Google Analytics 4 for E-commerce Companies

Mastering e-commerce events, checkout funnel measurement, and revenue attribution in Google Analytics 4.

Speakers: Berkan Bağcı

Content author

18 Oct 2023

Video Transcript

⏱ 23 min read• 4,095 words

Read the full speech or switch languages

— Good morning, everyone. I’m Nilden Himmetli from the Marketing Department. I’ll be your host today. I’ll guide you through our agenda and opening presentation. Welcome to all our e-commerce digital marketing pros joining us today. Our GM, Tuğçe, was supposed to open today. Unfortunately, she can’t be here. She tried her best to make it. I’ll be stepping in for her. We’ll cover the latest in digital marketing. We’ll also discuss how AI impacts the e-commerce sector. We used to host our "Digital Zone" event in person every year. Moving online helped us reach a much larger audience. Still, we’ll keep hosting physical industry meetups across Turkey.

Need Wi-Fi? Connect to the İstasyon-Guest network for free access. Before we bring our speakers out, let me introduce ZEO. ZEO started as an SEO consultancy at Bilkent Cyberpark. We launched our event in Istanbul in 2013. It was called SEO Zone back then. It’s now known as Digital Zone. We saw huge interest from brands. That led us to open our Istanbul office in 2014. In 2016, we launched İçerik.com to connect brands with writers. We also added PPC and data analytics to our services. Our London office opened in 2018. We released our Rank Tracker tool, WAP, in 2020.

So, what do we do at ZEO? We have tons of blog posts on digital marketing. We share deep industry insights. We dive into key topics. Check out all our content on our web site. We offer free tools under ZEO Tools. MFI Checker is a great example. Find them all under the ZEO Tools section on our web site. We also publish case studies of our success stories. Plus, we have detailed industry reports. My apologies, I misspoke earlier. Our industry reports cover site and keyword analysis. We used to focus only on Turkey. This year, we started publishing reports for the MENA region too.

As mentioned, we host Digital Zone annually. We also hold monthly Digital Zone meetups. We run SEO Bootcamp programs for students and grads. We train them and help them land jobs. Today marks our first industry meetup. We are thrilled to be here with you. Beyond Digital Zone and our meetups, we launched these industry gatherings. We want to connect digital marketing experts with select guests. We aim to explore new trends in specific sectors together. ZEO has also won awards across many categories. You can see our MENA Search Awards here. We also have our UK Search Awards and European Search Awards.

Here are the brands ZEO has worked with over the years. We currently partner with over 100 brands. This is the ZEO team. You can meet some of them in the foyer. Thanks for listening. Let’s welcome our first speaker. Berkan, founder of OMetrics, will present on what Google Analytics 4 brings to e-commerce companies.

— Hi everyone, welcome. I’m Berkan Bağcı, founder of OMetrics. We specialize in Analytics consulting. Today we’re talking about Analytics 4. Most of you know it’s a major industry shift. We have two months left. Universal Analytics is shutting down for non-360 users. We’re moving to Analytics 4. First, who here has opened, explored, or pulled reports in Analytics 4? Let me see your hands. Great. We have about an hour. Let’s say 50 minutes, plus 10 for Q&A. I’ll cover some Analytics 4 tips and key points that will impact you.

I’ll share insights to help your workflow. Please ask any questions you have. We’ll do a Q&A at the end for deeper dives. I’ve been working in digital for 15 years. I founded OMetrics in 2019. We focus on Analytics, Tag & Tracking, and conversion optimization. Let’s cover the agenda. What is Analytics 4? What are the core e-commerce definitions in Analytics 4? We have some cool dashboard features. It’s different from Universal. How do these work? Some might not know these hidden features. How does the audience side work in Analytics 4? I’ll cover that. We have the Explore area. Think of it as advanced custom reports.

