The Google Analytics 4 deadline is July 1, make your move before it’s too late and get AI-powered insights to improve your ROI.
The Google Analytics 4 deadline is July 1, make your move before it’s too late and get AI-powered insights to improve your ROI.
Three years ago, we introduced Google Analytics 4, a re-imagined tool that helps you get a complete view of consumer behavior across web and app by using first-party, modeled data. This is critical in an evolving privacy and technology landscape, where marketers have to rethink their approach to measurement in order to keep getting the insights they rely on. Today we’re introducing new resources to help you make the switch to Google Analytics 4, improved machine learning features, actionable reporting and new integrations.
Earlier this year we shared that we will begin sunsetting standard Universal Analytics properties on July 1, 2023. We recognize that setting up Google Analytics 4 to fit your needs takes time and resources, in particular for large enterprises with complex Analytics 360 setups. To allow enterprise customers more time to have a smoother transition to Google Analytics 4, we’re moving the Universal Analytics 360 properties’ sunset date from October 1, 2023 to July 1, 2024. We're focusing our efforts and investments on Google Analytics 4 to deliver a solution built to adapt to a changing ecosystem. Because of this, throughout 2023 we'll be shifting support away from Universal Analytics 360 and will move our full focus to Google Analytics 4 in 2024. As a result, performance will likely degrade in Universal Analytics 360 up until the new sunset date.
To help everyone make the move, we're launching new resources and tools to help you get started with Google Analytics 4. Our step by step guide helps you complete the entire setup of Google Analytics 4 at your pace and customize it to your needs. Or, if you prefer a more automated experience, you can use the Setup Assistant in the admin section of your Universal Analytics property. Once a Google Analytics 4 property is created and connected, the Setup Assistant can automate some required setup steps and help you track your progress. For example, the Setup Assistant lets you select the goals you want to import to Google Analytics 4, copy desired Google Ads links and audiences, and add users who have access to your current property.
The Setup Assistant tools
The best Google Analytics 4 setup comes from following the steps above to create a customized property tailored to your needs. The earlier you do this, the more historical data and insights you will have in Google Analytics 4. For example, SunCorp, one of Australia's largest financial services brands, prioritized setting up Google Analytics 4 to build a base of historical insights.
When Universal Analytics stops collecting data in 2023, we will have over two years of insights and reporting in Google Analytics 4. This is critical for a business like us to ensure we have a robust foundation of data to inform decision making.
Beginning in early 2023, the Setup Assistant will also create a new Google Analytics 4 property for each standard Universal Analytics property that doesn’t already have one — helping you jumpstart your migration. These new Google Analytics 4 properties will be connected with the corresponding Universal Analytics properties to match your privacy and collection settings. They’ll also enable equivalent basic features such as goals and Google Ads links. If you’d rather begin the switch on your own, you can opt out of having the Setup Assistant do it for you.
Behavioral modeling uses machine learning to fill gaps in your understanding of customer behavior when cookies and other identifiers aren’t available. Soon, behavioral modeling will also be available in the real time reporting, giving you a complete view of the consumer journey as it happens. It’s helping marketers like Nestlé get accurate insights from more customer activity.
Behavioral modeling with Consent Mode in Google Analytics 4 drove a 23% increase in the observable traffic in analytics reporting on European and UK websites.
To get a more accurate picture of your campaigns across all of your marketing touchpoints, we will soon introduce custom channel grouping in Google Analytics 4 to help you see the performance of different channels aggregated. For example, you’ll be able to compare the performance of your paid search brand with your non-brand campaigns. These custom channel groupings work in reporting retroactively, and across the advertising and explore workspaces.
Your insights are only as good as the actions you can take from them. On top of Google Ads, Display & Video 360 and Search Ads 360, we will soon launch an integration with Campaign Manager 360 via Floodlight. This will allow marketers to bid towards Google Analytics 4 conversions in Display & Video 360’s automated bid strategies.
Now is the time to make Google Analytics 4 your cross-platform Analytics solution. Get started with Google Analytics 4 now, complete the setup by following our step by step guide and learn how to get the most out of it with the refreshed Google Analytics 4 certification.
