After completing numerous UA to GA4 migrations, one issue that appears in almost all instances relates to categorizing existing marketing links into Google’s newly defined channels.

Old online marketing links with UTM parameters are no longer being categorized the same way. But why? 

In this article, we’ll discuss the common reasons for miscategorization in GA4 and tips to make sure your marketing campaign links are properly tagged and tracked.

Miscategorized links in GA4: Common reasons

While there are several reasons for miscategorization, sometimes it is caused by using a “custom channel” that GA4 no longer supports. Other times, it is due to invalid values entered into the marketing link’s source or medium UTM parameters.

While GA4 hasn’t changed or added new UTM parameters, they have become stricter about the values they accept. Failure to meet these specific settings will cause traffic generated from your marketing efforts to be categorized as “Unassigned.”

Formatting campaign URLs: What marketers need to know

To understand the problem and the solution, let’s review the proper format (as per Google’s requirements) for a marketing/campaign link.

The URL format must be (in all lowercase): 

https://www.ourcompanysite.com/?utm_source=source&utm_medium=medium&utm_campaign=campaing_name&utm_id=optional_campaign_id&utm_term=optioanl_term&utm_content=optional_content

In the above example, optional parameters are indicated.

When the values of the required utm_source or utm_medium parameters do not match specific values, the traffic is recorded in the “Unassigned” channel.  

To view the values assigned to that traffic within GA4 simply add the second dimension “source / medium” to your channel report.

Dealing with ‘unassigned’ traffic

In the report below, someone on the marketing team defined the medium as a “post,” which is not one of Google’s defined values for utm_medium and hence the traffic is categorized as “Unassigned.”

Below are examples of where someone on the marketing team just wanted to define the source but not the medium for various marketing efforts or incorrectly assigned an invalid medium.

You may notice that Google discourages using spaces in the parameter values and even hyphens (“-“) as an alternative. Instead, an underscore “_” is the preferred replacement. 

While failing to follow these new recommendations won’t impact GA4 reports today, with the constant changes taking place, it may in the future. 

The new format will become more critical when your organization starts using Google’s BigQuery data warehouse to store your analytics data beyond the 14-month maximum online availability — an inevitable undertaking.

Defining source and medium parameters

The two parameters that GA4 focuses on to categorize traffic correctly are:

• utm_source: The traffic referrer (i.e., google, newsletter4, billboard).
• utm_medium: The marketing medium (i.e., cpc, banner, email).

So, if you set the utm_source to equal “My Email List” and the utm_medium to equal “EMail,” GA4 may categorize it as “Unassigned” instead of “EMail.”

If you’re scratching your head about this, here’s the reason. 

According to GA4 documentation, the following criteria must be met for the traffic to be considered from the email channel:

• Source (utm_source) = email|e-mail|e_mail|e mail
• Medium (utm_medium) = email|e-mail|e_mail|e mail

For those not familiar with regular expressions (or regex), let’s break this down.

• Note there are no capitalizations allowed.
• Either the utm_source or utm_medium must contain one of the values provided where the “|” indicates “or.”

In the example provided, while the utm_medium contains “EMail,” having both an uppercase “E” and “M” means it does not equal “email” as per the GA4 specification. (While Google may convert all parameters to lowercase, you can not rely on them to fix your errors 100% of the time.) 

Having the name of an email list as the value for the utm_source parameter is still permissible, provided that the utm_medium equals “email.” (This is not ideal, though. The email list name is better assigned to one of the optional parameters or, at a minimum, made all lowercase with the spaces removed.)

Also, while in the example of acceptable values from Google, it is permissible to use “e mail” (with a space), it is not recommended and should be avoided.

Similar specifications are available for all 19 GA4 channels. A complete list of each channel and the acceptable values can be found here.

Pay attention to paid channels

While we don’t have to worry about the non-advertising channels (i.e., organic search, organic social, direct, referral, etc.), we need to concentrate on all the other ones. 

Paid channels require special attention. The new ones include: 

• Paid Social.
• Paid Shopping.
• Cross-network. 

All paid channels with “Traffic is Google Ads” in the requirements imply that the utm_medium value is either set to “cpc”, “ppc” or “paid.” 

The value of the utm_source must match the site value that Google has determined as a search/social/video site vs. something else based on Google’s defined list. 

(Here is an Excel spreadsheet you can download with the complete list of the utm_source values Google uses and how they are categorized.)

For example, if your URL has utm_source=blogger and utm_medium=cpc, it will appear as “Paid Social” in GA4. 

