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Tag: Analytics

A new way to unify app and website measurement in Google Analytics

April 10, 2021 No Comments

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.

Unified app and web 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?

User Overview

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.

Flexible event measurement

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

Enhanced measurement helps you measure events with the flip of a toggle

Cross-platform analysis

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

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 sequences of key events on your app and website using the Funnels technique

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

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. 

Start measuring across platforms

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.

Google Analytics Blog

A nonprofit finds volunteers with the new Google Analytics

March 25, 2021 No Comments

In the United States, almost half of our food supply is wasted. That’s enough to feed everyone who experiences food insecurity four times over. “In a lot of ways hunger is not a supply problem, it’s a distribution problem,” says Leah Lizarondo, cofounder and CEO of 412 Food Rescue, a Pittsburgh-based nonprofit organization seeking to close the gap between food surplus and food scarcity.

In order to successfully achieve their mission to reduce hunger by redirecting surplus food to people experiencing food insecurity, Leah and her team need to recruit volunteers to download the Food Rescue Hero app and complete a local food pickup and delivery, becoming what they call “Food Rescue Heroes.” As a growing nonprofit organization, 412 Food Rescue has limited resources, though, and relies on technology to save time and invest in the right places.

A cross-platform understanding of volunteers

Historically, measurement across 412 Food Rescue’s digital touchpoints had been a challenge for the nonprofit. Key data was siloed between their website and app, making it time intensive to get a complete understanding of how people were engaging with the organization online. With help from their digital analytics partner Bounteous, 412 Food Rescue turned to the new Google Analytics.

The new Google Analytics allows us to look at our data across platforms — web and app — to understand the full journey of our users. We’ve been able to cut our reporting time by 50%. Sara Swaney
Director of Advancement, 412 Food Rescue

With that time savings, the team at 412 Food Rescue has been able to improve their marketing and focus on engaging more volunteers in the community.

“In order to recruit more volunteers, we needed to know where people were learning about 412 Food Rescue,” Swaney says. With a view of user engagement across platforms and devices,  412 Food Rescue was able to easily discern where the majority of its volunteers discover the organization, and what their typical journey is to get started. The team was able to see that new users are most likely to accept a Food Rescue and become volunteers within 48 hours of downloading the app. As a result, they adjusted their social media campaigns to drive app downloads on Mondays and Tuesdays, when most Food Rescues are typically posted in the app. By facilitating Food Rescues that users can immediately act on upon downloading the app, 412 Food Rescue was able to improve the user journey and convert more users to volunteers.

Automated insights introduce a new set of learnings

With automated insights generated through machine learning, 412 Food Rescue has been able to save time analyzing data and spend more time taking action. They learned, for example, that there was a dip in volunteer engagement on weekends, an insight that had gone unnoticed. Because they had been proactively alerted to the change in Analytics, they were able to quickly respond by increasing their marketing efforts on weekends to boost engagement and address the demand for local deliveries on those days.

Greater impact despite limited resources

Even without a dedicated analytics team, 412 Food Rescue is able to easily get a deep understanding of their data and use it to shift their marketing strategy, grow their network of Food Rescue Heroes, and secure further investment to ultimately expand to more cities and achieve their mission to end food waste and hunger.

Get started with the new Google Analytics today.

Google Analytics Blog

New predictive capabilities in Google Analytics

March 20, 2021 No Comments

Google Analytics helps you measure the actions people take across your app and website. By applying Google’s machine learning models, Analytics can analyze your data and predict future actions people may take. Today we are introducing two new predictive metrics to App + Web properties. The first is Purchase Probability, which predicts the likelihood that users who have visited your app or site will purchase in the next seven days. And the second, Churn Probability, predicts how likely it is that recently active users will not visit your app or site in the next seven days. You can use these metrics to help drive growth for your business by reaching the people most likely to purchase and retaining the people who might not return to your app or site via Google Ads.

Reach predictive audiences in Google Ads

Analytics will now suggest new predictive audiences that you can create in the Audience Builder. For example, using Purchase Probability, we will suggest the audience “Likely 7-day purchasers” which includes users who are most likely to purchase in the next seven days. Or using Churn Probability, we will suggest the audience “Likely 7-day churning users” which includes active users who are not likely to visit your site or app in the next seven days.


In the Audience Builder, you can select from a set of suggested predictive audiences.