In today's measurement landscape, businesses need to navigate new challenges to understand the complex, multi-platform journeys of their customers — all while prioritizing user privacy.
Two and a half years ago, we introduced Google Analytics 4 to address these evolving measurement standards and help businesses succeed. Google Analytics 4 has the flexibility to measure many different kinds of data, delivering a strong analytics experience that’s designed for the future. It allows businesses to see unified user journeys across their websites and apps, use Google’s machine learning technology to surface and predict new insights, and most importantly, it’s built to keep up with a changing ecosystem.
Without a modern measurement solution, you leave essential insights on the table that can impact your business. So now is the time to make Google Analytics 4 your cross-platform Analytics solution. We will begin sunsetting Universal Analytics — the previous generation of Analytics — next year. All standard Universal Analytics properties will stop processing new hits on July 1, 2023. Given the new Analytics 360 experience was recently introduced, Universal Analytics 360 properties will receive an additional three months of new hit processing, ending on October 1, 2023.
Universal Analytics was built for a generation of online measurement that was anchored in the desktop web, independent sessions and more easily observable data from cookies. This measurement methodology is quickly becoming obsolete. Meanwhile, Google Analytics 4 operates across platforms, does not rely exclusively on cookies and uses an event-based data model to deliver user-centric measurement.
And though Universal Analytics offers a variety of privacy controls, Google Analytics 4 is designed with privacy at its core to provide a better experience for both our customers and their users. It helps businesses meet evolving needs and user expectations, with more comprehensive and granular controls for data collection and usage. Importantly, Google Analytics 4 will also no longer store IP addresses. These solutions and controls are especially necessary in today’s international data privacy landscape, where users are increasingly expecting more privacy protections and control over their data.
Google Analytics 4 is designed with your key objectives in mind — like driving sales or app installs, generating leads or connecting online and offline customer engagement.
Here are just a few ways Google Analytics 4 can support your business.
Understand your customers across touchpoints
Get a complete view of the customer lifecycle with an event-based measurement model that isn’t fragmented by platform or organized into independent sessions.
For example, UK-based fitness apparel and accessories brand Gymshark used Google Analytics 4 to measure across its website and app, allowing the Gymshark team to better understand how users moved through the purchase funnel. As a result, they reduced user drop off by 9%, increased product page clickthroughs by 5% and cut down their own time spent on user journey analysis by 30%.
Google Analytics 4 was the perfect choice in understanding and improving our new e-commerce app.
Improve ROI with data-driven attribution
Use data-driven attribution to analyze the full impact of your marketing across the customer journey. It assigns attribution credit to more than just the last click using your Analytics data, and helps you understand how your marketing activities collectively influence your conversions. You can export that analysis to Google Ads and Google Marketing Platform media tools to optimize campaigns.
Measure engagement and conversions with business and compliance needs in mind
With new country-level privacy controls, you can manage and minimize the collection of user-level data — like cookies and metadata — while preserving key measurement functionality.
Get greater value from your data
Machine learning generates sophisticated predictive insights about user behavior and conversions, creates new audiences of users likely to purchase or churn and automatically surfaces critical insights to improve your marketing.
Easily activate your insights
Expanded integrations with other Google products, like Google Ads, work across your combined web and app data, making it easy to use Analytics insights to optimize your campaigns.
McDonald’s Hong Kong met its goal to grow mobile orders using a predictive audience of “likely seven-day purchasers” and exporting it to Google Ads — increasing app orders more than six times. The team saw a 2.3 times stronger ROI, a 5.6 times increase in revenue, and a 63% reduction in cost per action.
“Google Analytics 4 has equipped us with a strong measurement foundation. We are able to get valuable insights from our first-party data with machine learning and utilize them in our marketing, driving impressive results to future-proof our business.”
— Tina Chao, McDonald’s Hong Kong Chief Marketing and Digital Customer Experience Officer
And now, Search Ads 360 and Display & Video 360 integrations are available for all customers. This means that any Google Analytics 4 property — standard or 360 — can activate its Analytics data, like conversions and audiences, in Google Marketing Platform buying tools to strengthen campaign performance.
