Google Launches New Video Campaign Types

Google Launches New Video Campaign Types

by Héctor Ariza Google YouTube

Nine out of 10 marketers use video as a marketing tool – an all-time high, according to HubSpot. Ninety six percent of marketers  — more than at any point in the past nine years — told HubSpot they see video as an “important part” of their marketing strategy. So it’s no surprise that Google continues to roll out new tools to help marketers capitalize on video advertising.

At Google’s May 23 Marketing Live event, the company launched new ad products intended to capitalize on video:

Video View Campaigns

The main goal of Video View Campaigns is to drive as many views as possible at the lowest cost per view (CPV). Google suggests that these campaigns can potentially increase views by an estimated 40 percent in comparison to the conventional skippable in-stream cost-per-view campaigns. This is achieved by integrating different ad formats, including skippable in-stream ads, in-feed ads, and Shorts ads, and letting Google-powered AI dynamically optimize where the ads are served. This new campaign type sounds ideal for advertisers looking to maximize views by running different ad formats (on different YouTube placements) under a single campaign, instead of splitting creatives by ad format into multiple campaigns. The global launch of the Video Views Campaigns beta is scheduled for the coming month. Ultimately, Google hopes to offer advertisers a broader range of alternatives for connecting with their target audience.

Demand Generation Campaigns

Demand Generation Campaigns are crafted to use AI to engage consumers and motivate them to take action. These campaigns will run on different platforms, such as YouTube Shorts, YouTube in-stream, YouTube in-feed, Discover, and Gmail placements. In contrast to the prior lead form ads, the call to action for these campaigns will direct users to the advertiser’s website, which (says Google) should facilitate simpler conversion tracking.

A noteworthy aspect of Demand Generation Campaigns is the development of lookalike segments based on seed lists. These lists may include first-party data and YouTube users, enabling enhanced targeting through the implementation of lookalike segment settings: narrow (2.5 percent reach), balanced (5 percent reach), and broad (10 percent reach). Ad creatives can be specifically designed for these lookalike segments – which, in theory, should improve the chances that the ads resonate with target audiences.

The development of lookalike segments based on seed lists is a departure from Google’s recent announcement regarding the phaseout of Similar Audiences. When Google first announced the sunsetting of Similar Audiences back in November 2022, Google mentioned that “similar audiences will be transitioned to more durable solutions.” At the time, it appeared as though Google was referring to audience expansion and optimized targeting, which are simple toggles an advertiser can enable or disable for any given audience to have Google find more users that either look like an advertiser’s target segments or are likely to convert. That said, it’s possible that Google is restricting the capabilities of Similar Audiences as we know them by removing them from an advertiser’s view, and reintroducing a more restricted version of these calling them Lookalike Audiences just as we are seeing for Demand Generation Campaigns.

While we were able to create Similar Audiences off rule-based segments such as visitors of “/shop/collections/jackets,” the new Lookalike Audiences seem to only allow the use of first-party or YouTube audiences for their creation. I am curious to see if Google makes Lookalike Audiences available for other campaign types in the near future, or if it still limits their use to Demand Generation video campaigns.

What Advertisers Should Do

We urge advertisers to take an even-handed, critical approach with these new products. Google plays up benefits, but with the benefits come some caveats. As I blogged recently, Google’s ad products have lately been launching without giving advertisers adequate control and visibility into performance so we can clearly see what is working and what is not and adjust our strategy accordingly. This is not to say Google is releasing bad products – but they should provide more visibility and control rather than take a “Just trust Google – we know what we are doing” stance.

At True Interactive, we advocate on behalf of our clients. We are monitoring these developments closely. Contact us to learn how we can help you succeed in all forms of digital advertising.

Image source: https://unsplash.com/photos/8LfE0Lywyak

 

How Google Is Transforming Advertising with AI

How Google Is Transforming Advertising with AI

by Héctor Ariza Artificial Intelligence Google

The Big Tech firms continue to change the online advertising landscape with AI. For example, on May 23 at Google’s Marketing Live event, Google announced new ways that the company is incorporating AI into advertising online. Google has been integrating AI into advertising for quite some time, as we have blogged. Google’s latest announcements make AI an essential tool now for any advertiser that works with Google. Here are some highlights:

Simplifying Campaign Management through Conversational Interfaces

Google said that it is introducing a new, natural-language conversational experience within Google Ads. This feature is designed to streamline the process of creating campaigns and to simplify the management of search ads.