In the past, if you wanted to reach people most likely to purchase, you’d probably build an audience of people who had added products to their shopping carts but didn’t purchase. However, with this approach you might miss reaching people who never selected an item but are likely to purchase in the future. Predictive audiences automatically determine which customer actions on your app or site might lead to a purchase—helping you find more people who are likely to convert at scale.

Imagine you run a home improvement store and are trying to drive more digital sales this month. Analytics will now suggest an audience that includes everyone who is likely to purchase in the next seven days—on either your app or your site—and then you can reach them with a personalized message using Google Ads.

Or let’s say you’re an online publisher and want to maintain your average number of daily users. You can build an audience of users who are likely to not visit your app or site in the next seven days and then create a Google Ads campaign to encourage them to read one of your popular articles.

Analyze customer activity with predictive metrics

In addition to building audiences, you can also use predictive metrics to analyze your data with the Analysis module. For example, you can use the User Lifetime technique to identify which marketing campaign helped you acquire users with the highest Purchase Probability. With that information you may decide to reallocate more of your marketing budget towards that high potential campaign.

predictions2 (1).gif

View the Purchase Probability of users from various marketing campaigns.

You will soon be able to use predictive metrics in the App + Web properties beta to build audiences and help you determine how to optimize your marketing budget. In the coming weeks these metrics will become available in properties that have purchase events implemented or are automatically measuring in-app purchases once certain thresholds are met.

If you haven’t yet created an App + Web property, you can get started here. We recommend continuing to  use your existing Analytics properties alongside an App + Web property.

Google Analytics Blog

Analytics: What Sources are Stealing Your Paid Revenue Attribution?

March 20, 2021 No Comments

“Where should we attribute revenue?” We found that referral and affiliate websites were receiving revenue credit for paid-initiated traffic.

PPC Hero

Take control of how data is used in Google Analytics

March 19, 2021 No Comments

Rising consumer expectations and changing industry regulations have set higher standards for user privacy and data protection. This has led many businesses to revisit how they are managing data in their Google Analytics accounts. To help, Analytics provides businesses with a variety of features to control how their data is used. Here is an updated overview of controls in Analytics that govern how data is collected, stored, and used–all of which can be adjusted at any time.

Three ways businesses can manage data in Google Analytics:


Control the data settings in your account

You can access various settings in your Analytics account to control how you collect, retain, and share data.

Decide if you need to accept the Data Processing Terms.

The optional Data Processing Terms are meant for businesses affected by the European Economic Area General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and other similar regulations. You can review and accept the terms if needed in your Analytics account, under Account Settings.

Anonymize IP addresses for your Web property.

When you enable IP anonymization in your Web property, Analytics will anonymize the addresses as soon as technically feasible. This may be useful for you to comply with your company’s privacy policies or government regulations. For Apps properties and App + Web properties, IP anonymization is enabled by default.

Disable some or all data collection.

You also have the ability to partially or completely disable data collection for any of your Analytics properties. Chrome users have the ability to opt out from data collection using the Analytics opt-out Add-on.

Set the data retention period.

You can select how long user-level and event-level data is stored by Analytics, and whether new events can reset that time period. Once that amount of time has passed, the data will be scheduled for automatic deletion from your account and Google’s servers.

Select what data you share with your support team and Google.

The data sharing settings allow you to customize whether to share Analytics data with Google, including whether to allow Google technical support representatives and Google marketing specialists to access your account when you want support using the product or performance recommendations.

Review your Google signals setting.

The Google signals setting allows you to enable additional features in Analytics like remarketing, demographics and interests reports, and Cross Device reports. You can also further customize this setting to keep Google signals enabled for reporting while limiting or disabling advertising personalization.

Choose whether your data is used for ads personalization

Digital advertising helps you reach people online and drive conversions on your app and website. When you enable ads personalization in Analytics, for example by activating Google signals, you gain the ability to use your Analytics audiences to personalize your digital ads which can improve the performance of your campaigns. You can customize how your Analytics data is used for ads personalization.

Control ads personalization for your entire Analytics property.

You can choose to disable ads personalization for an entire property, which will cause all incoming events for that property to be marked as not for use in ads personalization. You can manage this in the property settings of your account.

Control ads personalization by geography.

If you need to set the ads personalization setting for your property at the geographic level, you now have the ability to enable or disable this setting by country. And in the United States, you can adjust the setting at the state level.