Address your enterprise measurement needs
New sub and roll-up properties in Analytics 360 allow you to customize the structure of your Google Analytics 4 properties to meet data governance needs. This ensures that different teams or partners, like advertising agencies, can access the data they need in accordance with your policies.
Analytics 360 also offers higher limits to meet increasing demand — up to 125 custom dimensions, 400 audiences and 50 conversion types per property. And you’ll have peace of mind with service legal agreements (SLAs) across most core functionality, including data collection, processing, reporting and attribution.
"As a large enterprise business with a wide product portfolio, the new Analytics 360 has unlocked insights for our teams to make data-driven decisions, while providing the ability to meet our complex data governance needs with ease and flexibility.”
— Rashi Kacker, Director of Marketing Technology Innovation, Constellation Brands
All standard Universal Analytics properties will stop processing new hits on July 1, 2023, and 360 Universal Analytics properties will stop processing new hits on October 1, 2023. After that, you’ll be able to access your previously processed data in Universal Analytics for at least six months. Learn more about what to expect.
Make the move over to Google Analytics 4 as soon as possible to build the necessary historical data before Universal Analytics stops processing new hits. For guidance, check out our Help Center resources.
The web has to work for users, advertisers, and publishers of all sizes — but users first. And with good reason: people are using the internet in larger numbers for more daily needs than ever. They don’t want privacy as an afterthought; they want privacy by design.
Understanding this is core to how we think about building Google Analytics, a set of everyday tools that help organizations in the commercial, public, and nonprofit sectors understand how visitors use their sites and apps — but never by identifying individuals or tracking them across sites or apps.
Because some of these organizations lately have faced questions about whether an analytics service can be compatible with user privacy and the rules for international transfers of personal data, we wanted to explain what Google Analytics does, and just as important, what it does not do.
Fact: Google Analytics is a service used by organizations to understand how their sites and apps are used, so that they can make them work better. It does not track people or profile people across the internet.
Google Analytics customers are prohibited from uploading information that could be used by Google to identify a person. We provide our customers with data deletion tools to help them promptly remove data from our servers if they inadvertently do so.
Fact: Organizations control the data they collect using Google Analytics.
Fact: Google Analytics helps customers with compliance by providing them with a range of controls and resources.
Fact: Google Analytics helps put usersin control of their data.
Fact: Google Analytics cannot be used to show advertisements to people based on sensitive information like health, ethnicity, sexual orientation, etc.
Fact: An organization’s Google Analytics data can only be transferred when specific and rigorous privacy conditions are met.
And we use robust technical measures (such as Application Layer Transport Security and HTTPS encryption) to protect against interception in transit within Google’s infrastructure, between data centers, and between users and websites, including surveillance attempts by government authorities around the world.
A year ago, weintroduced the new Google Analytics to help you meet the challenges of an evolving measurement landscape and get better ROI from your marketing for the long term. Google Analytics 4 properties offer privacy-safe solutions to measure the customer journey, machine learning to predict outcomes and automate the discovery of insights, and easy activation of those insights in Google’s advertising platforms to enhance your marketing performance.
Since then, we’ve introduced features like improved advertising reporting and support for user consent choices that help you achieve your marketing objectives without compromising user privacy.
Now, we're launching additional capabilities, including an improved Search integration and smarter attribution to give you the insights you need to optimize performance across all of your marketing channels. We're also introducing new modeling features that will close gaps in your data and help you future-proof your measurement.
With these additional capabilities, we encourage you to use the new Google Analytics as your primary web and app analytics solution going forward.
Search Console provides detailed information about your website’s organic Search performance, including the site’s rank in Search results, queries that led to clicks, and post-click data like engaged sessions and conversions. With the new Search Console integration, you'll be able to understand the role that organic Search plays in driving traffic to and engagement on your site relative to other marketing channels like Search ads, email, or social.
Building on the two attribution reports, Conversion paths and Model comparison, we announced earlier this year, we are introducing data-driven attribution – without minimum threshold requirements – to Google Analytics 4 properties.
