The impressive output of generative AI has led some to voice concerns about whether their livelihoods are in jeopardy. Creativity, after all, has long been considered a strictly human skill.

But creatives aren’t about to lose their jobs to robot overlords who can spin strings of text into pixelated gold. To the contrary, these tools—which rely on human input and some level of artistic aptitude to really shine—are unlocking creative potential and helping people bring their concepts to life in new ways. This outlook prompted the Labs.Monks, our research and development team, to explore how generative AI can uplevel the work of our teams and our clients.

“We’ve been playing with this technology for a while, and after it began to trend, we’ve been getting more and more questions about it,” says Geert Eichhorn, Innovation Director and Head of Labs. For instance: a lot can be said about the future of content creation aided by AI, but how could today’s tools integrate into a present-day production pipeline? 

Looking for an answer, the Labs.Monks collaborated with animators and illustrators on our team to develop a prototype production workflow that blends traditional animation methods with cutting-edge AI technology. The result is an animated film trailer made using a fraction of the time and resources that a typical, frame-by-frame animation of its length would require.

Learn to live with the algorithm.

Ancestor Saga is a 2D-animated side project focused on a central question: what if people in the Viking Age realized they were living in a simulation? After learning that their purpose in life is to entertain the gods, will they accept their new reality, or put an end to the world by bringing about Ragnarök?

The theme might feel familiar to anyone trying to make sense of the increasingly algorithmic world we’ve suddenly found ourselves in. “We wanted to tell a story that could integrate with the tech we’re using: virtual worlds and virtual people,” says Samuel Snider-Held, Creative Technologist. Associate Creative Director Joan Llabata takes this thought further, citing some of the challenges faced when humans and AI don’t quite connect. “There’s some space where we need to find the best way to communicate with the machine effectively,” he says.

When using generative AI, a bespoke approach is best.

That challenge of getting humans and AI to play nice demonstrates the need for a team like the Labs.Monks to experiment with the tools that are available. While off-the-shelf tools are great for empowering individual creators, integrating them into team pipelines requires a more custom solution.

AI is designed to do specific tasks very, very well. Projects that involve multiple capabilities and phases call for a workflow that can integrate a variety of generative AI to fulfill different goals throughout. With an animation project, this means plugging into creative concepting, storyboarding, sound and of course animating the visuals.

In our case, says Snider-Held, “We wanted to explore how AI could allow us to do the work we really want to do, even if the time or the budget isn’t there.” He found that while our animation team loves classic, frame-by-frame animation, the method is often overlooked because it is slower to produce and less cost-efficient than other ways of animating. 

Now the team had a clear goal: orchestrate an AI-based workflow that could output a frame-by-frame animation in record time, without compromising quality. They took inspiration from rotoscoping, a method used by animators like Ralph Baskhi, in which an artist traces images over existing footage. This task of translating an existing recording from one style to another was ideal for image-to-image generative AI. In addition, the team used AI technology to develop background designs and read out the animation’s voiceover.

Generative AI isn’t a radical departure from tradition.

The team began by recording a 3D character model in a virtual setting, capturing a variety of poses for an illustrator to trace over. These visuals were then used to train the AI model on how to draw the character in different movements. “If you draw about five frames, you have enough to teach a neural network how to paint the others,” says Snider-Held, noting that it’s important to select frames that are different from one another so the AI can pick up on various forms, shapes and poses.

In addition to rotoscoping virtual production, the team also experimented with live-action stock footage. Being able to use two different types of visual source material baked extra flexibility into the process; teams could mix and match the different methods according to their specific needs or abilities. Fantastical creatures might be captured more easily in virtual production, while a team lacking in their ability to animate lifelike movements may prefer using live-action film as a base. “You get better acting from footage versus a 3D model, but the visual output is ultimately the same,” says Snider-Held.

Much like how that process emulated classic rotoscoping by hand, other ways of integrating AI followed a traditional animation process, albeit with some additional steps here and there. For example, the storyboarding phase is important for visualizing which types of shots or animations are needed for a specific sequence. In addition to pondering that, the team also planned which kinds of AI would be best for generating this or that shot.

Using Stable Diffusion—a kind of generative AI that translates a text prompt into an image—allowed the team to create a large volume of backgrounds that they could swap in and out to test how they looked. “You can explore a lot in this phase,” says Snider-Held.

As for developing backgrounds in particular, “It’s like describing the shot you want to a director of photography,” says Llabata. He was able to test hundreds of different environments, camera angles, artistic styles, lighting and more, all with relative ease.

Unlock efficiencies and long-term gains.

