Why Google’s Predictive Audiences Feature Matters to Advertisers

Why Google’s Predictive Audiences Feature Matters to Advertisers

Analytics

Google Analytics 4 (GA4) is more than an upgrade to Universal Analytics (UA). GA4 is a whole new analytics solution available now. Businesses should switch from from Universal Analytics (UA) to GA4 now in order to capitalize on GA4’s many features such as Predictive Audiences in Google Ads campaigns. Predictive Audiences relies on artificial intelligence (AI) to drive better results than currently possible with UA.

What Is Predictive Audiences?

Predictive Audiences makes it possible to classify users who are likely to perform an action in the near future based on a predictive metric. For example, a business might build an audience for “likely 7-day purchasers” that includes users who are likely to make a purchase in the next 7 days; or “likely 7-day churning users” for purchasing users who are not likely to visit your website in the next 7 days, just to cite two examples.

Audience data

Predictive Audiences are automatically shared with any Google Ads accounts you have linked to your property.

AI is not new to Google Analytics. UA properties have Smart Lists, which are audiences Google automatically builds using machine learning. However, Smart Lists are much more limited than the new Predictive Audiences available in GA4. Whereas Smart Lists are not customizable by advertisers, Predictive Audiences can be built with custom traffic/activity filters, as well as a membership duration that is anywhere between 1 and 540 days.

What Are Some Applications of Predictive Audiences?

With Predictive Audiences, an advertiser can improve marketing campaigns to target users before they take an action, potentially increasing conversions. For instance:

  • As remarketing audiences. A shopper who is considering your product but not ready to become a customer is a hot lead. For example, someone who has added a product to a shopping cart but has not yet made a purchase might be ready to buy, but they also might be checking out the competition. It’s important that the merchant act on those leads – to strike while the iron is hot. GA4 uses machine learning to find deep patterns of behavior that are unique to your property and show that a user is likely to convert. A persuasive follow-up from you via a well-crafted remarketing campaign can provide that last nudge they need to complete the process.
  • In re-engagement campaigns. Shoppers who are likely to churn are signaling a waning interest in your business. But they have also previously demonstrated engagement with your business. Why give up on them? Predictive Audiences makes it possible to approach them again with reminders of the value you offer in terms of product variety, quality, and price, or convenient shipping and return options.

Analytics

Why Does Predictive Audiences Matter?

Predictive Audiences illustrates how Google is using machine learning to understand future actions of a user. This gives marketers more ways to reach potential customers and increase revenue. When a machine teaches itself with minimal programming needed, it can ingest vast sets of consumer data and use it to determine things such as the best times to send emails or to run an ad. Proponents say machine learning can identify the clients or customers that would be most receptive to given messages.

Google continues to invest in machine learning to make marketing more effective. However, we caution against simply automating advertising. Human judgment is needed to ensure that a marketing campaign is adaptable and flexible as the behavior of users changes.

How Does an Advertiser Get Started with Predictive Analytics?

Availability of Predictive Audiences depends on the underlying predictive metrics being eligible for use by meeting all prerequisites. If you have exported Predictive Audiences to linked product accounts, those audiences will not accumulate new users if the property becomes ineligible for the predictive metric and new predictions are not generated. Google shares more insight on how to use suggested audience templates to create your own audiences with conditions based on those predictions.

Getting started with Predictive Analytics is but one of many steps an advertiser will need take in order to make the transition to GA4. Don’t wait until July 2023 to get ready. Only by acting now will an advertiser prepare itself to capitalize on the new features available in GA4.

True Interactive can help you do that. Read more about GA4 in this blog post.

Contact True Interactive

To succeed with online advertising, contact True Interactive. We design and develop successful marketing and advertising campaigns and know how to track results, including the use of Google. Read about some of our client work here.

Photo by Hannah Wei on Unsplash

Google Analytics 4: Advertiser Q&A

Google Analytics 4: Advertiser Q&A

Google

If you use Google Analytics, by now you are probably aware that a new version known as Google Analytics 4 is coming. By July 2023, Google Analytics 4 will replace the current version of the popular web analytics service, known as Universal Analytics (UA). This news has sent shock waves throughout an ad tech world that has grown dependent on UA to track and report website traffic. Here are some questions you may have – and some answers:

What exactly is happening to Google Analytics?