Google’s data-driven attribution models give you a better understanding of how all of your marketing activities collectively influence your conversions, so you don’t over or undervalue a single channel. Unlike last-click attribution, where 100% of the credit goes to the final interaction, data-driven attribution distributes credit to each marketing touchpoint based on how much impact the touchpoint had on driving a conversion.
Conversions by channel grouping using data-driven attribution
Data-driven attribution improves marketing ROI by helping you make smarter decisions about where and how much to invest, and as a result, drive more conversions for less cost. With its use of machine learning, data-driven attribution is a more durable approach that will deliver results even when it’s difficult to observe conversions. Notino, an ecommerce beauty platform, says data-driven attribution in Google Analytics 4 is essential to its measurement strategy.
We have seen benefits with using a data-driven attribution model compared to last click and have rolled it out as a standard for 23 of our markets. We are now excited to use the next generation of attribution reporting in Google Analytics 4.
Data-driven attribution will be available in attribution reports in the coming weeks. It will be available at the property level soon after, at which time you’ll be able to see attributed revenue and conversions in the Conversions report and in Explorations.
Using Google’s advanced modeling technology, the new Google Analytics allows you to fill gaps in your understanding of customer behavior when cookies and other identifiers aren’t available. It analyzes vast amounts of historical data, identifies correlations and trends between key data points, and uses those insights to make predictions about the customer journey.
We’re bringing a few new modeling capabilities to Google Analytics 4. First, conversion modeling is now used in attribution reports, the Conversions report, and Explorations to identify where conversions have come from and allocate them to the right Google and non-Google channels, such as Search ads, email, or paid social.
Second, behavioral modeling will soon be supported in reporting. Behavioral modeling uses rigorously tested and validated machine learning to fill gaps in behavioral data, like daily active users or average revenue per user. This allows you to conduct uninterrupted measurement across devices and platforms, and answer questions like, “How many new users did I acquire from my last campaign?” or “Which steps in my funnel have the highest user drop-off rates?”
Customers are seeing success using the new Google Analytics to help achieve key marketing objectives like generating leads, acquiring new users, and driving online and offline sales. Líder, a grocery retailer owned by Walmart Chile, is driving in-app purchases using predictive metrics and audiences. By marketing to a new “Likely 7-day Purchasers” audience generated by Analytics based on predicted purchase behavior, Líder increased its conversion rate to 5.4% from 0.3% for other audiences, and saw an 85% decrease in overall app campaign CPA.
We’ve seen firsthand the value that the new Analytics has brought to our business and plan on using more new capabilities as they become available in Google Analytics 4 properties.
Global beauty brand, L’Oreal, is also using the new Google Analytics to help adapt its measurement foundation for the future, and simplify how the entire organization generates business insights.
Google Analytics 4 democratizes the use of advanced data and analysis, making insights more accessible. The migration has been an opportunity for us to unify media and analytics with a single infrastructure that simplifies decision making.
Now is the time to build the measurement foundation your business needs for the future. We encourage you to make full use of your Google Analytics 4 property and put it at the center of your measurement in place of Universal Analytics.
At this year’s Google Marketing Livestream, we shared the latest updates coming to the new Google Analytics, the next generation of Analytics designed for the future of measurement.
With new privacy-safe solutions, Google is helping advertisers preserve marketing measurement while respecting user consent choices. This includes using machine learning to model conversions in Google Ads, so you can continue to optimize performance in a privacy-safe way when observed conversion data is not available.
Later this year, we’ll extend our modeling capabilities to certain reports in Google Analytics 4 properties to enhance your understanding of the customer journey when observed behavioral data is not available. If users don’t consent to analytics cookies, you’ll still be able to generate important customer insights while respecting your users’ privacy preferences.
For example, if there is incomplete data in your User Acquisition report, modeled data (in addition to observed data) will offer a more complete picture of the number of new users your campaigns have acquired.
We want to make the new Analytics experience as intuitive to navigate as possible, so you can discover key insights with unprecedented speed and ease. In a new modular left navigation, we’ve organized important use cases into workspaces that will guide you to the reports, analyses, or data — like advertising conversions — you’re looking for.
