And while various point solutions and startups have hopped onto the scene, a growing collection of enterprise solutions is offering newly accessible ways for teams to boost productivity—all within platforms they already use and trust. The generative-AI-scrawled writing on the wall is clear: there’s no better time than now to begin upskilling teams in artificial intelligence.

The rise of enterprise AI is upon us.

Enterprise AI can be divided into three categories: martech, of which many marketers are already familiar in the data and media space; general productivity and collaboration tools; and tools aiding in creativity. Let’s look at high-profile examples from the latter two categories that have only recently been revealed.

On March 14, Google announced its plans to add generative AI features to the Google Workspace suite, with Docs and Gmail being the first platforms that will make use of the new tools. This isn’t Google’s first foray into applying artificial intelligence to work; Smart Reply and Smart Compose were introduced in 2015 and 2019, respectively, to streamline email communication by recommending contextually relevance responses or auto-completing lines as they’re written in real time. 

Just a week after that announcement, Google opened up the waitlist for Bard, its chatbot alternative to ChatGPT. Unlike Workspace, Bard cannot be used with a corporate account; users must be logged into a Google account that they wholly control. Still, the application for business is significant, with Google suggesting use cases like generating blog post outlines or snappy taglines.

Just days after the Google Workspace reveal, Microsoft introduced Microsoft 365 Copilot to the world on March 16. Similar to Google’s offering, Copilot applies natural language to unlock productivity, like translating a product spec sheet into a drafted product announcement in seconds. A key feature behind Copilot is Business Chat, which works across a user’s data to surface up information and insights that are needed at a given moment. These moves come after a potential $10 billion investment in OpenAI, the company behind ChatGPT and other AI innovations, following previous investments in 2019 and 2021. 

Getting creative with AI.

Like the enterprise tools mentioned above, Adobe Creative Suite is no stranger to AI; Sensei, a feature uses AI and machine learning to help users quickly make key edits to photography and design, launched in 2016.

Now, Adobe is launching Firefly, a family of generative AI models to assist in visual creation of all kinds, including still imagery, video content and 3D models. Examples include adding context-aware elements to an image you’re already working on—like speaking a castle into existence within a drawing of a beautiful landscape—or generating a whole image or design based on a sketch or a few words.

What’s interesting about Adobe Firefly is that it’s trained on images from Adobe Stock and works that are either in public domain or open license, avoiding the challenges of rights and ownership that affect models trained from content sourced across the internet.

Embrace experimentation to build AI maturity.

The rise of enterprise-ready AI is a turning point of the technology, which is now becoming even more accessible for employees looking to supercharge their productivity and creativity. But simply adopting a new technology isn’t a silver bullet that will help people work better with the click of the mouse.

Consider the paradox of choice: this phenomenon explains how when presented with more options, people expend more energy to make the right choice. Everyone has felt the paralyzing dread of a blank page waiting to be filled, and opaque platforms that rely on natural language can easily overwhelm, particularly for employees who aren’t used to issuing directives. To make the most out of these tools, then, brands will need to upskill their teams to better understand their potential and how to act on it.

Our team has been eager to embrace these tools to experiment and share that knowledge with our partners. Following a successful AI hackathon last winter to kickstart that maker’s attitude, Jam3 hosted another AI hackathon in March across its global offices, with the goal of answering the question: how can (and should) creatives in our industry use AI-powered tools? Challenged to build a brand strategy and product offering for a fictional fashion and beauty brand, each team employed AI as a sparring partner to gain an unconventional creative perspective and accelerate results. AI had to be used as a tool to generate ideas, insights, visuals, scripts and code—ultimately resulting in a campaign to launch the fictional brand and a storyboard and prototype to bring it to life. These events go a long way in helping employees envision the role that AI can play in achieving their everyday responsibilities.

Don’t wait to get started.

We’re only in the beginning of the AI-augmented workplace, but these tools and platforms are becoming increasingly sophisticated each day—meaning if you haven’t embraced AI on your team yet, you’re already falling behind. 

That’s why we put together a quick, single-page guide mapping out areas where brands can begin building their AI maturity right now, while also gearing toward future goals as technology continues to improve. Whether you’re looking to do more with less, personalize marketing on a grander scale, or something else altogether, find out how to get started with our quick guide.

Working as a Senior Data Specialist, I’ve come across a series of common mistakes that prevent enterprises from leveraging this tool to its full potential—and consequently, accessing the true value of their data. During a series of panels at Melbourne MeasureCamp, I was lucky enough to host a session on these observations and some recommendations so that brands can bank on actionable insights into user behavior and application performance. If you missed it, continue reading for the main takeaways.

Learning #1: Only one Firebase project can be linked to one GA4 property.

An important thing to consider when it comes to integrating Firebase with GA4 is that only one Firebase project can be linked to one GA4 property. This means that if there are multiple Firebase projects, it’s necessary to transfer all applications—regardless of operating systems or development cycles—into one project and link it to the main GA4 property. 

This requires careful planning and a deep understanding of how Firebase projects are set up.  Keep in mind the potential technical challenges and limitations in migrating apps from one project to another. For example, certain app developers may have their own preferences in terms of project setups, so you need to talk to your development team and understand what that looks like. 

Also, be aware of dependencies such as Crashlytics or BigQuery exports setup when moving apps from one project to another. Each Firebase project can have multiple stack integrations, and we should be ready to reconfigure all of them. Make sure you have historical data and map out timelines for these app migrations.