Blog-geo-ads-personalization 0723.png

Allow or disallow ads personalization by state in the United States

Control ads personalization by event type or user property.

In App + Web properties, you can adjust the ads personalization setting for a specific event type or user property. For example you can exclude specific events or user properties from being used to personalize ads and only use that data for measurement purposes.

Control ads personalization for an individual event or session.

You can also manage whether an individual event or session is used for ads personalization. For example, if you need to obtain consent before enabling the setting you can dynamically disable ads personalization at the beginning of the session and on each subsequent event until consent is obtained.

Independent of these ads personalization controls that Analytics offers to advertisers, users can control their own ads personalization setting for their Google account. Once they’ve turned off this setting, Google will no longer use information about them for ads personalization.

Remove data from Analytics

You can remove your data from Analytics for any reason and at any time. You can request the data to be deleted from the Analytics servers or delete information for a single user.

Request data to be deleted.

If you need to delete data from the Analytics servers, you can submit a request for its removal. There is a seven-day grace period starting from the time you make the request before Analytics will begin the deletion process. All administrators and users with edit permission for your account will be informed of your request and have the ability to cancel the request during the grace period. Similar functionality will be available in App + Web properties soon.

Delete data for individual users.

You are able to delete a single user’s data from your Analytics account. If you have edit permission for the account, you can do this through the User Explorer report in Web properties or the User Explorer technique in the Analysis module in App + Web properties. Data associated with this user will be removed from the report within 72 hours and then deleted from the Analytics servers in the next deletion process. Your reports based on previously aggregated data, for example user counts in the Audience Overview report, won’t be affected. If you need to delete data for multiple users, you can use the Analytics User Deletion API.

Delete a property.

If you have edit permission, you can delete a property from your Analytics account. Your property and all the reporting views in the property will be permanently deleted 35 days after being moved to the Trash Can. Once deleted, you are not able to retrieve any historical data or reinstate reports.

All of the above features are available to use right now. For more information, please visit the Help Center.

We hope that you found this overview of current controls helpful. Google Analytics is continuously investing in capabilities to ensure businesses can access durable, privacy-centric, and easy to use analytics that work with and without cookies or identifiers. Please stay tuned for more in the coming months.

Google Analytics Blog

Introducing the new Google Analytics

March 8, 2021 No Comments

Millions of businesses, large and small, rely on Google Analytics to understand customer preferences and create better experiences for them. With more commerce moving online and businesses under increased pressure to make every marketing dollar count, insights from digital analytics tools are even more critical.

But with major shifts in consumer behavior and privacy-driven changes to longtime industry standards, current approaches to analytics aren’t keeping pace. In a survey from Forrester Consulting, marketers said that improving their use of analytics is a top priority, and that existing solutions make it difficult to get a complete view of the customer and derive insights from their data.

To help you get better ROI from your marketing for the long term, we’re creating a new, more intelligent Google Analytics that builds on the foundation of the App + Web property we introduced in beta last year. It has machine learning at its core to automatically surface helpful insights and gives you a complete understanding of your customers across devices and platforms. It’s privacy-centric by design, so you can rely on Analytics even as industry changes like restrictions on cookies and identifiers create gaps in your data. The new Google Analytics will give you the essential insights you need to be ready for what’s next.

Smarter insights to improve your marketing decisions and get better ROI

By applying Google’s advanced machine learning models, the new Analytics can automatically alert you to significant trends in your data – like products seeing rising demand because of new customer needs. It even helps you anticipate future actions your customers may take. For example, it calculates churn probability so you can more efficiently invest in retaining customers at a time when marketing budgets are under pressure. We’re continuing to add new predictive metrics, like the potential revenue you could earn from a particular group of customers. This allows you to create audiences to reach higher value customers and run analyses to better understand why some customers are likely to spend more than others, so you can take action to improve your results.


Churn probability in the Analysis module

With new integrations across Google’s marketing products, it’s easy to use what you learn to improve the ROI of your marketing. A deeper integration with Google Ads, for example, lets you create audiences that can reach your customers with more relevant, helpful experiences, wherever they choose to engage with your business.

The new approach also makes it possible to address longtime advertiser requests. Because the new Analytics can measure app and web interactions together, it can include conversions from YouTube engaged views that occur in-app and on the web in reports. Seeing conversions from YouTube video views alongside conversions from Google and non-Google paid channels, and organic channels like Google Search, social, and email, helps you understand the combined impact of all your marketing efforts.