If any other value is used for utm_medium beyond “cpc”, “ppc” or “paid” it will appear as simply “Organic Social.”

The spreadsheet from Google is constantly being updated, so be sure to download the latest before assuming how any new advertising partner will be categorized.

What happens to ‘unassigned’ campaign data?

While we need to be proactive in aligning all our marketing links to the new Google Analytics requirements, what can be done with the data that has already been captured and reported as “Unassigned” or perhaps it was a custom channel you defined for Universal Analytics?

This can be addressed when data is extracted from GA4 or BigQuery via Google’s Looker Studio (formerly Data Studio) or any other business intelligence tool. 

Within these, you can define your own logic where utm_source and utm_medium equal the values you defined in your UA custom channel and assign it to its own channel. (Hence, a custom channel.) 

Dig deeper: MarTech’s in-depth GA4 coverage

Adapting to GA4’s campaign tracking standards

Universal Analytics and Google Analytics 4 differ in many ways. There are technical reasons behind these differences, all with good intent.

Different isn’t always a good thing for marketers who are used to the traditional approach of tracking marketing campaigns. But one thing we can easily address is how our online marketing efforts are tagged to ensure they get classified into our preferred channels. 

Addressing this before your migration from UA to GA4 will help lessen the headache of the transition and the efforts required to fix them after you have made the inevitable move.

The post Campaign tracking in GA4: How to ensure your links are properly tagged appeared first on MarTech.

Google Analytics now has the ability to combine observed data and unobserved data. Not only is this a benefit, but it’s a necessity as changes in browser cookies and user identifiers increasingly limit the old way of tracking. 

Our tracking and analytics tools are losing data as we know it — and we must adapt. Using some easy features in GA will help compensate for this loss so that you can remain data-informed.

Dig deeper: 3 ‘secret’ marketing tools in Google Analytics 4

Unobserved data: How it works and why it matters 

No matter which analytics tool you use, leveraging unobserved data is a great tool to keep up with the evolving environment of digital marketing analysis. The difference between unobserved and observed data is the difference between collected data and modeled data. 

Tracking users with cookies used to be more reliable since almost all browsers accepted cookies. The way it functions with analytics is by automatically stamping a user with a cookie when they land on a website. This cookie allows platforms like GA to identify users by device information, location, demographics and, most importantly, a random ID that’s “sticky.” 

When that user returns to the website, the ID is recognized by GA as a returning user, which stitches that user’s past information with new activity. For mobile apps, the behavior is similar. Instead of a cookie, devices have a unique advertising ID as an identifier (Android and iOS have different versions.)

However, things have been changing gradually over the past several years and will continue to change. There’s a huge problem with this old behavior: it gave users little to no control over their personal information being shared. Privacy wasn’t a consideration, and organizations had 100% control over their audience’s information. 

No personally identifiable information (PII) was ever tracked with Google Analytics by default as collecting such data to GA is against the terms of service, but the definition of PII has changed depending on how policies are written and interpreted by different laws and security teams. 

Now, users can block and opt out of analytics tools from collecting data. Automatic opt-out is the default for GDPR and other countries’ laws are certain to adopt this. It’s the “cookieless future.” 

Long story short — we won’t get the volume or detail of user data we used to, so it’s time to fill that gap. In Google Analytics 4, there are several out-of-the-box features to make up for lost data. They require little to no lift once tracking has been set up, so you can test and take advantage of them today. Three examples are:

• Data-driven attribution
• Predictive metrics
• Behavior modeling

Dig deeper: What do marketing attribution and predictive analytics tools do?

1. Data-driven attribution

In GA4, data-driven attribution (DDA) may be somewhat hard to find if you’re not familiar with the interface. It’s located in the Advertising screen instead of the Reports area. The Advertising reports are interesting and split out because they provide a different view of your data. 

In Universal Analytics (sometimes referred to as GA3), the closest equivalent is the Multi-Channel Funnel reports. It’s a good descriptor because these reports expand the analysis of conversions into multiple touchpoints and a fuller user journey. Previously, data-driven attribution was only available to paid 360 accounts but now it’s available to all.

The DDA attribution model uses a statistical model to show how significant a channel was in assisting a conversion. For example, there may be 5,000 purchases attributed to the Organic Search channel in the main GA4 acquisition reporting but the previous touchpoints from the Paid Search channel may be significantly influential to the user who ultimately purchases. 

The statistical model will take the data about users’ behavior and paths leading up to the conversion and determine how much credit the different touchpoints should receive. Instead of 100% credit going to organic in the previous example, credit would be divided by percentages across all channels users came from before making a transaction.