The feature works this way: an advertiser adds a preferred landing page from your website, and Google AI summarizes its content. From there, Google will generate a range of (presumably more relevant) elements for your campaign, including keywords, headlines, descriptions, images, and other assets. Before deploying the generated suggestions, you have the flexibility to review and make edits. And, you can engage in a conversation with Google AI to enhance your campaign’s performance.

In the near future, Google says it will enhance automatically created assets (ACA) for search ads, which use existing ad content and landing pages to generate headlines and descriptions.

ACA also applies generative AI to create and adapt search ads more effectively based on the specific context of a query. For instance, let’s say a user searches for “skin care for dry sensitive skin.” With the assistance of AI, Google can analyze the content from your landing page and existing ads to generate a headline that aligns even more closely with the user’s query, such as “Soothe Your Dry, Sensitive Skin.” Google says this approach improves the relevance of your ads while staying true to your brand identity.

Helping Advertisers with Performance Max

Performance Max is a goal-based campaign type that allows performance advertisers to access all of their Google Ads inventory from a single campaign. According to Google, advertisers who use Performance Max have experienced an average increase of over 18 percent in conversions, all while maintaining a similar cost per action. However, it must be noted that at True Interactive, we’ve not witnessed these kinds of returns with Performance Max and remain very cautious about its value. That said, to improve the capabilities of Performance Max, Google is introducing generative AI technology. Google says that this addition will make it easier for advertisers to create customized assets and expand their reach with just a few clicks. Google AI will learn about your brand and populate your campaign with relevant text and other assets. Moreover, Google will suggest unique and tailored images exclusively generated for your brand.

This feature will also be integrated into the new conversational experience within Google Ads.

Introducing Enhanced Ad Experiences through Generative AI

During Google’s recent conference for developers (Google I/O – which is separate from its May 23 marketing event), Google unveiled new capabilities in generative AI that will promise to change search. This feature, known as search generative experience (SGE), uses generative AI to share answers to queries in the form of complete “snapshots” of content instead of providing a few rich snippets and links to websites for more information. Search can unfold as a series of questions and follow-up questions that the searcher refines (similar to ChatGPT prompt).

Earlier, Google had demonstrated how ads would appear both above and below this immersive new experience. On May 23, Google said it will conduct extensive experimentation to integrate search and shopping ads into the AI-powered snapshot and conversational mode. Additionally, Google will explore ad formats native to SGE, using generative AI to create relevant and high-quality ads tailored to every step of the user’s search journey (although how well Google will do this remains to be seen).

For instance, let’s consider a scenario where someone is searching for “outdoor activities to do in Maui” and then further narrows down their search to include “activities for kids” and ‘surfing.” In this case, they may encounter a fully personalized ad from a travel brand promoting surfing lessons specifically designed for children.

When search ads are displayed, they will include ad labels, with the “Sponsored” label presented in bold black text. This ensures a clear distinction between ads and organic search results, prioritizing a user-centric approach.

Three Implications for Advertisers

We advise advertisers to embrace AI (there really is no choice now – Google is bringing AI to your ad campaigns whether you like it or not). But do so carefully.

1. We Need Visibility and Control

Given that this year’s event was focused on artificial intelligence and automation (as expected), I would argue that both things empower advertisers to deliver incremental results, yet we need to have at least some degree of control over these, and more importantly, we need visibility into performance so we can clearly see what is working and what is not (they shouldn’t be mutually exclusive) and adjust our strategy accordingly.

2. Be Careful with ACA

I mentioned earlier that Google is enhancing automatically created assets (ACA) for search ads, which use existing ad content and landing pages to generate headlines and descriptions.

Incorporating generative AI into ACAs can potentially improve the relevance of advertisements. By using data from other ads and landing pages to improve query matching, ads can become more dynamic and effective, provided you are comfortable with relinquishing control to Google’s AI. this technology holds the potential to significantly boost the relevance of your advertisements, yet it may not be the ideal choice for heavily regulated industries or brands that adhere strictly to compliance standards. By fully handing over control to AI, Google gets the final say in your ad’s content. It’s important to remember that advertisements are subject to FTC regulations, and with ACAs, you will not have assurance over the message that will be displayed.