I’ll discuss these and take questions at the end. July 1, 2023, is a major date. For non-360 users, Universal stopped processing data then. We need to export and store our Universal data before 2024. We can use an API or other methods. Google announced that API access will shut down completely by July 2024. There is one major reason Google is rushing to move away from Universal. It’s all about GDPR. Universal isn't a GDPR-compliant tool. Google faced massive fines, especially in France. This creates issues for us regarding historical data access. It’s going to be a headache for all of us.

We have about 14 months. Start backing up your historical data now. It’s crucial. Analytics 4 lets us track apps and web together. It creates a unified platform. We monitor iOS, Android, and web in one dashboard. Reporting is much easier now. We track everything using the same events. It works across all three platforms perfectly. Analytics 4 is event-based. Every action is an event. Even starting a session is an event. It’s called Session Start in Analytics 4. This is how it calculates session counts.

Other features also rely on Session Start. I’ll cover those soon. Everything being event-based is a huge win. It makes building funnels and reports much easier. You might have noticed the shift. It’s similar to the Facebook Pixel logic. Analytics 4 tracks unique users. Once you have Google sinyallerini aktif, it links app and web users. It identifies the same person across platforms. Universal was different. It relied on unique cookies. Analytics 4 is smarter. It wants to know it’s me, Berkan. It tracks me across apps, web, and different browsers.

I mentioned GDPR earlier. Analytics 4 is GDPR compliant. That’s a key reason for the switch. This is internal info. We verified it. They’re moving fast because of GDPR. There’s also predictive modeling. Predictive models let you build segments based on user behavior. I’ll show you examples soon. It predicts if users will buy in the next 7 days. It uses their last 28 days of activity. You can share these audiences with Google Ads for remarketing. Analytics 4 has a hierarchy. It goes account, property, and data stream. Data stream covers our iOS, Android, and web areas.

Universal was different. Data collected at the property ID level. It was grouped into views. Here, it’s different. Data streams collect the info. It gathers data from iOS, Android, and web. These form the foundation of the property. Data from all three platforms creates the main property data. Let’s look at the core differences between Analytics 4 and Universal. Universal event funnels were only in 360. Analytics 4’s biggest advantage is building event funnels. I use this feature all the time. It requires a very detailed setup. My advice? Get into the details at every step in Analytics 4.

These details build great funnels and audiences later. They help you work deeper. You can reach people more effectively. I don't know if you use segment overlap. It looks great and provides deep insights. Universal didn't have this. It was limited to specific goals. It is possible in Analytics 4. I will show you the details soon. Session differences affect our reporting. Everyone compares Universal session counts to Analytics 4. You will see differences here. Session expiration rules cause these gaps. In Analytics 4, sessions don't end at midnight. In Universal, sessions ended at 23:59. A new one started at 00:00.

Here is why they don't expire. The session start event triggers when a user arrives. This event starts the session. If the user stays, the event doesn't re-trigger. So, a new session doesn't start. Sessions don't end at midnight in Analytics 4. No new session start event triggers then. The same applies when traffic sources change. In Universal, changing a UTM ended the session. It started a new one. That doesn't happen in Analytics 4. It follows the same logic. Since the session start event doesn't trigger, no new session begins. BigQuery integration was only in Universal 360.

In Analytics 4, everyone can use this. You can collect offline data in one place. You can also import online data via BigQuery. This lets you merge both datasets. You can feed CRM teams using custom queries. What changes? We are moving on from Universal. We only have two months left. Session and user counts will definitely drop. Compare them on the same day. You will see the drop immediately for the reasons I mentioned. Sales and revenue data will also differ by channel. Take organic traffic, for example. If Universal shows 1,000 organic sales, Analytics 4 will show something else. It might be 900 or 1,100. This depends entirely on the Analytics 4 attribution model.

