Faro was of course tremendously enhanced by the “vacation” setting in Algarve, the southernmost region of Portugal, also known as Portuguese Riviera (links below).
See you next year?
The answer is a resounding YES as far as I’m concerned! 🙂
Thanks again to the organizers, to the sponsors and to the University of Algarve!
So you use Mailchimp and designed the ideal e-mail campaign? You felt great about the copy and the visuals and pressed SEND. Great! After your e-mail is sent, Mailchimp provides you with reports and who received the email, who opened it and who clicked it. It also has a section about those pesky unsubscribers. But now you’re thinking:
“That’s great but what if I could track the performance of my e-mail campaigns based on what my subscribers do once they reach my site?”
– every e-mail marketer ever
In this post, I will show you how to integrate Google Analytics tracking with Mailchimp and how to track e-mail performance, with the help of Google Tag Manager.
If you own multiple websites, you’ve often wondered how to consolidate traffic data from all your Web properties (or apps) into a single view – besides Excel, that is!
Here is a quick guide on how to get this setup on all your sites, whether you use a tag management system or in-page tagging.
The year is 2019 and Google Analytics has been around for 13 years, give or take. Longer if you including its ancestor, Urchin. One would think that after all this time, digital marketers would know how to use Google Analytics campaign parameters to accurately track marketing initiatives.
The reality is far from ideal and nearly every client I audit has campaign tracking issues. Is it due to the agency handling campaigns? Is it a technical issue? A configuration issue? Politics? Actual bugs?
What I can tell you is that using Google Analytics campaign parameters is not rocket science and in this post I’ll show you techniques to efficiently measure your campaigns.
Reviewing the basics: UTM parameters
The basic mechanism by which Google Analytics campaign tracking works is by using specific parameters (key/value pairs) in the URL of your campaign’s landing page. These are called UTM parameters and are named UTM after Google Analytics’ ancestor, Urchin; UTM stands for Urchin Tracking Module.
In order to properly track campaigns, you need to use three (3) or more Google Analytics campaign parameters in each URLs. Let’s review the parameters available to you:
Parameter
Required
Usage
Example
utm_source
yes
Which site/company sent traffic
utm_source=facebook
utm_medium
recommended
Which marketing method was used to access the site
utm_medium=email
utm_campaign
recommended
Which marketing initiative was promoted
utm_campaign=2019%20Customer%20loyalty
utm_content
optional
Which visual element was clicked
utm_content=newsletter_hero
utm_term
optional
Which keyword was used for paid search
utm_term=running%20shoes
In the example column in the table above, you will notice encoded characters, for instance, %20 instead of spaces. If you are going to use special characters, make sure you encode these values first. When in doubt, use an encoder first.
As mentioned in the table above, you only need one parameter (in theory) but that is far from enough to run decent marketing campaign tracking. My recommendation (and Google’s) is to use at least three parameters:
utm_source
utm_medium
utm_campaign
This means a URL using Google Analytics campaign parameters could look something like this:
Now arguably the values you insert into utm_source, utm_medium, utm_campaign et al are fair game. As long as you stay away from reserved values as set by Google. Because Google Analytics uses source and medium to pre-build Channel Groupings, you want to stay away from certain keys in utm_medium, such as:
cpc
cpm
direct
display
email
organic
referral
There are more but stay away from the ones above.
Not sure how to handle these URLs? You have 3 solutions:
Got the hang of writing URLs with Google Analytics campaign parameters? Good, let’s move on to seeing how why they can be a bad idea.
“Those UTMs don’t look so good in my URLs”
I have seen my fair share of clients claiming that newsletter recipients don’t click links “with lots of dodgy characters in them”. A fair point. So what can we do about it? We can minimize the amount of Google Analytics campaign parameters in the URL by using one of two methods:
Using a URL shortener
Using the Campaign ID
Let’s explore both methods.
Using a URL shortener
URL shorteners are great because they generate (surprise) a short link after you feed them long, confusing, scary URLs.
When picking a URL shortener, make sure they are going to retain your link long enough for your links to be tracked because they tend to expire.
Using the Campaign ID
The campaign ID is a little-known gem in Google Analytics inherited from the Urchin days, back when you could use lookup table and file imports. It is brilliant in theory and very actionable in practice.
Using the campaign ID relies on the Data Import feature linked to your Google Analytics property. Go to your admin panel in GA and locate Data Import at the bottom of the Property settings column:
Then you will see a list of your data imports for the property. You can have up to 5 imports per property on a free Google Analytics account, more with Google Marketing Platform (360); In my case I already have a few imports set up so you can see my Campaigns and redirects import.
Create a new import and select Campaign data as import type. Once you’ve done that, name the export and the select the views in which data will be affected by the import. Hit save and in the next step select the campaign dimensions you will be replacing based on the ID column. I selected Source, Medium and Campaign.
Next, you need to manage the data structure by getting a schema (template for the CSV you will be generating.
Below is a sample of my import:
ga:campaignCode
ga:source
ga:medium
ga:campaign
twowned
twitter
social
Owned
gpowned
google
social
Owned
fbowned
facebook
social
Owned
tcen
google
social
Top Contributor EN
tcfr
google
social
Top Contributor FR
isowned
instagram
social
Owned
Whenever i use a URL with utm_id=tcen in links in posts on the Advertiser Community, as soon as the Google Analytics hit for that URL is processed, Google will populate the values “google”, social” and “Top Contributor EN” in source, medium and campaign respectively. Note that I don’t need to encode 😉
OK so let’s say you hit a wall with someone who doesn’t want to use utm_ variables “because Google can be hacked” or something. Actually this is somethgin that can happen when you migrate from another analytics stack over to Google Analytics and you have to capture old campaign tracking parameters. Actually, what I described with Campaign ID has been a native feature of Adobe Analytics, Webtrends and others.
Anyway, assuming you want to use sid instead of source, mid for medium id and cid for campaign id, you can change your Google Analytics tracking code to look for alternative parameters.
In Google Tag Manager, this is easily achieved by frist creating a variable to capture URL query element sid then assinging that variable to “Fields to set” in a page view tag or – better – in a Google Analytics Settings variables.
Now what?
Once you have your campaign URL, paste it in your links and wait for people to click.
The good news is now you should be getting cleaner campaign data!
If agencies and marketing teams cannot manage tracking URLs in 2019, there is something very sad about the state of training in our marketing schools and internships.
If there is an unsung hero in Google Analytics, it is definitely something called content groups (or content grouping). Never heard of it? It is hiding in plain sight, in your Google Analytics view settings, and can be set up in a couple of clicks. Once content groupings are set up, you will always want to use them 🙂
Ready? Get some coffee, snacks, and let’s go build some content groups.