3. Treat Performance Max with Caution

At True Interactive, we are not quite ready to call ourselves Performance Max enthusiasts considering the limited control advertisers have over these campaigns and lack of visibility into performance. Although we would certainly encourage everyone to try it (if they have the money to spare), we would also recommend exercising special caution, as this campaign may cannibalize traffic from other campaigns being run under the same ad account (such as Search Brand campaign), and therefore hurt the overall performance of Google Ads.

Contact True Interactive

At True Interactive, we advocate on behalf of our clients. We are monitoring these developments closely and assessing how to incorporate conversational AI. Contact us to learn how we can help you succeed in all forms of digital advertising.

How Microsoft Will Incorporate Ads into Conversational AI

How Microsoft Will Incorporate Ads into Conversational AI

by Héctor Ariza Microsoft

How will search engines such as Google Search and Microsoft Bing generate advertising revenue via conversational AI? This question has been hotly debated ever since Google and Microsoft launched their own conversational chatbots in their search engines. After all, conversational AI tools succeed by giving searchers concise responses instead of links to other sites. Google’s ad model depends on people staying engaged on Google Search clicking on links. Microsoft’s ad business, though nowhere near the size of Google’s, also depends on clicks and engagement.

Microsoft recently provided some guidance on this question. According to Kya Sainsbury-Carter, corporate vice president of Microsoft Advertising, the method of purchasing advertisements on Bing remains unchanged from its inception. However, a new feature now allows ads to be integrated into interactions with an AI chatbot. Advertisers will not be required to request for their ads to be included in the chat format, and they won’t be notified if their ads were displayed in this manner when they get performance reports.

She noted that whenever the AI chatbot provides a response, it includes a reference that can be viewed by hovering over the response. This citation may occasionally contain an advertisement link. Furthermore, image-based ads can be displayed following the chatbot’s reply. Companies aren’t required to create new content that replicates the style of a chatbot response. Rather, all text advertisements and other creative resources uploaded on Bing will be displayed in the new chat formats.

Here is an example courtesy of Microsoft:

Microsoft Bing

Bing has expanded to 100 million+ daily active users, according to the company, with one third of them utilizing the AI chat feature every day. Since February and the roll-out of its AI-driven search, daily downloads of the Bing mobile app have quadrupled. Microsoft recently moved its AI-chat product from limited preview to open preview (thus eliminating the waitlist for trial). This should expand the product’s user base.

Microsoft also noted that:

  • The advertising products within Microsoft’s AI chat will function based on the same auction principles as Bing search auctions, indicating that advertisers may not necessarily experience an increase in cost per click.
  • Advertisers have told Microsoft they favor visually engaging, immersive advertising experiences, increased automation for real-time ad placement optimization, and formats that support shoppable experiences, such as visual comparison designs or shop-the-look formats. In fact, Microsoft intends to make chat more visually appealing.
  • With the updated Bing, users request more product information within a shorter duration compared to conventional search. This implies that the AI-driven tool could offer advertisers more insights about users and expedite their transformation into buyers.

These developments are intriguing. We recommend that advertisers be open to the way conversational AI is evolving. At the same time, advertisers:

  • Need to challenge Microsoft on issues such as accuracy of conversational AI and bias. It’s essential that users trust conversational AI in order for these tools to be adopted.
  • Should have control over ad placements and whether they choose to show ads in the chat. How can an advertiser judge success of an ad placement when it’s unclear whether an ad shows up in chat?
  • Deserve visibility into how the ad performs specifically when showed in the chat. Google (and Bing) have been reducing advertisers’ visibility into search queries, placements, and ad performance in general.

Contact True Interactive

At True Interactive, we advocate on behalf of our clients. We are monitoring these developments closely and assessing how to incorporate conversational AI. Contact us to learn how we can help you succeed in all forms of digital advertising.

Image source: https://unsplash.com/@rubaitulazad

Are Meta’s Problems as Bad As They Seem for Advertisers?

Are Meta’s Problems as Bad As They Seem for Advertisers?

by Héctor Ariza Facebook Instagram Meta

Just when you think things couldn’t possibly get worse for Meta, along comes another disastrous earnings announcement. On October 26, Meta, the parent of Facebook and Instagram, announced third-quarter earnings characterized by declining revenue and profits.

Quarterly revenue was $27.7 billion, down more than 4 percent from a year ago, after Meta posted a 1 percent decrease last quarter. Advertising revenue came in at $27.2 billion, down nearly 4 percent year-over-year (although that figure beat analysts’ estimates of $26.9 billion). Since advertising represents 98.2 percent of the company’s total revenue, the revenue drop is especially worrisome for Meta.