Google_Analytics_YouTube_EVC_report (2).png

YouTube Engaged-view conversions in Analytics reports

Businesses taking part in the beta are already seeing benefits. Vistaprint, responding to rapid changes in their business at the start of the pandemic, was able to quickly measure and understand the customer response to their new line of protective masks. And Jeff Kacmarek, Vice President of Domino’s Pizza of Canada, found that “linking the new Google Analytics to Google Ads enables us to optimize around the actions that matter most to our customers, regardless of how they interact with our brand.”

A more complete understanding of how customers interact with your business

The new Analytics gives you customer-centric measurement, instead of measurement fragmented by device or by platform. It uses multiple identity spaces, including marketer-provided User IDs and unique Google signals from users opted into ads personalization, to give you a more complete view of how your customers interact with your business. For example, you can see if customers first discover your business from an ad on the web, then later install your app and make purchases there.

You’ll also get a better understanding of your customers across their entire lifecycle, from acquisition to conversion and retention. This is critical when people’s needs are rapidly changing and you have to make real-time decisions in order to win – and keep – new customers. Based on your feedback, we simplified and re-organized reporting so you can intuitively find marketing insights based on the part of the customer journey you’re interested in. For example, you can see what channels are driving new customers in the user acquisition report, then use the engagement and retention reports to understand the actions these customers take, and whether they stick around, after converting.


New reporting structure organized by the user lifecycle

Built for the long term

Now is the time to invest in your digital marketing basics, like smarter analytics, so you can be ready for what comes next. This will also help you respond to rising consumer expectations, regulatory developments, and changing technology standards for user privacy. With a new approach todata controls, you can better manage how you collect, retain and use your Analytics data. More granular controls for ads personalization let you choose when to use your data to optimize your ads and when to limit your data use to measurement. And of course, we continue to offer users control over sharing their activity with Google Analytics.

Because the technology landscape continues to evolve, the new Analytics is designed to adapt to a future with or without cookies or identifiers. It uses a flexible approach to measurement, and in the future, will include modeling to fill in the gaps where the data may be incomplete. This means that you can rely on Google Analytics to help you measure your marketing results and meet customer needs now as you navigate the recovery and as you face uncertainty in the future.

The future of Google Analytics

The new Google Analytics is now the default experience for new properties and is where we’re investing in future improvements. We know there are capabilities many marketers need before fully replacing their existing Analytics setup, so we encourage you to create a new Google Analytics 4 property (previously called an App + Web property) alongside your existing properties. This will allow you to start gathering data and benefit from the latest innovations as they become available while keeping your current implementation intact. If you’re an enterprise marketer, we’re currently in beta with an Analytics 360 version that will offer SLAs and advanced integrations with tools like BigQuery, and will have more to share soon.

Google Analytics Blog

Access Google Surveys and Google Analytics 4 data in Data Studio

March 7, 2021 No Comments

Today, Data Studio users can access over 300 data sets in just a couple clicks. From Google Ads to BigQuery to your CRM data, you can spend more time finding and sharing insights and less time configuring data sources. With two brand new data connectors you can access even more data through Data Studio to help you analyze your marketing investments and make decisions. You can now access your market research data with our new Google Surveys connector and connect to the next generation of Google Analytics with support for Google Analytics 4 properties. 

Google Surveys give you a quick, cost-effective way to get valuable insights into the minds of your target audience. Gather the insights you need to make smarter, faster business decisions—in a fraction of the time it takes for traditional market research. With the new Data Studio integration, you can quickly visualize your Surveys data alongside your marketing data from sources like Google Ads and Google Analytics.

Google Surveys report in Data Studio

Google Surveys report in Data Studio 

We’ve made it easy to visualize your Google Surveys data. Simply click “View report in Data Studio” when you’re in Google Surveys to see your survey data in a template that you can customize and share in a couple clicks.

View your report in Data Studio in one click

View your report in Data Studio in one click

In addition to expanding access to Google Surveys, we’re also excited to announce support for Google Analytics 4 properties. You can now connect to your Google Analytics 4 properties in Data Studio along with your Universal Analytics properties.

Google Analytics 4 report in Data Studio

Google Analytics 4 report in Data Studio

Accessing the data you need to make better decisions is only the first step. Finding insights from the data and determining the best way to communicate the insights to stakeholders can be challenging and time consuming. We’re making it easier to get started with new marketing templates across common data sets like Google Ads, Search Ads 360 and more. You can find over 30 solutions to help you get started in the Data Studio gallery.