The findings above hit on perhaps the biggest gain that a generative AI-powered workflow can provide: greater flexibility throughout the life of a creative project. Being able to generate 60 frames in one minute—rather than one frame in 60 minutes—makes it incredibly easy to pivot or change things up in the blink of an eye.

It doesn’t require a sophisticated hardware setup either, further making content creation accessible to teams of all sizes. “You don’t need a giant server or cloud computing,” says Eichhorn. “A reasonably good gaming PC can churn out assets like backdrops quickly.” Still, more complex uses of AI like rotoscoping may require more power.

The flexibility unlocked by integrating generative AI into a team’s pipeline continues to pay dividends beyond the life of a single project. “If you have a project whose scope is really big, the effort and money you spent in that R&D is compounded in value over time,” says Snider-Held, noting that whether a brand wants to make 10 animations or 30, the steps to lay down an AI-powered foundation will be roughly the same.

Experiment to find an approach that suits your needs.

Tools like stable diffusion aren’t meant to replace those in the creative field. “An AI will not achieve anything by itself,” says Llabata. Instead, these products will give teams the ability to chase more ambitious projects with fewer constraints in time and budget. Just consider how closely the creation of the Ancestor Saga trailer follows a traditional animation process, just with more efficiencies baked in. 

Such flexibility afforded by generative AI can go well beyond traditional animation.

Whatever your use case for generative AI, understand that while building tools from scratch can be challenging, the result is extremely powerful. “Our approach is that if an off-the-shelf tool is mature enough, use it. If not, create it yourself,” says Snider-Held. In addition to ensuring a tool is calibrated for their specific needs, teams who go the bespoke route will also be better poised to future proof as the technology continues to evolve at a rapid pace.

So, think you’re ready to explore what generative AI means for your field? Learn more about the ins and outs of the technology in the latest Labs Report exploring the rapid evolution of digital creation.

Owned digital products designate every digital platform whose code belongs to the brand. The terms “platforms” and “digital products” are often used interchangeably, but while the former can be mistaken for third-party channels like TikTok or IG, the latter is, in my opinion, a better name for a brand’s unique spaces. Marked by flexibility and potential for personalization, these digital products encompass everything from dotcoms to TV apps—and can serve whatever purpose brands deem necessary in meeting their goals and keeping with consumers’ desires.

Because there are no intermediaries, you can have full authority over the brand image that your digital products project. And that’s a big responsibility. What the brand experience looks and feels like on these platforms is how people will perceive your brand to be, so what should you prioritize when it comes to building your own digital products? 

Functionality, efficiency and innovation.

Back in the day, websites were unidirectional and served mostly as a source of information. Now, standards are higher. Whether we’re looking at content hubs or a smartwatch app, successful digital products must strike the right balance between functionality, efficiency and innovation. Consumers won’t stick around for websites that make it hard for them to find what they are looking for—or even worse, that don't fully work—but they will remain loyal to those that provide a seamless user experience.

That said, building functional websites from scratch is no easy feat. Because of this, many brands resort to auto-site builders—especially when it comes to ecommerce integrations. While this may temporarily fix the problem, website templates are not a permanent solution because it begs the question of whether consumers are going to be able to remember it. As they search for product options and scour through multiple tabs, will yours stand out among the rest?

Innovation is about creating the “wow” moments that will remain engraved in people’s minds, and adding interesting features that make a platform completely different from those of your competitors—even if your offering is similar. HP’s Possibility City, for example, is not just another ecommerce platform. Rather, it’s a showcase of HP’s digital printing presses that doubles as a hub to house sales events—from product presentations and webinars to one-on-one demos. And while visitors explore the brand’s lineup, the platform learns from their interests and provides them with tailored content recommendations.

Data and personalization: the next frontier of loyalty.

Provided that your platform is intuitive in its use and delightful in its appearance, the next step is to offer personalized features that make the experience truly unique. To get there, you need the data analytics infrastructure to provide valuable information about your consumers and a team of experts who can turn that into actionable insights.

I always work closely with the data team on both the company and the client side to improve our customer understanding. On one hand, a strong first-party data framework can help you identify how consumers are moving across the ecosystem—where they click, how they behave and where they find friction points. By designing around these general trends, you can deliver a more seamless experience for all.

On the other hand, individual data unlocks a new world of possibilities in terms of personalization. With Possibility City, for example, we included a virtual assistant that learns from visitor preferences—whether they’re looking for efficiency, sustainability, security or other priorities—and guides them through the brand’s offering. We also tied the platform into a CRM funnel that helps automate the closing of sales, keeping us informed of customer needs and how to improve efficiency. 