New workspaces in left navigation
The new Advertising Workspace is designed to quickly address everyday advertiser needs and unlock deeper insights into your campaign performance. In the snapshot, you can see relevant campaign and performance insights at a glance. You’ll get automated insights notifying you of things like performance spikes in your campaigns, where the majority of your customers are converting from, or what channel is performing the best that week.
With an intuitive and easily accessible home for these insights, you’ll be able to quickly improve campaign performance when you want to make real-time optimizations.
Advertising Workspace snapshot
Beyond easier navigation, it’s also important to be able to tailor Analytics to the specific needs of your business, and even your role. To allow flexibility, we’re launching an entirely new set of customization options to reporting.
For the first time, within the Reports Workspace, users with admin access will be able to curate the Analytics interface and reports to suit the specific needs of their teams. Admins can make simple edits to existing reports or even create entirely new custom reports. They can also customize the left navigation to group reports into collections, and create custom overviews to highlight information. You can showcase these overviews in the Reports snapshot, the new homepage for the Reports Workspace.
Custom reporting options
Once admins set up customized reporting preferences for your organization, you can reduce time spent on reporting and surface the most relevant insights faster than ever before.
We know how valuable it is to have attribution reporting for your campaigns directly within Analytics, so we’re bringing new cross-platform attribution capabilities into the Advertising Workspace.
Data-driven attribution models will soon be available in all Google Analytics 4 properties, so you can use Google’s machine learning to understand the contribution of each touchpoint in your marketing funnel, alongside your other customer journey insights. We’ve also introduced two new attribution reports: the Conversion Paths report and Model Comparison report.
Similar to Multi-Channel Funnels in Universal Analytics properties, the Conversion Paths report allows you to view the customer journey by channel, assigning credit to touchpoints from when your customers first arrive to your site or app through conversion, based on a selected attribution model. It also includes a new conversion credit visualization that helps you understand your ROI by channel.
Conversion Paths report in the Advertising Workspace
The Model Comparison report allows you to assess campaign performance using various attribution models, and compare how each affects the value of your marketing channels so you can determine which model best suits the needs of your business.
Model Comparison report in the Advertising Workspace
The new Google Analytics will help ensure your measurement foundation is reliable and ready to meet the demands of an evolving ecosystem.
Get started with Google Analytics 4 properties today, and stay tuned for more enhancements coming soon.
This July we announceda new property type in Google Analytics that helps you measure across both your app and website in one place. The new App + Web property helps you better understand your customers’ journeys across platforms so you can deliver more unified experiences.
Recently, we’ve introduced enhancements that allow you to measure multiple websites, do even more custom analysis, and get faster insights from your data.
App + Web properties now support multiple web streams, including Firebase web apps, in a single property—up to 50 data streams across your apps, websites, and web apps. This allows you to see metrics aggregated across all your related apps and websites, or apply filters to compare them individually. For example, if you were an online retailer with multiple regional stores, you could see your total global sales for the month or compare the sales of each of your regional sites and apps.
In July we introduced the Analysis module in App + Web properties with five techniques to do cross-platform analysis with more flexibility. Now, we’ve added two more techniques to the mix: cohort analysis and user lifetime, as well as an update to the existing pathing technique and a larger window for historical data. These capabilities will become available over the next few weeks.
Cohort analysis helps you compare engagement between groups of similar users with more metric and dimension breakdowns. For example, you can compare revenue between cohorts of users that were acquired at different times to understand the results of a change in your marketing strategy.
User lifetime gives you insight into the lifetime activity of a group of users, based on custom dimensions you choose. For example, see how many lifetime in-app purchases were made by users acquired from a holiday promotion you ran.
Backward pathing allows you to work backwards from a conversion or other key event and analyze the differences, trends, or patterns users took to get there. For example, you can start from a purchase event to see how many users that made a purchase entered the funnel from an email campaign to your website, compared to a search ad that deep-links to your app.
Data retention has now expanded to up to 14 months across all techniques within the Analysis module so you can conduct longer term analyses, like year-over-year. Go to data settings in your property admin to increase data retention.
Automated and custom insights, previously available only for web, are now in App + Web properties.