Learning #2: Standard naming unlocks customer insights. 

The main reason why you’d want to integrate Firebase with GA4 is that it provides valuable insights about user journeys across web and app platforms. However, the only way to unlock those insights is by ensuring standard naming conventions for web and app events. 

First, you’ll need to create a Google Sheet or an Excel spreadsheet to standardize the naming of events and parameters. Here’s an example:

As you can see, we recommend having standardized event names and parameters across web and app platforms in GA4. It may seem simple, but it's not uncommon for organizations to use different conventions on different platforms, making it harder to cross-reference the data.  

Other tips to make the process easier include:

• If you have a website, but no app implementation yet, rely on your web and GA4 Recommended Events to name the event and implement these for the app.
• If you already have an app implemented with Firebase, use the mapping sheet to understand which events from the app can be mapped to web. It is easier to rename web events with GTM than doing so for the app.
• Align with both web and app development teams for naming conventions. For example, using camelcase (e.g. SignUp) vs snake case (sign_up)

Learning #3: Be Aware of Data Collection Limits.

When you use Firebase to collect data from your apps, it’s important to be mindful of the data collection and configuration limits. Firebase Analytics does not log events, event parameters, and user properties that exceed certain limits—which means that the platform will drop the events and stop tracking valuable data even if you exceed the limit by a few characters. 

In my experience, this mistake is especially common among developers who implement the Firebase SDK without really knowing about the limits. These are some of the main caveats and my respective recommendations for them:

• Event parameters limits: 25 parameters per event may seem a lot, but it may add up if you’re sending ecommerce events. GA4 and Firebase will drop the events and event parameters if you exceed this limit.
• Be careful not to go over the maximum length of the event parameter value, which currently stands at 100 characters. Be aware of user-generated values (e.g. listing name in marketplaces)
• Remember that Firebase does not accept array type parameters.
• When setting up BigQuery export for GA4 (with both app and web streams), check the usage in advance so that you don’t get shocked with the cost for the storage and querying the data. Pro tip: Set up daily aggregated tables for important metrics instead of querying directly from raw export tables.

In conclusion, it is essential to be aware of limitations around linking Firebase projects with GA4 property and plan ahead for your migration. Create a mapping sheet to map the events across the website and apps and standardize app and web events naming. Take note of Firebase data collection limits and make sure you are not going over the limits and risk losing your data. Finally, learn how to debug apps using Firebase Debug Mode, a bonus tip that can save you time and headaches.

“It’s so much more powerful being a part of a team that’s full of mixed backgrounds and experiences,” says Doug Hall, VP of Data Services and Technology. “Tech isn’t just for computer science graduates. If we didn’t have a rich tapestry of skills and experiences woven into the team fabric, we’d have a homogeneous glom of great skills, but we’d be more likely to do the same things this week as we did last, and in the same way.”

My move from non-tech to tech-first taught me that many things surrounding data are isolated from business needs and outcomes, even though you don’t want this to happen. When teams operate in silos and data works in isolation, so does experimentation. This inevitably leads to random acts of marketing and chaotic reporting. Rather than siloing teams, data should unify them—even if they have totally different KPIs. For instance, marketing teams look at lead generation, engagement and visibility, while product teams focus on retention and acquisition. In short, if everyone has a separate way of tracking and collecting data, this also means that everyone is looking at different things. 

Viewing the full picture is pivotal to success. 

The bottom line is that all of this information is data, and everyone should be aligned on what type of data will actually help the company move forward. Companies may invest in tools that serve one or more departments—GA4, for one, can support marketing and product teams—but the way each team or department collects data should be a company-wide decision. In turn, this means that a company’s data collection mechanism needs to be strong and reliable to be able to support every team and department in a business and help spur progress. The goal is to unite, not separate. That’s why it’s critical to align what matters in terms of data collection and measurement with the company’s business needs. 

The operative word is context—whatever we do, we must keep this in mind. Getting your company or clients to believe in the data at hand starts with analysts and measurement marketers understanding where the business is right now and where it can go. By actively participating in the inner workings of a business—with a focus on resource allocation and the processes that generate money—and analyzing relevant and purposefully collected data, you can help steer your company or clients towards profit. 

As such, I recommend every digital analyst to get familiar with a business’ internal processes. You can use this knowledge to implement tracking and analytics systems that align with the company’s procedures. A good example of this is how we helped the multinational alcoholic beverage company Diageo deploy GA4 across its 150 brand websites. As Hall explains, “Due to alcohol regulations around the world, most countries require an age verification gateway, which is a major conversion blocker that goes above and beyond consent management. This means that measurement and optimization are crucial for Diageo—and that’s how we knew that deploying consistent measurement across all brand sites was the best solution.”

In short, every digital analyst should come to understand the business context and goals to make sure the tag management and analytics tools are both implemented effectively and in line with the needs of the business. The secret sauce here is to closely collaborate with business-focused team members like marketers, consultants and account managers, who can provide guidance on what data is needed and how it will be used. Sure, we can rely on our experience and heuristics, but that doesn't mean any of our assumptions can be valued as truth. Once you’ve actually combed through a specific business context, you can start to define the right strategy for your business—and even then, it’s a matter of seeing how things play out before you can confirm or reject your hypothesis. Experiment, experiment, experiment!  