Designing around your business priority.

In addition to collaborating with data experts, my team and I work closely with the business consulting unit, as they can provide valuable insights into a brand’s digital roadmap and long-term business goals. Digital products should be built around this vision—not only to help brands achieve their goals quicker; also, to ensure their platforms are one-of-a-kind. 

In working with multiple airlines throughout my career, for example, I found that while some needs were universal, no two business models were ever alike. Options like “book a flight,” “check-in,” or “see my reservation” were common currency—but while certain brands simply wanted a functional app to help travelers organize their trips, others sought to raise the average ticket value by encouraging consumers to opt for upgrades, extra bags and other add-ons. The mere act of designing around these priorities made each platform totally different from the next. 

The bottom line is that digital products are as much the translation of your business as they are the embodiment of your brand identity. To get the most out of them, you need to understand your consumers and, above all, your own brand. In working with clients, my goal is to help them create differentiated products that drive their business forward, and it’s the brand’s values and identity that ultimately do the trick. By taking identifiable brand elements and combining them with functional, innovative and personalized digital products, we can create a truly memorable brand experience that forges deeper connections with your audience.

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.

In this Labs report, we'll uncover how Generative AI is impacting digital creation today, and will explore how to keep ahead of where the tech is going next.

In this Labs report, you’ll:

• Learn what Generative AI is and what’s currently available
• Understand how the tech works
• See the technology in real-world action
• Peek into what the future holds
• Learn how to harness its power now

Generative AI supercharges production for higher quality creative output.

In this animated trailer for an original series called "Ancestor Saga," we demonstrate how Generative AI can be applied to film production. This prototype leverages Stable Diffusion AI for generating background scenes and custom Img2Img neural networks for AI-based rotoscoping of virtual characters.

See our findings about the benefits of using generative AI, including time and labor reduction in production, in the report.

In the latest episode of IMO, Brianna Mersey, Media.Monks Associate Director of Data, sat down with Marc Laurent-Atthalin, VP Data & Digital Media at Reitmans, and Zamira Khamidova, Director of Data North America at Media.Monks, to discuss what it took to shift the traditional retail business into a modern data stack capable of enabling marketing use cases. Throughout the conversation, they shared insight into how to set your data foundation up for success, the importance of aligning stakeholders across the business, and the need for a “test and learn” mindset. If you missed the episode, we’ve got you covered—watch it in full below.

Reitmans was able to adopt such advanced analytic methods because the team had already established a strong foundation of data, making it easy to implement models that were more reactive to customer behavior and transaction histories. Marc and Zamira offered advice on how to select which data sources to start with (opt for rich, actionable data sets that give you lots to work with) and how to ensure that data is clean and reliable.

Marc also shared the importance of aligning with internal stakeholders to gain buy-in and chart the path forward. “It’s important to build a clear vision and strategy initially and communicate it properly, and then use data to build your case,” Marc said. By tying data objectives with business outcomes, his team was able to prioritize use cases and deliver results quickly, then test and iterate from there. For example, building a 360-degree view of the customer provided insights to drive conversion, fulfilling the key business need to propel growth.

When it comes to initiatives like these, treating your partner as an extension of your team is key. “Collaboration is hugely important,” Zamira said. “When it comes to data, there are lots of questions on the context—especially with historical data, so it was important for us to have two-way communication and hear back on any questions we had.” This level of regular communication also helps with further collaboration as the engagement evolves. 

So, where is Reitmans headed next? You’ll have to watch above to find out—including the brand’s plans around Web3, which is set to transform the brand-customer relationship even further. And if you’re eager for more insights from Media.Monks subject matter experts and our partners, mark your calendar for the next episode of IMO later this month.

Amazon Brand Stores offer customization and control.

Amazon sellers can build a strong customer connection through the brand store by sharing their stories and educating shoppers on the brand’s mission, values, and much more. There is no other place on Amazon where the customer experience is controlled. Competitors’ ads are not visible on the Brand Store, which allows for a more customizable experience that focuses on just the brand’s products and offerings. With the spotlight being purely on the brand, this feature is crucial to leverage compelling brand storytelling.

Set your Brand Store up for success.

Once an Amazon seller completes the Amazon Brand Registry, they’ll be able to create an Amazon Brand Store. It’s important to note that the Brand Store template should reflect the brand’s image. Amazon frequently releases new ideas for sellers to boost their revenue and customers’ loyalty, such as brand videos to show products in motion, interactive posts, and product comparison tables. By adding these components, sellers can emphasize how their products can solve the shoppers’ problems with lifestyle images and a brief brand story. 