Automated insights use machine learning to identify key trends and anomalies in your data. For example, if there was an unusual spike in sales yesterday, you will get an alert of the change which you can then investigate. Automated insights get smarter and more relevant to your business over time.
Custom insights give you the control to tell Analytics what metrics you’d like to be alerted about. For example, if you are a retailer and you’ve just released a new product, you may want to track sales specifically for that SKU. You can set up a custom insight to alert you if the product’s sales increased by more than 10% week-over-week. These alerts can now be set up to run hourly, and you can receive email notifications within 5 minutes of a triggered alert.
When looking for specific insights in your Web properties you can simply ask a question in the search bar and get a quick answer. Today, we are extending this to App + Web properties, so you can ask questions and get holistic answers across your app and web data.
Ask questions using keywords, such as “users from organic channel last week,” and a relevant answer will appear in the search dropdown. Be specific about the metric, dimension, and time frame to get the best results.
Automated and custom insights, as well as instant answers from the search dropdown, are available in App + Web properties today in English and will soon be available in all languages supported by Google Analytics.
Businesses already see the benefits of bringing more of the customer journey into view. TUI group, a leading integrated tourism group based in Europe, is using App + Web properties to close the gap between their app and web data.
Previously we had been manually stitching together app and web sessions in order to generate customer behaviour insight and value our marketing investments; this release unifies that data to show the full path to conversion.
If you’re not already using the beta and your business is looking for a more complete view of how your customers engage across app and web, you can get started today by setting up a new property and linking your app and website.
This July we announceda new property type in Google Analytics that helps you measure across both your app and website in one place. The new App + Web property helps you better understand your customers’ journeys across platforms so you can deliver more unified experiences.
Recently, we’ve introduced enhancements that allow you to measure multiple websites, do even more custom analysis, and get faster insights from your data.
App + Web properties now support multiple web streams, including Firebase web apps, in a single property—up to 50 data streams across your apps, websites, and web apps. This allows you to see metrics aggregated across all your related apps and websites, or apply filters to compare them individually. For example, if you were an online retailer with multiple regional stores, you could see your total global sales for the month or compare the sales of each of your regional sites and apps.
In July we introduced the Analysis module in App + Web properties with five techniques to do cross-platform analysis with more flexibility. Now, we’ve added two more techniques to the mix: cohort analysis and user lifetime, as well as an update to the existing pathing technique and a larger window for historical data.
Cohort analysis helps you compare engagement between groups of similar users with more metric and dimension breakdowns. For example, you can compare revenue between cohorts of users that were acquired at different times to understand the results of a change in your marketing strategy.
User lifetime gives you insight into the lifetime activity of a group of users, based on custom dimensions you choose. For example, see how many lifetime in-app purchases were made by users acquired from a holiday promotion you ran.
Backward pathing allows you to work backwards from a conversion or other key event and analyze the differences, trends, or patterns users took to get there. For example, you can start from a purchase event to see how many users that made a purchase entered the funnel from an email campaign to your website, compared to a search ad that deep-links to your app.
Data retention has now expanded to up to 14 months across all techniques within the Analysis module so you can conduct longer term analyses, like year-over-year. Go to data settings in your property admin to increase data retention.
Automated and custom insights, previously available only for web, are now in App + Web properties.
Automated insights use machine learning to identify key trends and anomalies in your data. For example, if there was an unusual spike in sales yesterday, you will get an alert of the change which you can then investigate. Automated insights get smarter and more relevant to your business over time.
Custom insights give you the control to tell Analytics what metrics you’d like to be alerted about. For example, if you are a retailer and you’ve just released a new product, you may want to track sales specifically for that SKU. You can set up a custom insight to alert you if the product’s sales increased by more than 10% week-over-week. These alerts can now be set up to run hourly, and you can receive email notifications within 5 minutes of a triggered alert.
When looking for specific insights in your Web properties you can simply ask a question in the search bar and get a quick answer. Today, we are extending this to App + Web properties, so you can ask questions and get holistic answers across your app and web data.
Ask questions using keywords, such as “users from organic channel last week,” and a relevant answer will appear in the search dropdown. Be specific about the metric, dimension, and time frame to get the best results.