New Google Ads performance report in Data Studio solution gallery

New Google Ads performance report in Data Studio solution gallery

We are excited to hear how these new data connections and template solutions help you find insights and make decisions. Drop us a line in our community forum to let us know what’s working well and what you’re excited for next. 

Google Analytics Blog

What affiliate marketers have missed about Google Analytics

January 6, 2021 No Comments

30-second summary:

  • Affiliate marketers can use Google Analytics to do the following – Google Event Tracking to monitor on-site engagements, Google Dashboards for analyzing user behavior, and build custom Audiences for improving audience retargeting.
  • As an affiliate marketer, Google Analytics does not provide you with off-site tracking, so you can’t see what actions a person performs on a merchant site after leaving your website.
  • With server-side tracking and Google Analytics, you can monitor an entire affiliate funnel through one platform. Advantages include the ability to create lookalike audiences based on people who made a purchase, run improved retargeting campaigns, and export lookalike data across multiple ad platforms.

Google Analytics is a powerful tool that provides valuable insights for anyone managing a website. In this article, I will discuss how to use Google Analytics for your affiliate marketing campaigns. I will then show you how to use third-party tools to provide you with additional insights to generate more revenue from your existing traffic and make better use of your ad budget.

How marketers currently use Google Analytics for affiliate tracking

If you are using Pay Per Click (PPC) ads as your primary customer acquisition channel, your profit margins are directly tied to ad costs. Any edge you gain that improves your ROAS will provide you with a competitive advantage in the ad auction.

There are three primary levers of a PPC campaign, the ad copy, the audience targeting, and the landing page experience. The insights you gain through Google Analytics can help you improve audience targeting and the landing page experience.

PPC and how marketers use Google Analytics for tracking affiliate marketing

Google Event Tracking allows you to track outbound clicks on affiliate links. Once set up, the dashboard is accessible through Behavior > Events. If you know the average conversion rate for a product, you can assign each click a value by setting up Goal Values.

Google Analytics - Event tracking

You then need to make modifications to the GA tracking code or add a special configuration to your GTM tag. This article covers event tracking in more detail.

With Google Event Tracking, you can monitor your assumed profit margins for a campaign through Google Analytics. Of course, these figures are far from accurate.

When implemented effectively, Goal Values provide you with a theoretical model for predicting your campaign’s profitability. However, it does not reflect your actual sales. To access this data, you need to log in to your affiliate dashboard, check the sales, and see if the predicted profit margins align with the real results. Moreover, affiliate platforms provide differing levels of insights. That means you might only get a “gross sale value” that covers sales from all traffic, as opposed to traffic from one website.

The second thing most affiliate marketers will do is review the information provided through Google Analytics dashboards to monitor what people are doing on their landing pages. For example, you might monitor how far down a page people scroll, how much time they spend on the page, the bounce rate, and more. You can also see the number of affiliate link outbound clicks.

You can run A/B tests and other experiments to check how your actions impact the CTR to affiliate links. You can adjust the position of affiliate links and the placement of the products you are promoting to improve CTR.

Insights gained from Google Analytics provide you with essential data to test your assumptions. You can use this data to improve the landing page experience and boost your CTR.

Any improvements you make to the landing page experience can and should improve your ROAS.

The final thing you can do is use Google Analytics to improve your initial targeting. If you are tracking who clicked on the affiliate link, you can create a refined lookalike audience for Google AdWords through Google Analytics. The following guide discusses audience targeting and Similar Audiences.

Any improvement to your targeting will give you an edge in the ad auction.

What are the limitations of Google Analytics for affiliate tracking?

Google Analytics is a powerful tool for monitoring the on-site activities of your visitors. As a business owner that controls an entire funnel, you can place your Google Analytics tag across your site, including the checkout page where the transaction actually takes place. Therefore, Google Analytics provides you with all the data you might conceivably need to monitor and optimize a funnel.

Rather than relying on assumed transaction values, you can monitor everything through one or more Google Analytics dashboards. Unfortunately, as an affiliate marketer, since you can’t place your GA tag on the merchant “thank you” page, Google Analytics fails to provide you with these insights. You are forced to jump between your affiliate programs, the ads platform, and Google Analytics to monitor how your PPC campaigns are performing. 