Become data mature to make your cash flow. 

Ultimately, this all feeds into a company’s data maturity, which Forbes defines as “a measure of an organization's ability to use data, along with how well the organization leverages those capabilities.” It’s not just about making data-driven decisions, but also about making sure data resources are accessible across an organization. The more data mature you become, the more you can scale—a topic that Coquet will discuss in more detail during the upcoming SUPERWEEK conference.  

With scale comes growth, which, in turn, can lead to new opportunities—and let’s be honest, this is an outcome that every business is after in their search for better tools, better consultants, and better digital marketing partners. When it comes to collecting data and tracking user behaviors (with consent, but this goes without saying), businesses do not want to miss out on any opportunity to get new customers, while staying relevant to their existing ones so that they continue to trust and purchase from them. More happy customers equals more cash flow. In the end, profit is the ultimate validation of growth (and that you’re doing a good job), both from a product and a customer experience perspective. 

Three takeaways to make your data take off. 

While it may take some time to find the most advanced tech stack or the best digital marketing partner—one that truly understands your business and all its needs—there are some changes you can make today. Trust me when I say that these actions will pay off in the end and help your cash flow grow. 

First of all, start by defining the problems you are aiming to solve and the questions you are seeking to answer with your data before you implement anything. This will help fine-tune your efforts and ensure that you are using the right tools and approaches to address the specific challenges you face. 

Second, consider (and research) the possibility of teaming up with a data consultant or specialist, who is able to provide expert advice and guidance on what tools and approaches are best for your specific problems and questions. This is particularly helpful if you are working on a complex or unique challenge that requires specialized knowledge and skills.

Third, teamwork always makes the data dream work. It’s crucial to collaborate with your team members and exchange your knowledge and experience—as Doug said, the more mixed the expertise, the better. By closely working together and sharing what you know, you can pool your collective knowledge and experience in setting up your measurement strategy. Keep in mind that within a business context, every team has its own problems and questions. As a leader, it's important to begin by having them define these, which, in turn, will reveal how aligned your team is around the company’s needs.

The main lesson that you should learn from this article is that context is key. At the end of the day, understanding human behavior, the business landscape, and how a company and its clients bring in money is what makes a successful digital analyst. I didn’t know this ten years ago, but I do now and I’m very happy to share these insights with you—find Julien, Doug, me and many other Data.Monks at SUPERWEEK 2023 and learn more about what really matters in managing your data.

To help brands in their transition, our data experts have written a guide that explores how brands should approach personalization going forward—including how to assess new technology providers, frameworks and methodologies to structure your planning—and long-term goals to strive for. Access your copy by filling out the form immediately below.

Need answers at a quick glance? Continue reading on for a quick FAQ that will help you get started.

Will I still be able to use Google Optimize after September 2023?

No, Google plans to sunset the product entirely. This can be taken to mean that the product will no longer be accessible past this date, and experiments running at this date will turn off.

Does this apply to Optimize 360 as well as the free product?

Yes. Google intends to sunset the product entirely, across both the free and 360 tiers. Note that by the sunset date, all organizations should have migrated their GA360 contracts to GA4, meaning that Optimize 360 is provided free of charge.

Should I use Optimize with UA or GA4 up until the sunset date?

This is entirely dependent on your existing UA and GA4 setups. UA 360 will continue to be available until Optimize’s sunset date, so you can continue to use it if you are more comfortable with that dataset. Otherwise, you can use GA4 data to power reporting and audiences. Linking Optimize with UA is available even after renewing GA360 contracts with GA4.

What should I do if I want to continue testing and personalizing my website after Optimize is sunset?

You will need to procure an alternative testing and personalization platform. Our report details the factors that should go into making that decision, and you should note that alternative platforms will have different commercial models than Optimize.

Will I still be able to use Google Analytics with a new third-party Experience Optimization tool?

Google has announced that they are investing in integrations between GA4 and third-party tools, with the intent being that GA4 will act as a centralized measurement hub that can be used to analyze and report on experiments that are delivered via a different platform. Media.Monks can provide more details on these integrations as they are made available by Google.

What will happen to my historical data?

Optimize uses Google Analytics data for reporting, meaning the raw data from past experiments will still be available in GA (and BigQuery if using GA360). Regardless, we recommend our clients collate test results in a central register to build an insights and learnings repository to fuel future decision-making.  Media.Monks can support the creation of a learning repository before the sunset if required.

Key watch-outs:

• An Optimize container can only be linked to UA or GA4 one at a time, not to both. Media.Monks do not recommend running experiments out of dual containers, so you should choose whichever dataset has the most actionable data.
• There are many factors that go into selecting an alternate vendor, and a proper assessment takes time. Organizations should bring this process well ahead of September 30 to ensure the continuity of capabilities.
• Deploying, validating and ramping up a new testing/personalization platform could take a number of months, meaning organizations should start the selection process now.

To get detailed steps on how to prepare for the Optimize sunset and plan your post-Optimize goals, simply fill out the form above to download our report.

As part of Google’s Learn With GMP series, our Sr. Director of Tech Consulting & Architecture, Jackie Saplicki, and Sr. Director of Enterprise Data Transformation, Kosta Demopoulos, hosted a webinar on how to identify realistic and effective solutions that respect consumer privacy and help catalyze your brand toward digital maturity. Together with Google’s Ads Privacy Specialist, Lisa Tanzosh, they dove into the steps needed toward building trust in the quality of data—complete with key considerations including the importance of taxonomy in creating a functional approach. In case you missed it, you can watch the full session below, or continue reading for the main takeaways.