The visualization of DDA is located in the Advertising > Conversion Paths report (pictured above.)

2. Predictive metrics

We have data about what users saw and engaged with, but what will they do next? This is the ultimate example of unobserved data because it involves “future” behavior. As a note, this feature currently relates only to ecommerce and churning data.

Ecommerce tracking will need to be set up before predictive metrics and predictive audiences can be used. If you have ecommerce tracking, the top areas to see and use predictive modeling are in the Explore reports and the Audience tool.

In the Explore reports, predictive metrics are best used in the User Lifetime technique. In this report type, you can choose metrics to import based on purchase probability, churn probability and predicted revenue. There’s a section dedicated to those metrics on the selection screen.

The predictive data in GA4 (both here and in the Audience tool) is based on past user activity. With the data points of users who have made a purchase compared to those who haven’t, the model will learn trends that develop the probabilities and percentiles. For churn, the model looks at users who are active and users who become inactive to determine who won’t come back to your site or app in the next week.

The insights can be used outside of Google Analytics as well. Audiences and segments can be created to isolate likely/unlikely purchasers and used in Google Ads for remarketing. To build a predictive audience in a few clicks, you can go to Admin > Audiences > New Audience > Predictive. This will give you pre-made templated audiences to use and customize how you’d like (pictured below.)

3. Behavior modeling

Behavior modeling is the most impactful machine-learning feature out of these three because it affects user tracking right from the source — the identifier. It involves integrating GA4 with your cookie consent management tool so that Google Analytics can collect data on users who don’t consent to be tracked.

This sounds counter-intuitive, but the data is anonymized and not related to a cookie or any user identifier. Instead, the anonymous event-only data is used to determine user-level activity. It’s powerful because it’s based on your site or app’s data. The behavior of observed users (users who opt-in to tracking) trains a machine-learning model to estimate the behavior of users who opt out of tracking.

If you’re interested in taking advantage of behavior modeling, Google’s documentation on consent mode can help start conversations and action around using this user tracking method. The option to enable behavior modeling in your GA4 account is in Admin > Reporting Identity > Blended. 

Making the most out of GA4’s machine-learning features

With the tools above, questions about your users and data can transform from “How many views did page X receive?” to “Which users are most likely to make a large purchase within the next 7 days?” This sophistication is much more actionable. 

Combining GA4’s machine-learning methods with remarketing and audience-sharing can launch your analytics from solely analysis to immediate use cases and even audience engagement and RoAS impact. 

Dig deeper into GA4 with these stories.

The post 3 Google Analytics 4 features to make up for lost data appeared first on MarTech.

The “Admin” screen is usually frequented by analytics practitioners and those implementing data collection, but there are marketing benefits to getting familiar with the features available. 

Exploring Admin capabilities involves the consideration of property settings for account governance, attribution, reporting enhancement and overall user tracking.

Below are three things to know and keep in mind about Google Analytics 4 account governance.

What are properties in GA4?

In Google Analytics, a property is where the reporting on web or app data collection is located. Right now, there are two different types of properties — Google Analytics 4 and the previous version of GA, Universal Analytics (sometimes referred to as “GA3”). The latter version will sunset and stop accepting data by July 2023, so all marketers should be migrated to GA4 or in the midst of migration. 

As a tip, you can determine if it’s the old version by looking at the property ID. The ID is visible under the property name in the main dropdown or in parentheses in the Admin > Property column.

Does the number follow the letters “UA” and look something like this: UA-12345-1? If yes, that means that it is not a GA4 property.

Universal Analytics property IDs are tracking IDs. So, that ID would go on the website or in a tag manager to collect the data.

It’s important to know that the data source should be reviewed or added if you see any missing data or broken tracking. The number to request for GA4 is “measurement ID.”

Properties aren’t just about base measurement and they do much more than house the data and reports in GA4. Property settings and governance can affect remarketing capabilities, data integrity and even interpreting conversions. 

Dig deeper: Getting started with Google Analytics 4 (Tools and resources)

How account structure relates to measurement strategy

Account structure is the foundation of a reliable and actionable analytics implementation. Decisions around where data should flow into which properties affect the analysis of the user journey. This is why it’s important to have an understanding of how properties work with each other. 

When dealing with only one website or app, it’s typically straightforward and only involves creating a single data stream for a single property. For multiple websites and apps, websites with multiple domains and Google Analytics 360 customers, there are more great features to keep in your back pocket.