UA – the current version of Google Analytics — is going away. UA will stop processing hits in July 2023. That’s because Google is replacing UA with Google Analytics 4 (GA4). If you want to continue using Google to track and report website traffic, you’ll need to transition to GA4. Google actually began to introduce GA4 in 2020, as noted in this blog post. But in July 2023, Google is making GA4 mandatory, as Google said in March 2022. While standard UA properties will stop working July 2023, Universal Analytics 360 properties will receive an additional three months of new hit processing, meaning these will stop working come October 1, 2023.

Why is Google Replacing Universal Analytics with Google Analytics 4?

Google says that GA4 is coming for three primary reasons:

  • Provide more user-centric data. UA is built on a session-based data model that is 15 years old. Google built UA to measure independent sessions, or groups of user interactions within a given time frame on a desktop device. This measurement approach has become obsolete. GA4 does not measure goals by user, only by session. For instance, if someone watches four videos in one session, the interaction can only count as one conversion. By collecting user data as events, GA4 seeks to provide businesses with more accurate insight into user activity.
  • Work across platforms. UA was built for a desktop experience. GA4 is designed to work across platforms, including mobile. According to Google, GA4 provides a complete view of the customer lifecycle with an event-based measurement model that isn’t fragmented by platform or organized into independent sessions. Google cites the example of UK-based fitness apparel and accessories brand Gymshark, which is already using an iteration of GA4 to measure user activity across its website and app. This allows the Gymshark team to better understand how users move through the purchase funnel. Google says that as a result, Gymshark has reduced user drop off by 9 percent, increased product page clickthroughs by 5 percent, and cut down their own time spent on user journey analysis by 30 percent.
  • Transition to a privacy-centric world. Google is under tremendous pressure to adapt to a world in which user privacy is a much bigger priority than it used to be when UA was introduced. GA4 does that. For instance, GA4 4 will also no longer store internet protocol (IP) addresses. GA4 also offers a workaround for when users reject cookies. UA works by setting cookies on a user’s browser when visiting your website. But more people are opting out of sharing their data via cookies. So, UA cannot report on all the people who visit a website. GA4 will rely on a technique known as conversion modeling to provide results in a cookie-less world. Conversion modeling uses machine learning (a form of artificial intelligence) to enable accurate measurement while only reporting on aggregated and anonymized data. GA4 will still collect data from first-party cookies, but conversion modeling makes it possible for GA4 to continue collecting user data when cookies are rejected by users.

In short, Google is changing website tracking and reporting to adapt to a more privacy-centric world in which people use multiple devices to interact with brands.

How does Google Analytics 4 differ from Universal Analytics?

GA4 is a replacement, not an update. It’s a completely new way of tracking and reporting website traffic. The key difference is the adoption of more user-centric data as discussed above. This post from the Google Help Center explains in more detail how the more user-centric data model differs from Universal Analytics. Don’t read it until you’ve had your morning coffee.

There are many other differences too numerous to describe here. For instance, with GA4, you can choose to retain data for two months or 14 months. And GA4 offers custom reporting templates (whereas UA favored the use of pre-built reports).

What will happen to Universal Analytics?

UA will go away. It will not be possible to track and report website traffic with UA as of July 2023 for standard accounts, and October 2023 for UA 360 accounts.

After UA properties stop processing new hits, all previously processed data will remain accessible for at least six months. In the coming months, Google will provide a future date for when existing Universal Analytics properties will no longer be available. After that date, users will no longer be able to see UA reports in the Google Analytics interface or access UA data via the API.

What should I do to prepare for Google Analytics 4?

If you rely on a marketing and advertising agency to manage GA4, it’s highly likely that they are managing the transition for you. Just the same, contact them to understand how they are going to make the transition and how your website tracking and reporting will change. True Interactive uses UA in our client work. We’re doing all the heavy lifting for our clients by transitioning them to GA4.

If you manage GA4 yourself, it’s important to start your transition now. Don’t wait until 2023. For example, right now you’ll need to start building historical data so that you can do a year-over-year analysis in 2023.

In addition, we recommend downloading historic data from your UA account and storing it for future reference before Google shuts off access to it via both the web interface and its reporting API as mentioned above.

Make no mistake: the learning curve is steep. You’ll need to understand how GA4 conducts event reports, conversion reports, and many other details. We recommend that businesses review resources such as:

It’s going to take an effort from an integrated team to pull this off. You’ll need to make this effort a high priority managed with a project timeline to get it right.

Contact True Interactive

To succeed with online advertising, contact True Interactive. We design and develop successful marketing and advertising campaigns and know how to track results, including the use of Google. Read about some of our client work here.