A strong data foundation starts with control.

For every organization, reliable data systems and good decision-making go hand in hand. At its core, that’s exactly what building solid data foundations is about: ensuring that the information we have is accessible, timely, trustworthy and fit for purpose so we can take the right steps toward our business goals. But that doesn’t happen spontaneously. Instead, it hinges on our capacity to exercise control over the data we own.

A good first step to gaining that control is building a list of all known data sources, such as ad servers, buying platforms and analytics tools. Data lives in many different places, and we need to bridge that divide in order to access a complete view.

Once you’ve conducted that streamlining process, the next phase is establishing data standards and rigorous governance practices to assess the quality of the data. “We can do so by leveraging media buying platforms and Cloud infrastructure to understand how the data is being reported out, how we can automate pipeline ingestion, things of that nature,” says Saplicki. “Identify vulnerable or error-prone areas and ensure that they are protected and have the proper standardization around them.”

Data quality is critical. 

Proper data standardization means looking at the rules we’re using to make sure we’re off to a good start. And that includes how we’re naming things. “Solving the taxonomy challenge is a critical first step,” says Demopoulos. “A single error in an object taxonomy entry or in the glossary maintenance system will bring reporting issues, requiring manual effort to investigate the error and correct it.”

While it’s not always easy to have a full grasp of the relevance of taxonomy, the truth is this is the bedrock on which everything else is built—including all the steps that lead to more effective creative and cost-efficient campaigns. Working with Bayer, we built a highly complex but unified taxonomy that assists with analysis and provides a consistent data feedback loop. That way, the team was able to condense multiple sources of data into a single dashboard that empowered them to make optimization decisions with meaningful impact.

To build equally powerful taxonomy strings, take into account the different data sources and their specific terms and requirements. While doing so, consider future changes in the market or even within the organization. If done right, you’ll reap the rewards of this effort for years to come; and if you are ever faced with the need to make changes, minimize the risk by doing so during downtime. 

Earning the trust of your organization.

A solid data foundation with impeccable taxonomy doesn’t only lead to good reporting, it also provides a common language for everyone to rely on. Especially when collaborating with external partners or even as new hires join the team, data that is labeled and structured becomes accessible to the entire organization.

After all, no single team is fully responsible for the data transformation program that building a solid data foundation requires. It spans data, tech, people, marketing, processes and more. Initially, putting together a series of use cases can be incredibly potent to get the buy-in from different stakeholders. As time goes by, trustable and transparent data will keep them on board. 

Overall, data foundations yield unified data sets in an organized, secure environment. If you want to improve the performance of your content campaigns and access advanced solutions such as machine learning, you need complete, standardized data. Especially now that the privacy landscape is changing, there’s no better time to buckle down and bolster your journey toward digital maturity.

These are not off-the-cuff suggestions, as the impact of ignoring or misinterpreting these recommendations is plainly visible. With privacy currently being the fastest moving field in our industry, we’re reaching the point where most—if not all—professional discussions have a privacy angle. While that’s great in terms of profile, it’s not really good in terms of quality.  

If you ask me, most cookie banners are subprime usability blockers that annoy users and turn them away. At worst, they’re dark patterns obscuring malice. When the most common denominator is so prevalent—that being lousy banners—we get what is called banner blindness, a phenomenon where web users (un)consciously ignore any banner-like information. When that symptom kicks in, it’s a downhill race to the bottom.

A likely sequence of events then plays out: marketers settle on a nice and easy bottom feeding tactic, the whack-a-mole game of privacy merry-go-round spins through another orbit as either tech, public opinion or regulators (or all of the above) make a new move to counter it. Recently, for example, it was Brave’s turn in the game of ignoring the privacy elephant in the room. The company announced it was going to block cookies by default and roll out a cookie pop-up blocking feature to Android and desktop users, which is arguably a step backwards. Rather than adding any clarity around what data is collected and why, the browser actually acts on behalf of consumers and removes choice from the user. It’s important to highlight that regulation is not anti-business, but it’s pro-consumer. Privacy-enhancing technology needs to respect this narrative. 

My former colleague (and still just as wise) Myles Younger powers his crystal ball with some nostalgia to suggest consent pop-ups are dead. “Someday soon we’ll look back on cookie consent pop-ups the same way we look back on “300 hours of free AOL” CD-ROMs littering our sidewalks. The farcical dying gasp of a dying way of transacting a digital thing,” Myles argues—and he is not wrong. It’s been seen before, as observed by the analytics supremo Simo Ahava, who argues that Do Not Track was a failure from the start. Diving into the implications of Safari’s Intelligent Tracking Prevention, better known as ITP 2.1, on web analytics, Ahava says that “Funnily enough, ITP 2.1 removes support for the Do Not Track signal in Safari, denoting the end to this miserable experiment in WebKit. Had more sites respected DNT when determining should visitors be tracked or not, perhaps we wouldn’t have seen ITP 2.1 in its current shape.” 

Consent management is anti-user.

Why are these well-meaning initiatives failing? Google surveyed over 7000 people across Europe in 2021 and found that users want to have control of their data. Recent follow-up research quantified the degree to which the feeling of control influenced customer confidence in brands. The conclusion? A positive privacy experience on a site has a measurable positive impact on a brand.  