Universal uses last non-direct click in standard reports. Analytics 4 uses data-driven attribution. That is why sales and revenue figures differ. Remember, it works on an event-based model. It has a specific event mechanism. How does this work? Let me explain. We have an event. Every event has parameters underneath it. There are many parameters. These can be event-scoped, user-scoped, or item-scoped. Item-scoped parameters are new. I think they launched about a month ago. Before, we only had event and user-scoped parameters. Here is what that means. This is an example of an event-scoped parameter. I am triggering a page view here.

I set the page type to product listing. I named the page iPhone 14 models. You can scale this up. These are all parameters. They work based on events. This is an e-commerce action. This e-commerce action is view item. It tracks product views. Under items, there is a lot of product data. This is sample code from Google. You can adapt it for your own web site or app. Until a month ago, we were limited. Now, just like Universal, we can use custom dimensions. We can create as many parameters as we want. We can name them anything. You can convert them to product-scoped parameters in Analytics 4.

User-scoped parameters are like the dimensions we used in Universal. We collect user IDs, gender, age, and similar data. There are only 3 scopes right now. I doubt a fourth one is coming. Product-scoped parameters arrived very late. They came just 3 months before the transition. That was a bit problematic. It is important to grasp this. Every action is logged as an event. This helps you collect the right parameters for every event. For example, I only get these two data points for a page view. The more I expand this, the more data I get for this event. Don't overlook that. Everyone is testing e-commerce events now. I will move through this quickly. We have view item, add to cart, remove from cart, and wishlist.

Wishlist is here. View item list is here. We have product listing views and clicks. Promo data is included. Views and clicks too. View cart was missing. Now we have View cart. Begin checkout is here. Shipping info, add payment info, purchase, and refund are all set. These are all product-based events. They use an item array. They feed e-commerce data. If the naming is off, you break your e-commerce tracking. If you write add to basket instead of add to cart. It won't feed Analytics correctly. The names must match exactly. You don't have to feed add shipping info with just items.

You can use the event-based parameters I mentioned earlier. I will show you an example on screen soon. I track payment steps using the add payment info event. I want to see the products there too. But I also added steps as parameters under this event. Those steps help me identify the current stage. Don't think of these e-commerce events as item-only. You can expand them with event-based parameters. Here are three screenshots you will see. After the changes to item scope, these unfortunately changed too.

You see two checkouts here. There's checkout and items checkout. There's e-commerce purchase and item purchase. Add to cart and items add to cart. Use these metrics for channel or device-based reports. The other is for product-level reports only. You can't use checkout in product-level reports in Analytics 4. You also can't use items checkout in channel-based reports. Just a heads-up on that. Things have changed here. Keep that in mind. Let's cover some key e-commerce metrics. Analytics 4 splits revenue into three categories. One is e-commerce purchase. Another is in-app purchases.

This includes things like in-app subscriptions. The third is publisher revenue. Assuming we're e-commerce focused, in-app purchase and publisher revenue use different events. These metrics are distinct. E-commerce purchase is the total count of e-commerce transactions. It excludes in-app purchases. The standard purchase metric includes those in-app sales. For e-commerce, these will match. But if you have subscriptions or an in-app store, they will differ. Right now, they show the same data. There’s a change here. It’s between purchase revenue and total revenue. Purchase revenue is total site or app revenue minus refunds. If you track refunds in Analytics 4, I highly recommend it.

You need to capture purchase revenue. That’s your actual revenue. Total revenue is the data without refunds deducted. Say I sold 1,000 lira. 200 was refunded. I’ll see 800 in purchase revenue. I’ll see 1,000 in total revenue. You’ve surely seen both in your Analytics 4 reports. If you aren't tracking refunds, there’s no difference. But that’s the main distinction. Track refunds and you’ll see the gap. Item revenue shows total product sales, like in Universal. It excludes shipping and taxes. It’s just revenue from the products. Analytics 4 brought two new concepts. We check these as soon as we start our day.