If a website has different domains (such as www.exampleA.com and www.exampleB.com), it’s essential for marketers to make note of where the data is and why. This is a step where things can go wrong, resulting in a drop in data integrity.

There are three questions to solve with the knowledge of how users are expected to move between sites along with how team members are going to get the most out of GA4. 

1. Will users navigate back and forth between the domains as part of the web experience?

If not, no action is necessary for this part and data can (and should) be in separate properties.

If yes, the domains must be in the same property. If you find yourself navigating to two different properties for reports, what’s called cross-domain tracking needs to be enabled. With GA4, it can be a low level of effort. 

Next steps to do or request: 

• Make sure all data goes to one property with one measurement ID. 
• Check Admin > Property > Data Streams.

• Then, navigate to the data stream mentioned earlier in the article and simply add your domains. The screen should look like this:

Note: This includes PayPal since the user flow will likely come back to your site after payment in most cases.

2. Would it be better and more efficient to incorporate a feature that allows for more granular data available in the account structure? 

(For those who are familiar with Universal Analytics, this could be thought of as a replacement for Views. ***360 paid customers only. Your Google Partner vendor can provide guidance or assistance, if needed.)

Almost all organizations can answer “yes” to this question. Having subsets of data might be useful for:

• Making a different interface for a section of the site and content.
• Splitting by teams so they have their own custom interface.
• Separating conversion settings and Ads Links.

The next step only involves Google Analytics and not technical or implementation work. Subproperty creation is in the same area where regular source properties are (Admin).

3. Is there an opportunity to aggregate data from multiple GA4 properties into a holistic rollup property?

On the other hand, there may be opportunities to take more than one regular property and do the opposite subproperties by rolling them up to a holistic rollup property. 

This enablement just involves creating the rollup property type and selecting which existing properties you’d like to include in the same admin area as the subproperties.

(***360 paid customers only. Your Google Partner vendor can provide guidance or assistance, if needed.)

Property settings can enable more data and activation

Other Admin capabilities are also in the properties area. For media metrics and audiences, integrations are essential. Linking Google Ads to Google Analytics 4 should be one of the first steps in migration or a refreshed measurement strategy. In the same Admin area mentioned above, the integrations are located at the bottom of the property column.

To link, no tracking changes are needed and it is self-serve. The prerequisites are having the Edit role in GA4 and the role of Administrator in Google Ads.

The Ads account will show up on the integration screen and everything is good to go. Audiences created in Google Analytics will be available in Ads automatically.

You will also have to check to make sure that the toggles are enabled for Google Signals and Ads Personalization on the same Admin screen where the other former steps are located (Admin > Data Settings).

If they are off, you may want to double-check with whoever is the administrator of GA (if it’s not you) to make sure that it is okay to use these settings in alignment with your privacy policies.

Make meaningful improvements to your analytics

There will be edge cases to any implementation, but the above topics and questions should kickstart more collaboration between marketers and analytics for meaningful improvements. 

Having data in the right place, in addition to tracking correctly with enablement for media, will open up opportunities for valuable audience creation.

It might seem like many steps. But just a few settings, toggles and reviews of the properties can have a payoff for decision-making and analytics involvement for marketers in Google Analytics 4.

Getting started with Google Analytics 4

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The post 3 “secret” marketing tools in Google Analytics 4 appeared first on MarTech.

MarTech: What is the most important thing to know about migrating from UA to GA4?

Russ Ketchum: GA4 is truly different from Universal Analytics at its core — and that’s intentional. Before Google Analytics, page views and sessions were unfamiliar concepts. And, even so, they worked great for website analytics. But the world has evolved. “The internet” isn’t a synonym for a desktop website. The internet is all around us and that’s the world that we’ve built GA4 to measure. Streams, events, partial data, behavioral modeling, and so on are the “page views and sessions” of today’s connected world.

We know that this is a big leap for many of our customers. With migration tools, educational content, videos, and more, we are working to be as helpful as possible for our customers during this transition. 

Dig deeper: Using Google Analytics 4 integrations for insights and media activations

MT: Power user moves for GA4?

RK: It’s a great question. I’ll highlight two; one that helps customers migrate a little easier and another which highlights a big improvement we made to GA4 based on customer feedback about Universal Analytics. 

When a customer is migrating to GA4, one of the first things they need to consider is how to get the data they care about the most into the system. In Universal Analytics, the ability to measure events is somewhat limited with just a Category, Action, and Label to indicate a particular interaction. In GA4, customers can create as many events as they want and use parameters to be very descriptive. 