I discussed why you couldn’t use GA Event Tracking for the final stages of an affiliate funnel. It is an inconvenience that prevents the real attribution of transactions to an ad click. 

This issue impacts your marketing at two crucial levels, which will inevitably increase your Cost Per Acquisition (CPA) and your ability to automate your campaign targeting and optimization:

  1. Your entire audience is blended into general “buckets,” which prevents you from displaying relevant ads according to the users’ positions in the funnel.
  2. You can’t build lookalike audiences of your best possible “customers” because you don’t know who’s done what. 

While these two factors will undoubtedly reduce your profit margins, they will also undermine your long-term business objectives and ability to compete on the ad auction.

The final inconvenience you’ll face is that you can’t share custom audiences generated through Google Analytics across other ad platforms. To be fair, Google Analytics was never designed to provide off-site analytics tracking. However, as an affiliate marketer, enriching your Google Analytics data with off-site conversion data can bring a lot of value to your business. I’ll discuss how off-site tracking works in the next section.

How offline conversion tracking works

Offline conversion tracking ties actions taken by users on your site and actions taken on sites or systems outside the reach of the initial site’s Google Analytics tag. The most common methods for implementing off-site analytics tracking are through server-side tracking API (also known as postback tracking) and manual data / CSV upload.

Out of the two options, JavaScript tracking is the simplest method to implement. However, strict browser privacy settings and AdBlocks have made this method increasingly unreliable. Moreover, with JavaScript, there are further restrictions like browser memory, shortened cookie runtimes, and denial of access to session storage.

Offline conversion tracking model

With server-side tracking, unique click ID data is passed during the outbound click and is then sent back via a server-side URL. The unique click ID value is the common denominator that links a click from your website to actions on a separate site.

The data flow is managed through a postback URL. In the following blog post, I share technical information about how postback URLs work and why they’re important.

The main benefit of server side tracking is that it is not affected by ad blockers, ITP, ETP.

As an affiliate marketer, off-site marketing analytics provides you with a complete overview of your marketing funnel. You can track an off-site purchase. With this data, you get the same insights and advantages as a business where the end sale is made on their site.

An additional advantage of off-site tracking is that you can sync conversion data across multiple channels/ platforms and then use this data to create custom audiences. You can, therefore, test your marketing funnel utilizing cheaper traffic sources, then use the data to build lookalike audiences for ads on Facebook or Google, for example.

Unfortunately, not all ad platforms support off-site tracking. Google introduced off-site tracking in 2013. Bing Ads introduced the service in 2017, while social media platforms such as Twitter and TikTok have yet to provide a suitable solution for affiliate marketers.

Solutions for offsite tracking

Offsite tracking has multiple advantages for people operating in the affiliate marketing niche. That’s not to say that it’s not without problems. You need a lot of technical knowledge to set up a system to connect data from a browser to the server-side.

Google Analytics provides an extensive API that enables developers to implement server-side tracking. There are three primary methods for implementing off-site tracking:

  1. Google Analytics API: Requires the highest level of development skills. However, the Google Analytics API provides programmers with the best potential for complete server-side tracking.
  2. Google Tag Manager: A High level of technical skills. Google Tag Manager will only allow you to effectively track off-site actions if you can add Google Tags to the merchant’s site.
  3. Third-Party Affiliate Tracking Software: Plug & play solutions that connect Google Analytics and other Ads marketplaces (Bing, Facebook, and other platforms).

Due to the ever-evolving data and analytics space, developing and keeping up with the constant changes requires a significant investment of time and resources. Large companies might choose to invest in a custom in-house solution for off-site tracking. However, solutions that utilize the Google Analytics API are too expensive for most affiliate marketers.

Affiliate tracking software like, a company that I founded, provides a native server-side tracking integration with Google Analytics, Bing Ads, and other ad networks. It’s certainly a lot easier than hiring a developer to create a custom solution.

On balance, regardless of your approach, the limitations of offsite tracking are outweighed by the sizable benefits. That is, assuming you want to optimize your marketing funnel and increase your ROAS.

Integrating Google Analytics With Offsite Tracking

Implementing Google Analytics with offsite tracking software like is straightforward. Google Analytics already provides the standard dashboards for tracking visitor flow across a site from landing page to conversion.

When you integrate offsite tracking, you are, fundamentally, just gaining the same type of data as someone who manages an entire funnel across a single site would see. The benefit is that you get access to data you can use to improve your ROAS.