Advertisers, Watch Your Referrals

Advertisers, Watch Your Referrals

Google

At True Interactive, we use tools such as Google Analytics to monitor and measure everything we do. And doing so includes keeping close tabs on referral traffic. Referral traffic consists of visits that come to your site from sources outside of Google’s search engine. When someone clicks on a hyperlink to go to a new page on a different website, Google Analytics tracks the click as a referral visit to the second site. Referral traffic is a recommendation from one site to visit another — like an assist from one basketball or hockey player to another leading to a score.

Referral traffic helps you understand how people find your website. With good referral data, you can understand, for instance, whether your Facebook or Instagram pages are sending traffic to your site (and how much traffic).

But you need to keep a close watch on how Google Analytics measures referral traffic in order to get a true measure. Recently, for one of our clients, we noticed that Google Analytics was reporting a sharp increase in referral traffic from payment sites such as Affirm and Paypal. When we looked under the hood, we noticed that Google Analytics was giving those payment sites credit as the referring sites for customer transactions.

Now, payment sites are essential for a transaction to occur. They make the web more seamless by making online checkout happen faster. Customers making purchases on ecommerce sites probably don’t even notice when they’re referred to a third-party payment site to complete a purchase. But that doesn’t mean Affirm or Paypal should get credit as the referring site. Affirm ensures the purchase happens easily. But Affirm becomes part of the picture after a customer has decided to make a purchase, not before.

Fortunately, we monitor Google Analytics data closely. We acted quickly by adding the third-party payment sites in question to the referral exclusion list, or a list of domains whose incoming traffic is treated as direct traffic (instead of referral traffic) by Google Analytics. We were able to course-correct quickly enough to ensure that we continue to provide our clients accurate data.

The lessons here:

  • Watch your referral traffic closely.
  • If you find a spike in referrals for third-party payment sites, take a closer look at your referral exclusion list. The payment system might be getting an inordinate amount of credit that another site should be getting credit for.

How closely do you monitor your Google Analytics data?

Contact True Interactive

To succeed with online advertising in 2020, contact True Interactive. Read about some of our client work here.

Understanding How Retailers Can Use Analytics to Optimize Their Digital Marketing

Analytics Retail Analytics Spotlights

The-Marketing-ScopeIn 2016, global e-commerce sales are expected to eclipse $1.1 trillion, according to leading consulting firm A.T. Kearney, with annual growth of 15%-20%. When the money is that big, you can bet that competition for wallet share in digital marketing will be stiff.

A competitive advertising space can drive up costs rapidly, so retailers need to make sure they are using analytics fully to optimize their digital marketing campaigns. When you dive into any analytics package, even free ones such as Google Analytics, the options can get complicated and overwhelming quickly. However, understanding the basic key performance indicators (KPIs) and using them correctly can help you optimize your website and improve conversions, which in turn boosts your digital marketing ROI.

I sat down with Eric Vidal, Editor & Chief Content Officer of The Marketing Scope, to discuss “Why Digital Marketing Analytics Is Important for Retail Sales.” This video is part of the “Marketing Mash” series produced by Vidal. We talked about how to understand what you’re looking at when you open your analytics package then, more importantly, how to use the data to optimize your website and drive more conversions from your digital ads.

Best Practices in Applying Analytics to Digital Marketing Campaigns for Retail

Analytics Retail Analytics Spotlights

The-Marketing-ScopeThe retail industry depends heavily on digital marketing, and consequently, that makes online advertising very competitive. The online marketplace brings additional challenges that don’t exist in the brick-and-mortar world. Products, prices and even competitors change rapidly, sometimes by the minute.

To have any hope of achieving a positive return on advertising expenditures, online retailers must analyze what is working and what isn’t. While most digital marketers have an analytics program, such as Google Analytics, in place, more than half of them aren’t using analytics effectively.

These issues were the focus of a conversation I had with Eric Vidal, an Editor & Chief Content Officer, on this episode of “Marketing Mash,” a video series produced by The Marketing Scope. Watch the video, “Why Digital Marketing Analytics Is Important for Retail Sales,” to learn some best practices in applying analytics to digital marketing campaigns.

Prepping for the Digital Advertising Race

Analytics

RED INDY CAR 3For my last couple of posts, I’ve drawn parallels between the “The Greatest Spectacle in Racing” – the Indianapolis 500 – and the current state of digital advertising because recent changes to Google’s Search Engine Results Page (SERP) have made competing for space a more rigorous contest. And in the last installment, I advised digital marketers to keep in mind there is more than one competitor on the track.