We check acquisition to see what happened. Where did it come from? Now we have user acquisition and traffic acquisition. User acquisition is about acquiring the user. Traffic acquisition reports on the traffic we drive. Check your user acquisition reports. The metric columns start with new user. You won't see sessions there directly. It starts with new user and continues with engaged session. We couldn't clearly separate this in Universal. It gives us this option. I check the user acquisition report for first-time users. If I want to see traffic, I check traffic acquisition. I want to know who visited today and what they did.

I check user acquisition to see who is new today. That is the difference. You will see this often. You might see 25k in organic here and 35k there. That is the reason. User acquisition tracks acquiring the user. Traffic acquisition tracks the traffic within those dates. Make sure you grasp this. Customizing reports is also key for us. I could not use real data here. I could not show it clearly. But since you are exploring, you have seen it. There is an edit button on the top right. You can customize this report area.

Let me show you how. Clicking edit opens up your dimensions and metrics. It shows you the report area. It asks which dimensions and metrics you want to use. You can make your selections there. Remove what you do not need. I removed some while doing this. Add to cart, checkout, and purchase are not default. I added them and saved the report. This is the biggest difference between Analytics 4 and Universal. You can customize these dashboards. I mean, they are customizable at the account level. If two people log into the same account, they see the same changes.

It changes for the property, not the individual. This is our standard traffic acquisition report. It didn't have add to cart, checkout, or purchase. I added them. Now, this report is completely customized for my property. I'll save it and move on. Some of you might have missed this feature. Let me mention another useful trick. This is our left menu. We have life cycle, real time, and user info. These are called collections on the backend. You see life cycle and user as collections here. You can create your own new collections. You can add topics under these new collections. Like demographic text. You can also add your own custom reports into these topics.

Just like we made custom reports in Universal. We can build custom reports here to a certain extent. Then we place them under these collections and topics. Look, this is a collection I created. There are topics here. I separated them as organic, paid, and internal traffic. I just threw some reports in there. I didn't build them from scratch. I just pulled the existing ones. But I can add my own reports to these too. I have that option too. I save them and push them live. We publish it. It’s just like publishing in Tag Manager. We publish it here too. This is the unpublished version.

This is it. The published version is over here. I closed Life cycle and User. I opened the digital marketing collection you see here. It has organic traffic, traffic, and internal traffic topics. It also has reports inside. This will really simplify your work. We use Data Studio, of course. It’s useful. But using a screen like this in Analytics is a huge advantage. It makes things easier. We use it this way too. It’s genuinely helpful. I highly recommend it. Let me go back to show you our reports on this screen. You access the library screen right here. If you have admin permissions, you can see it. There is a library area at the bottom left. Click there to enter the screen I mentioned.

You can manage your tasks from there. Remember, all changes affect everyone with access to this property. Be careful when deleting things. Now, let’s talk about audiences. One of the biggest features of Analytics 4 is predictive metrics. It uses algorithms and machine learning. Even though I don't think it works perfectly in Turkey yet, it gives us data. It predicts what might happen in the next 7 days based on the last 7 days of purchases. It gives you those insights. It gives you the probabilities. It builds these audiences. Link your Analytics 4 to Google Ads. You can push these audiences directly to Google Ads. Test them out there. I personally claim it doesn't work.

But it might work for your account. Check the audience section. You'll see them ready to go. You'll see them pre-built. You need Google sinyallerini aktif to see them this way. When setting up your property, enable Google sinyallerini. Grant these permissions. That's how these calculations happen. This builds the audiences. Then you can share them with Google Ads. These are just the pre-built ones. We can also create custom audiences. For example, look at this. Users who viewed an item and added to cart within 30 seconds. Analytics 4 is great for these sequential actions. The biggest win is the time-based logic.

In Universal, we had to calculate this manually. We fired events every 2, 5, or 10 seconds. We tried to capture it. Analytics 4 handles this natively. Here is what we defined. They must view an item. Then add to cart as the next action. We added a 30-second window. If they add to cart within 30 seconds, group them. Share this audience with Google Ads. Then you can run remarketing campaigns. Here’s a second benefit. Everything runs on events. We can use "add parameter" for those details I mentioned. We can pull in all that data. We know the product brand.