So, how can you create such a positive privacy experience and avoid the pitfalls that we’ve seen with Do Not Track (DNT) and the current crop of Consent Management Platforms (CMP)? If it’s up to Google, brands should make the experience:

• Meaningful by showing people what they get in return for sharing their data
• Memorable by reminding people what data they shared and when
• Manageable by providing tools for people to manage their privacy

The demise of third-party cookies means the future of first-party cookies. 

For many, applying this mnemonic to first-party cookies is a work in progress. Cookie consent banners are still relatively new, even though third-party cookies have been under threat for many years. We know which browsers restrict their use and we expect these restrictions to extend to Chromium browsers in 2023.

If digital marketing can’t function without third-party cookies, this has the potential to hit big tech in the coffers, and we cannot allow this to happen. There’s a clear motivation to solve existing use cases by utilizing privacy-enhancing technology—this is where The Privacy Sandbox comes in. According to a Google statement, “Privacy Sandbox for the Web will phase out third-party cookies and limit covert tracking. By creating new web standards, it will provide publishers with safer alternatives to existing technology, so they can continue building digital businesses while your data stays private.”

We’ll see the next phase of testing kick off in 2023 when the Privacy Sandbox API is publicly available for testing on Android. Right now, this is API testing, which means that they’re testing for developers rather than users. The user testing phase is where it gets real for real people. This is the opportunity to succeed, think of Google’s mnemonic, instead of failing like DNT and CMPs.  

Cookie management sitrep.

Right now, you can open the settings in your browser on each device and scroll through the list of cookies for each site, and decide to delete them. You can then visit the site and repeat the exercise in the “manage cookies” section of the CMP.  However, this current process doesn’t fit in terms of being manageable. In fact, the term laborious doesn’t even begin to describe it.

When it comes to qualifying as meaningful, cookie management has a low score because it’s so opaque—how can you tell who else is getting access to the cookies and for what purposes? As for memorability, most users only remember the frustration and tedium, but little else regarding their choices.

So, considering the future of cookie management, how might the Privacy Sandbox address the choices users have to make with regards to “tracking” and their privacy? While this section is entirely speculation and therefore not an official roadmap, it’s aspirational with the aim to be realistic and pragmatic. My thoughts are as follows. 

• Users get to decide what topics they are interested in and willing to share with third parties.  
• Users allow the browser to build a list of topics, but the user reviews and controls the list periodically asking to be reminded on a set schedule.
• Users can choose to set their topics to apply across all sites they visit. Any advertising they see on any site they visit will use and respect these settings.
• Users can choose to review their topics preferences on a per site basis. Users get to curate (and review) their own whitelist/blacklist for sites or types of sites.
• Users ask to be reminded to check their preferences every so many days, weeks or months.
• Users can choose to reset all data in the browser automatically every so many days, weeks or months.

Now, let’s apply similar controls to first-party cookies:

• Users will be able to tell the browser what type of cookies they will accept, and whether they want to be measured—anonymously or otherwise.
• Users can specify this applies to all sites, some sites (whitelist) or types of sites.
• These settings are reviewed on a scheduled basis.

What are the right default values to apply on first use? The good news is, there are no default values. On first use, and on a frequent basis, the user must explicitly set their own first use values. In other words, no values are suggested or automatically preselected.

How is this different from a CMP banner? Set it once, and make a conscious set of decisions with no intrusive user experience on every site or app you use. This could actually be set at a “profile” level across all devices and all browsers. This requires less mark-up and coding to be done by site owners. In short, there’s less to maintain, less to go wrong, less to slow down and less to cause friction.

How is this different from DNT or Brave? A more granular approach and a genuine user-controlled choice are the fundamental differences that make this approach manageable and meaningful. The range of choice is meaningful and the act of making a choice is manageable as it is made as friction-free as possible. Moreover, having to make a choice is memorable, as well as the ability to set reminders to review these choices at your convenience.

Now is the time to apply these lessons for the future.

The challenge for The Privacy Sandbox is to reduce friction, increase transparency and enhance authority. The privacy improvements will cater for existing use cases as well as provide a manageable, meaningful and memorable privacy experience for users.

That said, what’s the takeaway for digital marketers? Google said that “The Privacy Sandbox on Android will be a multi-year effort,” so what to do right now? Circling back to the start of this article, it’s important to:

• Take control of your data
• Embrace the regulatory spirit
• Go beyond the bare minimum
• Make it meaningful, memorable and manageable

Though we accept the looming end of the third-party cookie, this doesn’t mean we have to stop digital marketing. New privacy-enhancing tech changes the methodology, as the same use cases are catered for with new tech to enable better ad serving. Having learned from the success of these technologies applied to the end of third-party cookies, we can confidently focus the lessons on our first-party data collection. What works across sites and apps must also have the same utility on individual sites and apps. Keeping that in mind, the end goals remain:

• Build a relationship with your customers
• Be transparent
• Be useful
• Be responsible with data

All in all, achieving these goals and aiming to provide a better experience has immense value for your customers and your business.

When it comes to the privacy arena, what trends are you seeing agnostically?