Sure, Google has the pole position. But other racers, such as Bing or YouTube and social-media contestants Facebook and Instagram, also are worth evaluating. These online venues can still yield excellent results. So, we walked through the garage and kicked a few tires.

OK. Some of the alternative vehicles look pretty slick. But admiring their gleaming chassis in the garage isn’t the same as jumping behind the wheel, gunning the engine and burning rubber on the track.

So, here are a few pointers for running the race…

Different Vehicle, Same Race

Just because you’re slipping into a new cockpit doesn’t mean your overall objective has changed. You want to finish in a competitive position – generating as many quality clicks as possible. To cross that finish line, you need to be comfortable in your new seat, knowing what your vehicle can and can’t handle. In other words, know what to expect in terms of performance. Don’t figuratively slam the gas pedal before you have had a few test laps in your new ride.

In marketing speak, this means you should move to new vehicles incrementally. If you want to explore other channels, pick one for your experimentation, rather than blanketing Bing and YouTube and Instagram and Facebook all at once. The digital world gives you hard data very rapidly, so you can conduct a test and know within days or weeks if it works for you.

Are Car & Driver Up to Specs?

No one just rolls up on race day and enters the Indy 500 field. Racing teams must qualify for the event, demonstrating that their cars and drivers are up to the challenge. In marketing terms, when you think about where to extend your digital advertising, which new channels to try, always consider your goals and your target market. As noted in earlier posts, your product may or may not play well on Instagram, and your target may or may not be more likely to be a Bing user.

One Car Can Run Two Races at the Same Time

My Indy 500 analogy finally has run out of gas. Because digital advertising is not limited by the constraints of the physical world. We’ve seen many clients who set up Bing ad accounts and put 10-20% of their budget in them, then let them run on auto-pilot while tending to the 80-90% of their campaigns in Google. As they make refinements in their Google AdWords campaigns, they don’t go back and make the same adjustments in Bing. But Bing has made it very easy to import your Google campaigns and keywords directly into Bing. So, by carefully choosing your channels and managing your digital advertising strategy, you can effectively drive one vehicle and have it compete simultaneously in two races.

That’s a feat not even the best Indy 500 driver can accomplish.

Vetting Competitors in the Digital Advertising Race

Analytics

RED INDY STRAIGHTAWAY shutterstock_141403861In my last post, I drew parallels between the “The Greatest Spectacle in Racing” – the Indianapolis 500 – and the current state of digital advertising because recent changes to Google’s Search Engine Results Page (SERP) have made competing for space a more rigorous contest. And when faced with picking a winning strategy for this daunting challenge, digital marketers would be wise to remember there is more than one competitor on the track.

Yes, Google has earned the pole position. But it’s worthwhile considering other racers, such as Bing or YouTube and social-media contestants Facebook and Instagram. These online venues can still yield excellent results. By placing figurative bets on multiple vehicles, you can determine whether keeping all your money riding on Google is the most optimal strategy. Perhaps you should spread your digital advertising wagers across several “cars” in the race, which could yield a more dominant position in the field.

So, let’s kick a few tires…

Bing customers tend to be more educated and affluent. It’s the default search engine on Windows 10 devices, including the popular Microsoft Surface laptop/tablet hybrid, which are becoming standard issue in corporate suites. Bing’s share of the search market, while still much smaller than Google, is growing. It’s worth consideration, especially if the demographics of your target market align with Bing users, which are skewing toward businesses large and small.

If you want more eyeballs and increased branding at a relatively low cost, then YouTube is a solid option. After all, it is the second-largest search engine on the internet.

Depending on your product, Instagram might be a good option, too. Particularly for business-to-consumer marketers who have visually appealing products, we are seeing some strong results on Instagram. Flowers, landscape designers, foodies – these are strong plays on Instagram. However, if you are a B2B industrial machine supplier, Instagram is probably not the best venue for a share of your marketing budget.

Another avenue to explore down is remarketing campaigns on Facebook. Remarketing, if you’re not familiar with the term, is the ability to show an ad to someone who has previously visited your website or Facebook page. Since we know most consumers begin their purchasing decision process online, remarketing is an excellent way to reconnect with people who have already shown some interest in your company or product.

Facebook’s targeting options have improved dramatically, so you have many options for reaching people: standard demographics, of course, as well as tight geographic areas, interests, pages they have visited and liked. Especially useful to many advertisers are “lookalike” options – the ability to target people who share similar characteristics to a group you understand already, such as your current customer base.

Now that you’ve vetted the racers, it’s time to determine the best approach to race day. More on that topic in my next post.