We know the category. Let's say we have other details too. We can filter these in the "add parameter" field. We can narrow down the audience. We can make retargeting more precise. We can make it even more relevant. Like I said, you can toggle this duration on or off. It’s up to you. But you can build audiences this way. Here’s another audience. We’re targeting users who viewed over 5 products and added over 3 to cart in a day. We can get that granular. This is a big deal for us. We’ve excluded "purchase" here. They viewed 5+ products and added 3+ to cart. But they didn't buy. I need to engage them.

I need to experiment with this. This is the audience I should use. So, what reports can I build? Let’s head to the Explore section. Explore is a whole new world in Analytics 4. The interface takes some getting used to. But once you’re used to it, it’s super powerful. I mentioned payment earlier. This is just the credit card payment page. What are we trying to track on the credit card payment page? Users land on the page. They start typing their name. They enter their number, month, and CVV. They check the box. They hit complete order. Then they buy.

Event-based tracking gives me all this data clearly. Universal did this indirectly. But Analytics 4 is much easier to use. I see a 65% purchase success rate on the credit card page. I converted 65 out of 100 people. I lost 35 users on the payment page. That’s a red flag for me. The best part is the segmentation. We don't just use standard Google Analytics 4 dimensions. We use custom dimensions and custom parameters too. We split this by mobile and desktop. It shows the steps for both correctly. I can see exactly where I’m losing users by device type. We used device category here. You can use anything. Let's say we track an app.

We set up an app funnel. I can add app versions as a breakdown. I can see where I lose users from page view to purchase. If you can imagine it, you can track it here. Use them as parameters or breakdowns. What does this funnel look like? What do we see when building it? It’s the same logic as building an audience. I trigger an event here with add payment info. See, they’re all add payment info. I just change the difference with a step. I have a parameter called step. I use it to segment everything. I break down page views and card entry steps.

Here is why I do this. Add payment info tells me which products are involved. This lets me create product-based funnels. We have many categories on e-commerce sites. Let’s say my funnel rate for credit card payments is 65% for sneakers. It’s 85% for kids' shoes. I can investigate if there’s a specific issue with sneakers. I can focus on that. I wanted to show that we can add custom parameters to e-commerce events. My favorite feature in Analytics 4 is segment overlap. It’s incredibly valuable.

Anyone can build and use this for their business. I created a standard one. Users who added to wishlist. Then, users who abandoned their carts. It shows me the intersection of both. This intersection shows a huge overlap. Cart abandoners and wishlist users are mixing. There might be a connection here. Maybe they use the wishlist differently. They might not see it as a favorite. They might just save it for later. It depends on your logic. I personally linked wishlist users with cart abandoners.

We can build audiences from these intersections. Then push them to Google Ads. The best part is the segments are limitless. Say they bought kids' shoes. But only browsed men's sneakers. If you compare these, you might find a huge overlap. You can then adjust your sales or bundle scenarios. It doesn't provide automated alerts, though. You have to do the heavy lifting. You might need to do some forecasting. Sure, there are tools for this. But you have segment overlap right here in your interface.

It is very easy to use. Find it under Explore. Create a new report there. It will ask for report techniques. Choose table, graph, or segment overlap. This is another key feature. In the Explore section, check out Cohort. It’s not just Segment Overlap. Universal had this too. Cohort gives me a breakdown by platform. I find this really valuable. It shows me cohorts based on purchases. I didn't use visits here. I used purchases. There should be three or four different events. It builds cohorts based on these events.

On the web, 1,825 users bought between April 3-8. 136 of them bought again the next week. It shows me that. We’d see different results for iOS. Analytics 4 gives me this level of detail in Cohort. That’s all for now. Thanks for listening.

This transcript was generated using AI speech recognition and verified against subtitle style rules.

Content author

Zeo's Guest

author

Contact us

How we handle your data

Open as a full page