Case Study

One of our clients,, has six websites in the pet care industry. Most of the traffic to their sites comes from organic search. They were facing a data challenge that you may be familiar with; they found it difficult to understand what products were converting and from which pages those conversions were occurring.

In addition, PPC ads were more expensive than needed. For example, they were running retargeting ads to people who had purchased an affiliate product suggesting they make a purchase. With better data, they could improve ROAS.

Using, Cliverse could finally see from what page, and which link on a page was generating the conversions. Through analyzing the data, Cliverse was able to increase revenue by 30% thanks to page optimization. Because they have the complete picture, they are now able to run paid media campaigns to their site with full confidence.


Bridging the gap between your google analytics data and affiliate network conversions is the optimal way to improve your position at the ad auction. With a full overview of your affiliate funnel, you gain actionable insights on what triggers conversions and generates sales. It’s a vital edge that can help improve your ROAS.

In this guide, I showed you three ways to use Google Analytics as an affiliate marketer. You can use Google Event Tracking to monitor people who click on your affiliate links. With Goal Values set up, you can track your campaigns’ probable results. Moreover, you can run retargeting campaigns and create Custom Audiences for future ad campaigns.

Through the Google Analytics dashboards, you can gain insights into your site visitors’ actions. You can use these insights to validate the assumptions you make when running conversion optimization tests.

While Google Analytics is a powerful tool, you can’t see what actions people take when they leave your site. If you integrate off-site tracking, you get access to this data. Most third-party tools, such as the one we created, allow you to use Google Analytics to get a complete overview of your affiliate marketing funnel.

As an affiliate marketer, off-site tracking combined with Google Analytics provides you with valuable insights that can help you improve your ROAS. Follow the steps shared in this guide to see the results for yourself.

Laurent Malka is Co-founder of, a plug & play conversion tracking platform. He can be found on Twitter @laurent_malka.

The post What affiliate marketers have missed about Google Analytics appeared first on Search Engine Watch.

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Seven underrated Google Analytics features that boost performance

December 20, 2020 No Comments

30-second summary:

  • Google Analytics is an important web analytics tool from Google used in digital marketing.
  • Many digital marketers and website owners use it to track and measure the performance of their websites.
  • There are a lot of Google Analytics features that perform different functions. All working towards helping you get the best of your website.
  • However, there are some Google Analytics features that are underrated. Many digital marketers don’t recognize them and what they are capable of doing to improve the performance of their website.
  • This piece will highlight seven of them and how they can be helpful to you.

Google Analytics is a web analytics product from Google that has helped a lot of digital marketers and website owners ascertain the performance of their website. Approximately 29 million websites use it as an analytics tool. A lot of Google Analytics features are only known to a few digital marketers. Many people rush to it to check how page views they got over a period of time or how many conversations they got. To these people, that’s only what this great tool can for them – the basics. But it’s far beyond that.

There are some features it has which can help improve the performance of your website but are underrated.

Are you hearing this for the first time? Don’t worry that’s why I’m here and this piece will discuss seven of them and how they can be helpful to your site.

1. Custom alert

This Google Analytics feature can be located when you log into your report and tap on the ‘customization’ drop-down menu. When set up, you will be alerted through emails when there is a change in your traffic or behavior of your website.

This could be on a daily, weekly, or monthly basis. For a beginner who is curious to grow his traffic or conversion, it is simple to keep your eye on it. Another crucial function of a custom alert is to automatically notify you of trends in your data.

This could be tracking and informing you in real-time about the events on your website be it positive or negative. The advantage here is that you can fix any negative development before it becomes obvious. You can follow the screenshot below to set up your custom alert. 

Google Analytics features - Custom alerts

2. Channel groupings

It’s easy to manage the traffic source to your website with channel groupings feature. This feature is on default on your analytics report and it organizes and groups your common source of traffic. 

For instance, you launched an ad campaign on Facebook, and Instagram as social media tactics to grow your small business,  the channels grouping will allow you to compare and analyze the performance of each of the traffic channels.

 For a marketer to want to be more specific with his traffic channel, you can create custom channels grouping and apply it to your report.

 Its effect will be seen in how your data display but won’t change the data itself. To make use of channels grouping on your GA, when you sign in to your report and locate admin at the bottom left. Click on it and you will list of features which channel groupings are one of.