So, what’s causing the meltdown?

Weakening Demand

The biggest factor: diminishing demand for ad products caused by market uncertainty. In a call with investors, CFO Dave Wehner cited “weak advertising demand, which we believe continues to be impacted by the uncertain and volatile macroeconomic landscape.” CEO Mark Zuckerberg added that “. . . it’s not clear that the economy has stabilized yet so we’re planning our budget somewhat more conservatively.” As a result, Meta predicted that ad revenues will be $30 billion to $32.5 billion for the fourth quarter, below analysts’ expectations of $32.2 billion. (That level would represent another decline from a year ago, when total revenue was $33.67 billion.)

The TikTok Factor

The company, like Google, also faces rising competition from TikTok, whose popular short-form videos have generated a sharp increase in advertising revenue. According to Statista, TikTok generated $4 billion in advertising revenue in 2021, a figure that is expected to double by 2024 and triple by 2026. Digiday reported recently that ad agencies are shifting content creation from Instagram and YouTube to TikTok. In April, Insider Intelligence predicted that TikTok’s ad revenue will grow 184 percent to nearly $6 billion in 2023 (that amount tops Twitter and Snap combined).

To fight TikTok, Meta has given priority to the development and growth of Reels, its short-form video format on Facebook and Instagram. Meta is now seeing 140 billion Reels plays across Facebook and Instagram each day, which is a 50 percent increase from six months ago, according to Zuckerberg.

But Reels doesn’t monetize as effectively as the company’s other types of content. So, as Meta pivots toward showing more short-form video, Meta is taking a quarterly revenue headwind of more than $500 million, Zuckerberg told investors. Meta expects to get to a more neutral place with this shift within the next 12 to 18 months.

“As Reels grows, we’re displacing revenue from higher-monetized surfaces,” Zuckerberg told investors. “That’s clearly the right thing to do.”

The Apple Factor

Meta continues to grapple with the fall-out of Apple’s privacy controls, known as App Tracking Transparency (ATT). Meta said its average ad price decreased 18 percent on the year, as it adjusts to Apple’s changes that make it harder for Meta to track users and serve them personalized advertising. In the same quarter last year, the average price per ad climbed 22 percent.

But Meta also said that the blow to ad revenue caused by ATT is diminishing. Per CFO Dave Wehner, “Consistent with our expectations, the headwind to year-over-year growth from Apple’s ATT changes diminished in Q3 as we lapped the first full quarter post the launch of iOS14.5.”

But Apple isn’t done punishing Meta. Apple recently changed its App Store terms to take a portion of social-media advertising revenue. The policy change requires users and advertisers to make an in-app purchase when they pay to boost posts in apps like TikTok and Meta’s Instagram. Apple takes a commission of as much as 30 percent on in-app purchases, meaning a company like Meta would lose a portion of its ad revenue to the iPhone maker.

The company also faced stiff criticism from investors over its continued push into the metaverse, which has cost the company billions of dollars. Although the company’s metaverse investments technically do not affect its ad revenue – they’re more of a drain on profits than anything else – they have raised concerns that Meta is taking its eye off its core social media growth engine in the web 2.0 world.

The Good News

But on the bright side, Meta reported that:

  • Daily Active Users (DAUs) for the quarter were: 1.98 billion versus 1.98 billion expected, according to StreetAccount. That was up from 1.97 billion three months ago. 
  • Monthly Active Users (MAUs): 2.96 billion versus 2.94 billion expected, according to StreetAccount

Meta said Instagram now claims more than 2 billion monthly active users, while WhatsApp’s user base has surpassed 2 billion daily active users, with North America being the messaging app’s fastest-growing region.

What This Means for Advertisers

So, what does all this mean for advertisers? Well, now might be an opportune time to advertise on Meta, with its user base being strong and average ad prices decreasing. The company is rolling out new ad products to improve the monetization of Reels, and a new “Performance 5” framework, which is a set of five data-proven tactics that can help to improve advertising performance on Meta platforms amid tighter privacy controls. For instance, broad targeting consists of an automated targeting approach that reportedly produces better results for Facebook and Instagram ads than more refined, more niche audience approaches.

Meta, like its competitors, faces some difficult times amid economic uncertainty. But businesses that are taking the long view with their advertising efforts may turn out to be the winners so long as they don’t push the brakes on their online advertising efforts.