Privacy is one of the fastest changing and most complex realms in the digital space, even more so than Web3. On top of that, privacy is an ever-present undercurrent—ongoing in everything that we do. With a plethora of global and regional players involved—the tech sector, regulatory bodies, public opinion—we can safely say there’s a complex interaction at play, which makes coming up with any long-term prediction or silver bullet solution practically impossible. As a consequence, our waterways can quickly go from clear to muddy. What follows is a sense of fear, uncertainty and doubt among many companies. 

In working with companies across the board, we still see a lot of confusion around technical terminology, with partners raising questions such as, “What is personal data compared to Personally Identifiable Information (PII)?” To be frank, we believe this is in part driven by clickbait. Headlines propagating that “GA is illegal” cause unnecessary confusion and concern, when the fact of the matter is that Google’s GA4 as a product has gone through a massive rebuild from the ground up to address and tackle the issues in question. As a baseline trend, we’re receiving more and more questions about privacy matters with regards to all products in the digital marketing ecosystem—and we welcome them with open arms, because we’re here to help solve the riddle. 

How are you helping clients navigate this new, data-focused advertising landscape?

Our objective is to help our partners take proper control of and ownership over their data collection and activation. Therefore, we first focus on basic data hygiene, conducting health checks and audits. It’s very important to know what your company has in store, so we ask questions like what data is collected, which cookies are set, how is the collected data used, and who else is getting the data of your users? Creating a graph of 3P consumers and beyond is complex and thus requires high levels of scrutiny. 

Though the third-party cookie deprecation has been pushed back until at least late 2025, we don’t like to wait around and carry on in the same way we have always done. Rather, we’re embracing a first-class, first-party and privacy-first strategy, for instance by helping companies migrate to GA4—because we see no reasons for taking a reactive approach. We make sure our partners get on the front foot as fast and efficiently as possible, with a strong emphasis on automation. When you’re working with large data volumes, you can’t rely on human-centric processes to manage compliance. For instance, we have implemented automated machine learning as part of the data pipelines in order to prevent PII ingestion. There’s no way that a company can afford to manage a breach retrospectively or be proactive without automation—simply put, this is the most efficient way to scale. 

What are the main lessons that you have learned on this journey?

First of all, we clearly communicate to every brand we partner with to always aim for transparency, make a plan, and move beyond the minimum. Let’s be honest, the economic headwinds that we are all currently facing mean that every dollar, euro and pound spent needs to deliver a return more than ever before. As such, preserving data quality is our top priority. To give you the full scoop: everything we do to be more transparent, protect users’ privacy, and apply rigor and governance to data collection and activation is, in fact, enhancing the data quality, too. So long as you go about your data the right way, you can’t go wrong. 

Speaking of data quality, another key lesson that we have learned is to use time to the fullest. Yes, industry leaders like Google may unexpectedly push back plans, but rather than seeing this as an issue, we believe it can work to our advantage. Setting up the privacy tech for this tool is quick and easy—the hard part is changing the people and processes, which we know can take a while to get completely right. Though we expect that many brands will interpret this extension of GA360 as extra time to look around and perhaps jump ship to another technology, we believe that this is a risky strategy. Instead, we recommend our partners to take this change of plans as an opportunity to perfect, rather than a chance to pivot. There are no excuses to delay GA4 migration. It's imperative to use this time to manage change, translate data workloads, dashboards and data pipelines, and ensure all those GA360 assets become high quality GA4 assets.

Do you see gaps in performance between brands that invest in privacy and those who don’t?

There's a clear and definite advantage to taking a strong privacy-first approach to data—and companies are catching on. People are realizing (or, at least, starting to realize) that we’re not playing a zero-sum game and the exchange of data in return for personalization and better ad targeting is the data privacy transaction we all engage in—with reciprocity being the key word. Those who are best able to complete this transaction at scale will be rewarded with the best results, whereas those who continue to walk the third-party cookie path will fall behind. For some time now, we’ve been helping many of our partners run on a healthy diet of deterministic and probabilistic data and not trip over the mix of consented first-party and modeled data, and we can tell you: they are in good shape. 

Want to discuss next steps? Get in touch. 

Everything you do for privacy feeds back into your data quality, hence the opportunity to sharpen and perfect your process of migration to GA4 is one to take with both hands. It’s essential for brands to look beyond the obstacles of GA4 and work to get the best first-party data off the back of the migration.

We’re here to help make sense of changes in the privacy landscape, how to make use of GA4 data, and how such technologies can support all your marketing needs. If you have any questions with regards to GA4 migration, please reach out to growth@mediamonks.com. We’ll schedule some time to discuss any questions you may have and see how we can support your analytics needs.

Insights for this piece were contributed by Doug Hall, VP Data Services and Technology, EMEA; Julien Coquet, Director of Analytics, EMEA; Suzanne Jansen, Head of Data Strategy, EMEA; Véronique Franzen, Senior Director Business Consulting, EMEA; Jakub Otrząsek, VP Data, APAC; Sayf Sharif, VP Data, NAMER; Michael Neveu, Director of Data, NAMER; and Wenting Wang, Senior Director of Data & Analytics, UK.

When it comes to the reason why Google has chosen to deprecate third-party cookies to begin with, an increase in users’ demand for more control of their data is only the start.

Google must also comply with a long list of regulations surrounding privacy, the most notable being the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). These regulations ensure that there are certain standards for what constitutes valid consent when collecting personal data, as well as giving consumers more control over the personal information that businesses collect about them.