Google Analytics features - Channel groupings

3. Behavior flow

When users visit your website, they move from one page or event to another in an attempt to achieve their desire which may be to get help through your content. It is a visual representation that can help you understand how your audience interacts with your site, the content they enjoy, and the ones that turn them off.

 The behavior flow of your site simply displays the node, the connections to pages on your website, and exit. After consuming your content, do your audiences click on another link to learn more? Or do they bounce because they aren’t satisfied? 

This increases your bounce rate and a clear indication that you need to work on that particular content. Below is a screenshot of the behavior flow from my blog.

Google Analytics features - Behavioral flow

4. Ecommerce tracking

For those who want to start an ecommerce business or those already in the field. Tracking the performance of your ecommerce website is possible with ecommerce tracking feature on GA. 

As a merchant who sells on Shopify or BigCommerce, you’ll want to know where your high-paying customers come from, how they interact with the products you have in your store, and which product converts more.

 With the knowledge of this, you can identify the location of customers that make you smile when you remember the number of sales you have made, the products they like, and things to fix to continue to be ahead of your competitors. 

channel groupings

Below is how to set up ecommerce  tracking on GA

  • Sign in to your report on GA
  • Click on Admin on the bottom left and you will be in a new window
  • Click on ecommerce  settings
  • Enable ecommerce  
  • Enable enhanced ecommerce  reporting and save
  • The final step is to set up your tracking code. Learn how to do it here.

Once your ecommerce site is being tracked on GA, you will gain insight into the following metrics on your dashboard; unique purchases, revenue, quantity, conversion rate, average order revenue, etc.

5. Demographic

Some digital marketers don’t know the importance of analyzing the demography of users who visit their websites.  Age, sex, and interest category of your audience are key metrics that should matter to you. 

You can use them to make decisions that can improve the performance of your website. Take, for instance, you run a small business website on women’s clothing, and your demography metrics show that 80% of your visitors in the last month were male within the age range of 18 and 24.

That’s a red flag that you’re targeting the wrong audience. A female clothing line business should have more female visitors. Also, the age range of 18 and 24 are mostly young people who are either schooling or unemployment. Hence won’t have much money to spend on clothes. Below is how you can locate the demographic metrics in your GA.


6. Site speed report

Speed is one of the key factors Google considers when ranking your website. It even became more obvious with the introduction of Accelerated Mobile Page, AMP. Not paying attention to this one of the SEO mistakes you make. Google Analytics tracks the load time of your web pages.

The aim is to give you reasons to learn how to improve the speed of your website. A web page that loads slowly is a turn off for your audiences. Nobody wants to wait for a long time for a page to load when there are many web pages competing for their attention.

 It can increase the bounce rate of your website or even cost you sales if you sell online. Site speed is an indicator of a healthy site, hence the need to learn how to make it happen.

Google Analytics features - Site speed report

7. UTM parameters

To some digital marketers and small businesses, this might be the first time of hearing this marketing acronym. Don’t be confused, UTM simply stands for Urchin Tracking Modules. They are codes you add at the end of your URL. This is crucial if you run ad campaigns for your business. 

For example, if you run an ad campaign on Instagram, Facebook, and LinkedIn and made a lot of sales, you won’t know which of the social media platforms drove more sales to you. 

The only way to know that is if you add campaign parameters to your URLs which is tracked on GA. For every user who clicked on the URL, the parameter is sent to Google  Analytics. The goal is to identify the platform in which the campaign performed better and intensify your strategy on it to make more sales next time. 

Google Analytics features - UTM parameters

Wrapping up

The performance of your website should be of utmost importance to you as a digital marketer,  small business or someone who earns passive income online. Google Analytics has all it takes to keep your site healthy all the time. 

Google Analytics features factored in all aspects of your website be it blog, ecommerce, or any other kind of website.

Yours is to take your time to identify these features, explore them, make use of them and you will be surprised at how they can keep your website at its best all the time.

Chuks Chukwuemeka is a content creator, blogger, digital marketer, and founder of, an online business blog.

The post Seven underrated Google Analytics features that boost performance appeared first on Search Engine Watch.

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Why Google Ads and Google Analytics Convs. Don’t Align (And Why You Should Try The Attribution Beta)

September 11, 2020 No Comments

In this blog, one PPC expert walks through Google Ads and Analytics conv. discrepancy scenarios and how the Google Attribution beta (within GA) can help.

PPC Hero

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