Contact True Interactive

To succeed with social media advertising, contact True Interactive. We have extensive experience helping businesses succeed on social media.

Why Google’s Predictive Audiences Feature Matters to Advertisers

Why Google’s Predictive Audiences Feature Matters to Advertisers

by Héctor Ariza 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 Enhanced Conversions for Web: Advertiser Q&A

Google Enhanced Conversions for Web: Advertiser Q&A

by Héctor Ariza Google

Google continues to evolve its advertising products for a privacy-first world. One important way is to move businesses to more aggregated measurement solutions as the availability of individual level identifiers decreases with the value of third-party cookies eroding. One such tool that has capture more interest in the market is Enhanced Conversions for Web. This is a conversion tracking feature that enables more accurate conversion measurement by increasing observable data – and, according to Google, improving overall quality of conversion modeling. Enhanced Conversions for Web allows businesses to capture customer data that advertisers collect on their conversion page (e.g., email addresses) and then match it against Google logged-in data. The raw data (e.g., an email address in plain-text format) is captured“as is” on the website, and then automatically hashed by Google as it is sent to Google’s server. Following are answers to commonly asked questions about Enhanced Conversions for Web.

What exactly are Enhanced Conversions for Web?

Enhanced Conversions for Web are not a replacement to the standard online (gtag-based) Google Ads conversions, but are rather a complementary feature that improves the accuracy of conversion measurement.

Enhanced Conversions for Web is basically a setting under the online conversion that enables your website to send hashed first-party, user-provided data directly to Google Ads when a user converts in the form of email addresses, phone numbers, first names, last names, and street addresses. Although email addresses are preferred and often suffice, an advertiser can choose to send more information to Google to improve the matching rate. Google then uses the hashed user data to match your customers to Google accounts, which were signed in to when they engaged with one of your ads.

Why does True Interactive recommend enabling Enhanced Conversions for Web?

As the industry starts to move away from cookies, advertising platforms/providers like Google are already developing new privacy-focused conversion measurement methods that do not use browser cookies.

Today, standard online conversion tracking relies on the web browser/cookies, where the Google Click ID (GCLID) is stored upon arrival to your website right after someone clicks a Google ad. Once a specific conversion action is completed and the conversion tag is triggered on the website, the GCLID is sent to Google so that Google can attribute the conversion to the appropriate ad campaign, keyword, creative, audience, etc.

The Enhanced Conversions for Web feature helps Google match the conversion to its corresponding ad campaign, keyword, creative, audience, etc., by providing more keys (such as email addresses) in the event that the GCLID is missing.

This not only provides advertisers with better visibility into campaign ROI by recovering conversions that otherwise would not have been measured, but it also helps drive better performance by giving the Google algorithm (auto-bidding strategies) more data points to optimize ad delivery.

How does a business enable Enhanced Conversions for Web?

There are a few steps to implementing Enhanced Conversion tracking, all of which True Interactive can assist you with:

  1. Identify the online conversion(s) for which the Enhanced Conversions feature needs to be activated.
  1. Enable the Enhanced Conversions setting inside your Google Ads account.
  1. Depending on the current Google Ads tag implementation, advise on how to enable the Enhanced Conversions feature by editing the conversion tag on the site (if the tags have been deployed manually on the website), updating the conversion tag in GTM, or setting it up via the Enhanced Conversions API.

Note that Enhanced Conversions will only work for conversion types where customer data is present – such as subscriptions, sign-ups and purchases. One or more of the following pieces of customer data must be available:

  • Email address (preferred)
  • Name and home address (street address, city, state/region and postcode)
  • Phone number (must be provided in addition to one of the other two pieces of information above)

Enhanced Conversions for Web underscores a larger point: it’s essential that businesses understand how a privacy-first world is affecting the way they manage their advertising and marketing. For more insight on Enhanced Conversions for Web, please consult this post from Google. And to stay on top of advertising, including developments with consumer privacy, follow our blog.

Contact True Interactive

To succeed with online advertising in a privacy-centric world, contact True Interactive. Read about some of our client work here.

Google Analytics 4: Advertiser Q&A

Google Analytics 4: Advertiser Q&A

by Héctor Ariza 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. (Author’s note: Google has since revised its timeline. Google now gives 360 properties an additional full year, making the new deadline July 1, 2024.)

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.