We get a lot of questions about what’s the easiest way to go from the old world to the new. In our experience, “easiest” usually means “without writing new code for your site.” In GA4, there’s an easy way to do this thanks to Google tag. If you look under your tag settings for a given stream, you’ll find an option “Collect Universal Analytics events” in GA4. This will create a single GA4 event type that records Category/Action/Label as parameters. You can confirm this is working by looking at the Events section under Configure. 

Now, the Pro move is to click the “Create Event” button. This lets you write rules to break-out the legacy event into as many native GA4 events as you want. For example, you can make “Category” the GA4 event name and “Action” and “Label” some of the parameters. Now businesses can analyze what their users are doing with all the power of GA4.

Now that you have the data they care about in GA4, here’s another pro tip to help focus on what matters to them the most: customize reports.

Report customization is something entirely new and different in GA4 and a feature that has long been requested in Universal Analytics. All of the default reports can be customized and customers can even replace the entire standard set of reports with something completely custom to meet the specific needs of their business. 

MT: What topics are you seeing the most questions about?

RK: Honestly, it’s a pretty wide range at this point. As you might expect, we have customers who are in the setup process so they’re asking lots of questions about the best way to structure their properties, their events, etc.. This is why we’ve made such a big investment in our Setup Assistant to make it as easy as possible to move from UA to Google Analytics 4. 

We also have customers who were experts in Universal Analytics and are now learning how to apply that expertise to GA4. We’ve already launched a lot of educational content aimed exactly towards this audience, but in 2023, we’re excited to add even more. 

MT: Will GA4 do anything to comply with EU privacy laws? 

RK: One of the reasons that Google Analytics is so unique is because our customers own their data — not Google. Because of this, we have an obligation to provide our customers with the controls and tools they need to comply with regulations wherever they operate, not just in the EU. Over the course of the past few months, we’ve introduced more granular privacy controls and we’ll continue to evolve as necessary.

Dig deeper: 3 ways to do segmentation in Google Analytics 4

While these concerns are something we’re actively addressing in GA4, we don’t have the same flexibility with Universal Analytics. That makes it more important than ever that customers move to GA4 as quickly as possible. 

MT: Will the sunset date for Universal Analytics get changed from July of next year? 

RK: We appreciate the fact that the migration to GA4 is a heavylift for many of our customers. That’s why we recently made two announcements to make things a little easier. First, we announced an update to our Setup Assistant which will effectively “Jumpstart” our customers on the path to GA4 by creating a GA4 property and carrying over the settings from their Universal Analytics properties automatically.

Additionally, due to the scale and complexity of many of our Analytics 360 accounts, we announced that we will be extending their sunset date to July 1, 2024.  Our goal with both updates is to help customers be best positioned for the migration to GA4, with as much historical data and customization possible.

MT: What areas can we expect new features and/or updates in?

RK: Customers can expect even more out of the customization features I mentioned earlier, especially for SMB customers. We have some pretty big plans for the Advertiser Workspace, so what you see there now really only scratches the surface. 

Getting started with Google Analytics 4

Catch up on the entire series:

The post Q&A with the director of Google Analytics: Getting started with Google Analytics 4 appeared first on MarTech.

Channel groups are rule-based definitions of your website’s traffic sources that let you monitor the performance of all of the channels sending traffic to your website.

“Default channel grouping is one of those reports that everybody loves and kind of becomes that first individualized report to use.” says Harris. “Because it wouldn’t be Google without making new things available in these metrics, there are now going to be both user related reports and traffic related reports.”

This is an important distinction and one you have to keep in mind. This is really and truly about using the same type of metric throughout your entire report analysis work that you’re doing.

Dig deeper: Google rolls out new features for GA4

Before we get further into how they’re used in GA4, there is one other thing to know.

New terms to keep in mind

There are several new terms you should familiarize yourself with because you’re going to see them on all tables by default. 

• Users: users who visited the website. A user can visit the website multiple times. Users are defined by the device ID.
• New User: people who visited the website first the first time. User is defined by the Google Analytics browser cookie, so someone who deletes their cookies would show up as a new user.
• Engaged Session: when a session either lasts longer than 10 seconds, includes at least one conversion or includes more than 2 page views.
• Engagement Rate: calculated by dividing the number of engaged sessions by the number of total sessions.
• Engaged Session per User: total number of sessions per user averaged by the total user count.