The phaseout of third-party cookies will support these legislations and ensure the success of the privacy-first era. From an overall perspective, the deprecation of third-party cookies will impact how campaigns are implemented and managed by brands and their partners. Previously, brands relied on third-party cookies to learn about a target audience and their online behaviors. Without this information, we can expect significant impacts on remarketing, frequency management, personalization, attribution and measurement. 

New ways to identify are on the horizon.

Third-party cookies facilitate cross-site audience identification, which essentially allows marketers to “follow” users across the web, collecting data about their interests and online behavior. Each of the tactics above rely on this form of cross-site audience identification, and without third-party cookies, marketers will be unable to access this information about their target market so easily. 

But that doesn’t mean marketers will no longer be able to conduct successful remarketing campaigns, control the amount of times a user views an ad, deliver highly personalized ads, or identify a user’s touchpoints along the customer journey—provided they prepare for the cookie-less future now and minimize its impacts on their digital media activities. 

Since the announcement of the deprecation of third-party cookies, Google has been working on a range of solutions to continue to show relevant content and ads. FLEDGE and Topics are two examples of current Privacy Sandbox solutions for showing relevant content to audiences.  

FLEDGE’s purpose is to serve remarketing and custom audience use cases, without using third-party cookies. It enables interest-group-based advertising by asking the browser to choose which ads users see based on the sites they’ve previously visited. To keep this data secure, the browser conducts an on-device action to select relevant ads. 

Topics is a proposal that enables interest-based advertising without tracking the sites a user visits. It provides topics that a user may currently be interested in, based on their recent browsing history. These topics can supplement contextual information to help select appropriate advertisements. 

However, trials for FLEDGE and Topics are still a work in progress and the solutions are continuously changing, so we must focus on what we can do now to be able to navigate in a world without third-party cookies. Don’t take a “wait-and-see” approach. Those who look to prepare now will increase their chances of success and advancement in the privacy-first era. Here are some strategies to help you on your way to post-cookie marketing success.

Prioritize and invest in a first-party data collection strategy.

To prepare for the deprecation of third-party cookies, marketers should focus on growing quality customer data that informs both strategy and tactics. Utilizing the data from customers who have shown interest in your brand is more reliable and powerful than buying and selling access to third-party data. 

First-party data gathered from your websites, apps, physical stores (including offline transaction data), or other places where customers interact with your business, are all examples of first-party data that you passively—but directly—collect from consumers. Earning this data relies on building a fair value exchange, so that consumer data is understood to contribute to a better experience. Customer trust is built on transparency, hence it's always important to explain how you’re going to collect and use the data in your cookie consent banner or consent management platform. When collecting data about your customers, you must also make certain that you are compliant with regulations such as the GDPR, ensuring you are getting valid consent when collecting personal data and not collecting personally identifiable information (PII). 

With first-party data, brands can evaluate local touch points and preferred paths, while customizing interactions for a superior customer experience. Now is an excellent time to look inward and begin to build the foundations of your data strategy—one that will power your marketing with clean, unified and actionable data. Collecting first-party data and linking it together allows you to have a persistent, cross-device recognition for a single view of your customer, and an overall understanding of your audience. Mondelēz, for example, understood that digital marketing is most effective when you know how to play to consumers’ personalized taste. After helping them along the road to clean data, we achieved a +70% global return on investment.

Focus on collecting information and data you have access to.

As a marketer, you have access to a plethora of data about your customers, whether it be purchase data, device information or email engagement. Having an identification-first approach to customer data will give you an upper-hand to targeting effectively without third-party cookies. With data from third-party cookies being cut off, the priority should lay with first and second-party data, audience partners such as walled gardens, prominent publishers and media platforms, retailers and strategic partners. 

After prioritizing your first-party data and collection strategy, you should focus on building experience with reputable, trustworthy second-party data partners. Second-party data is essentially someone else’s first party data that you purchase access to from partners like Google, Amazon, or large publishers. You should focus not only on historical data, but real-time behavioral data such as users’ devices, interactions with your website, their carts, purchase history, media consumption, as well as the categories and products they visited while browsing on your website. By leveraging second-party data from trustworthy partners, you will have more data transparency and access to more precise and niche audiences which are crucial after the deprecation of third-party cookies.

Conduct a measurement audit. 

Conducting a measurement audit will consist of analyzing everything you’re currently tracking and identifying if it is necessary to be measuring it. It will help you to identify potential gaps and develop a roadmap to achieve measurement excellence that drives business results in a world without third-party cookies. A measurement audit includes the evaluation of current measurement tools and systems, as well as the alignment of key goals to further develop the practice. When conducting the audit, you’ll want to identify the necessary data, reporting and analysis methodology to improve measuring marketing effectiveness going forward to help with planning and forecasting.

Key considerations when conducting the audit are to understand the need and whether you can drive more value from your analysis and analysis partners. You want to develop a robust framework that will be effective and efficient to leverage in your decision making. You also want to ensure the roadmap provides added value, and is adaptive and not difficult to implement. By conducting a measurement audit, you hope to identify opportunities for maximizing the value of your measurement, strengthening your analytic capabilities and performance, and understanding how to holistically link together different techniques for marketing effectiveness in a world without third-party cookies. 

Evaluate your ad tech stack and partnerships. 