Automated and custom insights, as well as instant answers from the search dropdown, are available in App + Web properties today in English and will soon be available in all languages supported by Google Analytics.
Businesses already see the benefits of bringing more of the customer journey into view. TUI group, a leading integrated tourism group based in Europe, is using App + Web properties to close the gap between their app and web data.
Previously we had been manually stitching together app and web sessions in order to generate customer behaviour insight and value our marketing investments; this release unifies that data to show the full path to conversion.
If you’re not already using the beta and your business is looking for a more complete view of how your customers engage across app and web, you can get started today by setting up a new property and linking your app and website.
People expect to interact with businesses when and how they like, such as browsing a brand's website to research a product and then purchasing it later using the brand's app. Getting insight into these cross-platform journeys is critical for businesses to predict customer needs and provide great experiences—but it can be very challenging.
Currently, many businesses measure app engagement with Google Analytics for Firebase and website engagement with Google Analytics. While each of these products separately offer powerful insights, getting a more unified picture of engagement across your app and website can be a manual and painstaking process.
To make this simpler, we’re announcing a new way to measure apps and websites together for the first time in Google Analytics.
First, we’re introducing a new property type, App + Web, that allows you to combine app and web data for unified reporting and analysis.
Measure your app and website together in Google Analytics
Reports for this new property use a single set of consistent metrics and dimensions, making it possible to see integrated reporting across app and web like never before. Now you can answer questions like: Which marketing channel is responsible for acquiring the most new users across your different platforms? How many total unique users do you have, regardless of which platform they use? How many conversions have occurred on your app and website in the last week—and which platform is driving most of these conversions?
See combined metrics across your app and website
You can also go deeper to understand the effectiveness of your marketing campaigns across platforms. For example, you can see how many users started on your app then visited your website to make a purchase.
Understanding how people engage with your app and website means that you need to measure a diverse range of user interactions like clicks, page views, app opens, and more. We’re making it easier to measure those actions on all of your platforms in a consistent way. The new property type utilizes a more flexible event-based model for collecting the unique interactions that users have with your content, allowing you to measure any custom event that you set up.
This event-based model also allows you to automate the manual work of tagging some of the events on your site with no additional coding required. In addition to page views, enhanced measurement allows you to measure many common web events like scrolls, downloads, video views and more with the flip of a toggle in the admin settings for your property.
Enhanced measurement helps you measure events with the flip of a toggle
Given the many different ways people interact with your brand between app and web, you need flexible tools to make sense of your data and discover insights unique to your business. The new Analysis module enables you to examine your data in ways that are not limited by pre-defined reports.
There are a number of techniques you can use including:
Exploration: Conduct ad-hoc analysis by dragging and dropping multiple variables—the different segments, dimensions, and metrics you use to measure your business—onto a canvas to see instant visualizations of yourdata.
The Exploration technique allows you to visualize your data with drag and drop ease
Funnels: Identify important steps to conversion and understand how users navigate among them—where they enter the funnel, as well as where they drop off—with both open and closed funnel options.
Understand how users engage with a sequence of key events on your app and website using the Funnels technique
Path analysis: Understand the actions users take between the steps within a funnel to help explain why users did or did not convert.
Visualize actions taken on the users’ path to conversion with the Path analysis technique
Once you’ve surfaced insights from your analysis, you can use the results to create audiences and use those audiences to deliver more relevant marketing experiences to your customers.
The first version of this new app and web experience—including the new event model and new analysis capabilities—will be available to all Analytics and Analytics 360 accounts in beta in the coming weeks. If you use Google Tag Manager or the global site tag for Google Analytics today, there’s no re-tagging required for your website. To include your app data, you’ll need the Firebase SDK implemented in your app. See how to get started in Google Analytics, or if you’re an existing Firebase customer, here’s how to upgrade.
If your business has both an app and website, and is looking for a more complete view of how your customers engage across both, we encourage you to participate in this beta and share your feedback. We are working to make Google Analytics the best possible solution for helping you understand the customer journey and create great customer experiences across platforms. Your partnership is essential to help us get there.