Engage session, engagement rate and engage session per user are the new metrics meant to replace Universal Analytics’ (UA) bounce rate. This is a big improvement. No more telling you how quickly people leave your site. Instead you get to find out about the ones who stuck around. 

“To me it doesn’t matter if 20,000 people visited the site,” says Harris. “I care about the 2000 engaged sessions and that my paid search had an engagement rate of 60% compared to non-paid search engagement rate of 20%.”

Default channel grouping

This picture shows what your default channel grouping looks like. It starts with user medium and doesn’t have the default channel grouping report anymore. Under “first medium” there’s a drop box where you can change that to session, medium, session, source, campaign, all of those things. 

• Pro tip: “Anytime you see one of these carrots right here,” says Harris, “that’s going to mean that there are multiple parts of this report that live in one screen.” 

In UA, source/medium is in one screen, content group is in another and campaign in yet another. In GA4 they’ve combined them all into one screen. This turns a flat report into one where you can see interactions and activity in real time. The same thing happens with browser and technology.

“What used to live in five or six reports now can all live within the same report,” says Harris. “I think it’s very helpful and a more streamlined process.” 

This is also where you’re going to be able to add in a secondary dimension as shown in this picture.

Remember, reports in GA4 use two different attribution models for data.

• User Traffic Source —  gives credit to the first source of traffic that first caused the user to visit your website.
• Session Traffic Source -– gives credit to the last source of traffic that first caused the user to visit your website.

Be sure you’re using the same sources when compiling your reports, otherwise you’ll wind up comparing oranges to antelopes.

Getting started with Google Analytics 4

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Key articles by Google support

• Release Notes for GA4 
• Make the switch to GA4
• Introduction to Google Analytics 4

Universal Tag Manager tools

• Google Analytics URL Builder — create a UTM tag on the page you are on
• UTM IO — Google Analytics URL Builder to bulk create UTM tags

Google Tag Manager help

For WordPress

• Measure School — GTM for WordPress Plugin
• MonsterInsights — GTM Plugin for WordPress

Using GTM with other CMS 

Data Layer Building — Tracking the right clicks

• GTM Variable Builder
• Trigger Guide for GTM

Tag analysis — what’s firing on my site?

• Google Tag Assistant is a Chrome extension that ensures Google tags such as Google Analytics, Google Tag Manager, Adwords Conversion Tracking and more are working correctly. 
• Data Slayer is a Chrome extension for debugging and testing tag management (Google Tag Manager, DTM, Tealium) and analytics implementations.

• Using Meta Pixel with GTM
• How to add schema in GTM

Templates to use to map commerce to GA4

Consent Management Platforms with resources about Google’s Consent Mode

• Cookie Script 
• Cookie Pro
• Cookie Information

‘How to’ helpers

• 3 ways to do segmentation in Google Analytics 4
• How to make a Google Analytics 4 custom report in :30 seconds
• 11 steps to setting up a successful GA4 property
• How to make a GA4 landing page report in 10 easy steps
• Using Google Analytics 4 integrations for insights and media activations

Getting started with Google Analytics 4

Catch up on the entire series:

The post Tools and resources: Getting started with Google Analytics 4 appeared first on MarTech.

• Setup Assistant: Currently the user has to create a new property in GA4 for each Universal Analytics (UA) property and then configure the data collection and privacy settings. The updated version of Setup Assistant — expected early next year — will automatically do this and enable Goals and Google Ad links. 
• Behavioral modeling: This is designed to fill in the gaps in understanding customer behavior when/if cookies go away. Expected to go live soon, this feature will provide real-time info on customer behavior while respecting privacy.
• Data-driven attribution: DDA will add custom channel grouping which enables cross-channel comparisons of cost-per-acquisition and return-on-ad-spend.

Dig deeper: GA4: What marketers need to know for a successful transition

• New homepage design: This went live today. According to Google’s marketing blog, it “is personalized for customers, highlighting key top line trends, real-time behavior and their most viewed reports.” The company has also added a feature that uses machine learning “to look for trends and insights and surfaces them directly to advertisers on the home page.
• Campaign Manager 360 integration: Expected soon, this will provide marketers with a more complete picture of their advertising performance alongside web / app behavioral metrics.

And speaking of Campaign Manager, Google is delaying its phaseout until July 2024 to give enterprise customers more time to migrate to GA4. UA’s phaseout in July 2023 is unchanged.

Why we care. Google promised it would continue rolling out GA4 improvements and they are delivering. The Setup Assistant change will make life much easier for those migrating from UA. The other changes represent big adds to an already impressive product.