It’s important for you to evaluate your ad tech stack and partnerships to identify technologies and practices at risk of deprecation in the near future. Having a strong, well-engineered ad tech stack will create seamless, relevant, and meaningful experiences for consumers and give you a deeper insight into those interactions. When evaluating your tech stack, you must analyze how much control you have over fee transparency, brand safety, streamlined operations, data ownership, targeting and ad serving. Your tech stack should also be able to enable current operations and be able to incorporate future ones. 

A partner risk assessment should be undertaken to evaluate how reliant partners are on non-compliant tactics, data and technology; what their new publisher and media partner offerings are, and opportunities beyond basic ad units. Those partners who rely on non-compliant tactics, data and technology should be making it clear what they are doing to prepare for the third-party cookie deprecation. Marketers should carefully consider their platform partners and ad tech stack and focus on those that can deliver results without third-party cookies.

Consider a dedicated testing budget. 

Marketers should allocate a dedicated testing budget for first-party data practices, audiences and strategies across thousands of variables. These areas should be tested and leveraged, becoming an integral part of the targeting strategy where successful. One way to do this is by  testing and targeting customer experiences to improve digital performance using optimization and personalization. You’ll want to design net new campaigns and tests running without cookies, leveraging experimental design. 

As the data agency of record for Molson-Coors, we’ve spent the last year helping the brand undergo a data transformation that ranges from data acquisition, data activation and optimization. With hands-on-keyboard talent and an in-house team, Molson-Coors is able to use that data to better understand creative and media performance, then make tweaks to drive long-term growth.

By testing audiences and strategies across thousands of variables to build detailed customer profiles and to increase ad performance, scaled experimentation is the best alternative to third-party cookies when it comes to personalized customer experiences, and the performance benefits have consistently been shown to outweigh the costs of investment. 

Don’t wait to get your digital house in order.

Third-party cookies have played an instrumental role in the immense growth in online advertising. Yet their often-intrusive nature is misaligned with current attitudes toward privacy and transparency—so moving beyond our reliance on cookies, while maybe painful in the short term, is a net positive in building stronger brand-consumer relationships. That said, we can expect more changes to data collection and privacy on both the platform and legislative level in the long term; the only thing that’s certain about privacy is that there will continue to be uncertainty. A privacy partner can help you navigate the always evolving world of data privacy with ease, and our Data Foundations offering is designed to help brands build data maturity to meet the demands of a new era, including increased privacy scrutiny.

In a broad sense, laying the foundation of a first-party data strategy will enable a clearer understanding of your audience. Meanwhile, new solutions on the horizon like Topics and FLEDGE will help brands mitigate risk and continue to deliver relevant content to their audiences. But marketers shouldn’t wait for tech giants to implement new solutions before they act. Those who build and enhance the core components and practices of a customer-centric marketing strategy will be better positioned for a world without third-party cookies and thrive in the privacy-first era.

We might speculate as to other reasons why the deadline has changed, but we can be confident that—whether from a privacy or commercial perspective—the proposed solutions haven’t met expectations. This is actually encouraging because we should expect a 2024 solution that doesn’t compromise on privacy or commercial performance.

But what does this mean for digital marketing? What changes? How do we position ourselves with this delay? There are things we know and things we don’t, but we can prepare for both. And one thing is for certain, the worst possible tactic is doing nothing. 

Here’s what we do know:

• Marketing on Google owned and operated properties (Search, YouTube and Maps) remains unchanged given its use of first party, rather than third party cookies.
• Audience (re)targeting, measurement and attribution will change, but we don’t know when or how.
• Life goes on within walled gardens, but with an increased focus on the value of first-party data across industry leaders like Google, Meta, Amazon, LinkedIn and TikTok.
• Elsewhere in the industry, there’s an expectation that the adoption of so-called “solutions”—clean rooms, ID resolution, SaaS marketing clouds, contextual—will slow down.

We agree that increased first-party data focus is the best move for marketers and agencies. This is a gift that cements the foundation of fully consented first-party data as part of the overall data strategy. 

The postponement is not an excuse to just keep doing digital marketing as we’ve always done it.  That’s a “fat and happy” symptom and a one-way ticket to extinction. Indeed, any lost opportunity to explore and learn new avenues is a waste.  That’s not to say we need to spend this extra time trying to maintain the status quo. Embracing regulatory and tech change as a driver rather than a business impediment is a competitive advantage.  

Here’s a recap of the Death of the 3P cookie timeline:

• 2018: DoubleClick ID files redacted
• 2019: Privacy Sandbox is announced
• 2020: Third-party cookie deprecation announced (targeting 2022) 
• January 2021: Google commits to Privacy Sandbox and Federated Learning of Cohorts (FLoC)
• March 2021: Google announces that it will not allow “alternate identifiers”
• June 2021: Google announces Chrome will stop supporting 3P cookies by end of 2023
• July 2022: Google Chrome has delayed 3P Cookie deprecation to 2024

How many more delays do we face? It doesn’t matter.  We’re already in a precarious situation that common sense says we don’t leave untouched.

One of the most recognizable personalities in the digital analytics industry, Avinash Kaushik, said, “Most browsers have allowed you to block third-party cookies since the dawn of the internet. A cluster of people (like me) have taken advantage of that option.” (Chrome is the last of the most popular browsers to have no restrictions on third-party data storage like cookies). “So your current third-party cookie tracking based audience and measurement at the minimum already has a signal quality degradation built in,” Kaushik goes on to say.

These are the unignorable signals of change. More than ever, be prepared.