Getting started with Google Analytics 4

Catch up on the entire series:

The post Google rolls out new features for GA4 appeared first on MarTech.

In the last post we discussed the GA4 Setup Assistant in Universal Analytics. Now we’re going to look at the GA4 Setup Assistant in GA4 itself.

Once you’ve used the setup wizard in UA to create a new GA4 property, it automatically sends you to GA4’s setup assistant. This assistant has tools to select the goals you want to import, copy Google Ads links and add users who can access your current property.

The first thing to do is start tracking a data stream with Google Tag Manager (GTM). These streams are the sources of data that feed into your GA4 property. You need to create at least one data stream to collect data. 

“Data collection is ‘I want to know other things about people,”’ says Harris. “I want to be able to know demo location. Are they in market? Not in market? And, as long as people have given consent for it and we’re collecting information, you’re going to be able to see that all here. For better or for worse, Google’s gonna collect the information regardless, we might as well take advantage of it.”

To start tracking with GTM, click the arrow next to “Tag installation.” 

Dig deeper: GA4: What marketers need to know for a successful transition

Doing that sends you to your data streams page. Then click on the web property and you’ll see the measurement ID which you need to use along with your GTM tag. You’ll also see options to use new and existing on-page tags. You will need to use your measurement ID to start tracking with GTM. 

1. Go to your GTM account and create a new tag. 
2. Go to Tag configuration > Google Analytics: GA4 configuration.
3. Enter the measurement ID you got from clicking on the web data stream in the new property. 

Once it is set to fire on all pages you’re all set to start collecting data.

Google signals

Once you’ve done that, go to property settings and turn on Google signals — which gathers data from Google users who have turned on ads personalization.

“That’s a key thing,” says Harris. “People forget to come in here and turn it all on. Make sure that your granular location is turned on. Make sure that all these different pieces are turned on so you can have all of that.”

To turn on Google signals:

1. In Setup Assistant, click the Actions menu Forward arrow to the right of the row.
2. Click Manage Google signals.
3. In Data collection, turn on Google signals data collection.

Mark an event as a conversion

Nomenclature reminder: In GA4 any interaction with a website or app is an event. 

To measure events, they must first be marked as a conversion.

GA4 automatically designates the following events as conversions. 

• purchase (web and app)
• first_open (app only)
• in_app_purchase (app only)
• app_store_subscription_convert (app only)
• app_store_subscription_renew (app only)

You can also mark an additional 30 conversion events per property

.(Go here to see how to migrate your UA Goals to GA4 Events.)

To mark an existing event as a conversion, follow these steps:

1. In GA4 go to Configure > Events on the left.
2. In the Existing events table, select the toggle under Mark as conversion.

If you recently created an event or haven’t created the event yet, see Set up conversions for information about how to mark new events as conversions.

• Reminder: You must import Google Ads links from an existing Universal Analytics’ property into the new GA4 one in order to see Google Ads data in your GA4 reports. 

Custom events

You can also create custom events. Before you do, make sure there aren’t any automatic, enhanced measurement or recommended events which already provide what you need.

To create a custom event:

1. Log into GTM and click on “Tags” in the left side menu.
2. Click on “New.”
3. Name your tag and click on “tag configuration.” 
4. Then you’ll see a list of tag templates, click on “Google Analytics: GA4 Event.”
5. Click on “Select configuration.”
6. If you’ve set up a configuration tag, select it. If not select “None-Manually set ID.”
7. Enter the measurement ID. (Reminder: It’s in the Admin section under “data streams.”)
8. Enter the name of the tag you created before in “Event name.”
9. Then you will need to click on “Event parameters” in the drop down menu. 

Google does an excellent job of explaining how to set event parameters here.

When you’ve set those, clicking on the “trigger” button creates a new trigger. Click on the “+” button, then name the trigger and click on “Choose your trigger type.” Click on “All elements,” then choose some clicks and set the trigger condition.

Getting started with Google Analytics 4

Catch up on the entire series:

The post GA4 Setup Assistant part 2: Getting started with Google Analytics 4 appeared first on MarTech.

As we all know, Google is ending support for Universal Analytics (UA) next July and replacing it with GA4. Google has two different GA4 Setup Assistants, one in UA and one in GA4, to help you migrate from one to the other.

Dig deeper: Using Google Analytics 4 integrations for insights and media activations

Here’s what you need to know about the Setup Assistant in UA.

“In a Universal account there’s this GA4 setup assistant,” says Harris. “This actually has a couple of sweet pieces. This is where you can enable the tagging and it also allows you to set up and import the goals and anything from the Google Tag Manager (GTM).”

What does the GA4 Setup Assistant do?

It creates a new GA4 property that collects data in parallel with your existing Universal Analytics property. It doesn’t change your Universal Analytics property, which will continue to collect data. Both properties can be accessed and managed via the property selector or Admin screen.

You have to create GA4 versions of your UA properties because GA4 is structured completely differently than UA. It’s impossible to move all your data from one to another.

How do I find it?

In the admin section of your UA account, there’s a button marked “GA4 setup assistant.”

Clicking on it brings up a wizard that:

• Creates a new GA4 property. It will not have the historical data your UA property has. It only collects data going forward. Your original property is not affected in any way by this.
• Copies basic settings from your UA property. You can manually configure additional settings like conversions, audiences, events and product links. 
• Activates Enhanced Measurement. This is done automatically. You must ensure that no Personally Identifiable Information (PII) is sent to Google.

One of the many useful things about the UA Setup Assistant is that it creates a checklist of what’s needed to get your GA4 property up and running. 

• VERY IMPORTANT: You must already be using Google tags for this to work. From Google Support: “If you use a website builder or your site is hosted on a Content Management System (CMS) (for example, WordPress, Squarespace, etc.) that doesn’t already use gtag.js, follow these instructions for your particular CMS. Do not simply paste your “G-” ID into the field that your CMS provides.” 

To use your current GTM tags, click the box marked “optional.” Be aware that customizations won’t automatically transfer. You should be able to use your current tags if you’re using gtag.js. If you’re running an older version such as analytics.js, this won’t work.

You must configure your GTM tags for GA4 to work.

Time to click the button

Having resolved any or all of these warnings, click the “Create property” button. A new tab will open showing your new GA4 property. Just to reiterate: Doing this won’t affect your existing property isn’t in any way.

In addition to creating the GA4 property, the setup wizard also copies the property name, website URL, and currency and time zone settings from the existing UA property.

When all that is done, you will be sent to the setup assistant in your new GA4 property. A reassuring message appears saying, “You have successfully connected your properties.” 

The next post will look at the setup assistant in GA4.

Getting started with Google Analytics 4

Catch up on the entire series:

The post GA4 Setup Assistant part 1: Getting started with Google Analytics 4 appeared first on MarTech.

In this post we’ll be talking about UTM tagging. To some folks this may seem like a very basic thing, but it’s so important in GA4 that a refresher is in order.

Dig deeper: GA4: What marketers need to know for a successful transition

“GA4 is based a lot around source, medium, as well as campaign and things like that,” says Colleen Harris. “So it’s becoming a time where UTM tagging of more than just source medium is necessary for all of your strategies. You really want to be looking at trying to use a keyword, trying to use campaign content, things like that. The more that you put into those UTM parts, the more that you’re able to get in the reporting in GA4.”

What is UTM?

UTM codes are text you add to a link that gives your analytics tool more information about each link. 

What does UTM do?

It tells you specific information about how your traffic is coming to you. Things like:

• Where is the traffic coming from?
• How is it getting to me?
• Why is it coming to me?

How does it work?

By using elements called “UTM parameters.” These include:

• utm_source — Where traffic is coming from. Sample sources can be facebook, google, twitter, linkedin (UTM source and medium elements must always be lowercase).
• utm_medium — Identifies the medium of the traffic. More below.
• utm_content — Tracks the ad or the link where the website traffic is sent to. This lets you test variations of the same ad.
• utm_name — Identifies the particular campaign this traffic is linked to.
• utm_term — specifically for paid search activities and for Google Ads. It is auto-populated if auto-tagging on Google Ads and Google Analytics 4 are turned on.

As a result, you can track the performance of each of those links. 

Don’t get creative with names in the medium field

Below are the only names that should be used in the medium field in the UTM tag. Using other definitions of “medium” which corrupts the GA reports. 

Tools to use

“My two favorite tools to build UTM tagging [are] the Google Analytics URL Builder, which is a Chrome extension, and the UTM IO is a total game changer for making UTM work and happen at scale,” says Harris. 

Also, a helpful thing to keep in mind from Colleen: “Even those of us who are thought leaders, industry experts on GA4, we’re all figuring this out, too. It is a plane being put together at 30,000 feet. So, don’t feel like you’re alone in this lack of understanding or frustration.”

Getting started with Google Analytics 4

Catch up on the entire series:

The post UTM tagging: Getting started in Google Analytics 4 appeared first on MarTech.