The Brand Store should include an “About Us” section or page, which speaks on the brand’s story and competitive advantages. This allows them to establish a rapport with their shoppers and provide a more personable experience. 

Since ecommerce shoppers rely heavily on visuals to make important purchase decisions, Brand Store imagery should be a top priority for sellers. Images and videos should follow specific size requirements to avoid any store errors. Other best practices for images include showing a variety of high quality images and ordering them in a way that prioritizes the images in a specific sequence.

Successful Brand Stores should also have a user-friendly navigation menu, categorized in a way that matches the brand’s target audience needs. Since the Brand Store acts as a hub for customer browsing, I recommend all products are available and accessible through the Brand Store. 

Analyze and optimize every step of the customer journey.

Amazon Brand Stores should always be monitored and optimized based on the data and engagement. This includes updating active promotions as well as featuring new product launches and seasonal products. If the seller fails to keep the Brand Store updated, they risk losing sales and revenue. According to Amazon, on average Brand Stores updated within a 90-day window have 21% more repeat visitors and 35% higher attributed sales per visitor. With the goal of increasing sales and customer loyalty, sellers should focus on optimizing the Brand Store content to be as informative and relevant as possible. 

Last but not least, sellers are able to track their Brand Store performance and shoppers’ engagement. These metrics include but are not limited to daily visitors, page views, estimated total sales, and so much more. Reviewing these metrics can be beneficial for a seller who wants to use their Brand Store in conjunction with their other marketing efforts.

What is A/B testing?

In a digital environment where everything can be tracked and measured, testing your strategies is a no brainer. Content strategy plays a key role in driving organic traffic and converting sales, so by leveraging and optimizing your content, you can increase the chances of shoppers purchasing your product over your competitors. A/B testing is one of a handful of the best practices you can use to enhance content on the platform.

Also known as split testing, A/B testing on Amazon is a method of determining the best-performing product listing variation. By comparing two versions of the same content, you can identify the exact element that is driving purchase-ready shoppers to act, taking into account metrics such as conversion rate, sessions, and total sales. That being said, you should have a strong understanding of your current metrics, performance and challenges before building an A/B testing plan. This will allow you to have a solid base foundation before making any changes.

Start by running an A/B test experiment on Amazon.

Amazon launched its own A/B testing tool in 2019 called Manage Your Experiments, which allows US brand owners to test two variations of one product listing element. As a brand owner wanting to test different A+ content elements, you must have eligible ASINs, otherwise they will not be displayed in the A/B test experience. To be eligible, ASINs must belong to your brand, and they must have high enough traffic in their respective categories to determine content winners with confidence. 

Keep best practices for A/B testing in mind.

By following a few tips, you can begin your test experiment with confidence. Here are some recommendations:

• Strategically create a hypothesis to learn something from the experiment regardless of the outcomes.
• To get a larger sample size, experiment on high-traffic ASINs.
• Stick to making one change at a time to avoid confusion on which variables influenced the experiment outcomes. 
• Don’t stop early – you can run experiments for four, six, eight or ten weeks to ensure accurate results.

Get to know the elements of A/B testing.

Nearly any element of your A+ content can be A/B tested. However, you should use your own judgment to determine what to test based on your current performance. Consider working with an Amazon Ads Partner to strategically outline the testing method. Some variation ideas for your A/B experiment: 

• Utilize a comparison chart.
• Rearrange and update your modules and images.
• Present the same images and text using a different module layout.
• Include lifestyle images.
• Highlight one set of product features versus a different set.
• Add your brand name to the product title.
• Use different headlines to engage and motivate shoppers to learn more about your product.

Keep in mind that your experimental content should differ from the existing content, otherwise it is less likely to affect consumer behavior and you may not be able to confidently determine a winning variation. The key to a unified branding strategy is consistency, which applies to your color scheme, icons, layout, and even text fonts.

Wait for optimal data.

Patience is key here as most tests need several weeks to gather enough data to determine a winning variation. While Amazon recommends testing for eight to ten weeks, you can adjust the schedule or even turn off the test while it is running. You will start to see data within one or two weeks, although this preliminary data is not representative of the true impact of your experiment. Be sure to let your experiment run its full course before interpreting the results and making a decision. 

Gauge the effectiveness of your experiment.

While launching new marketing initiatives on Amazon can lead to an increase in traffic, you should know how to gauge the effectiveness of each initiative to dial in on what works best. 

Once your A/B test ends, you will get the following from Amazon: 

• Recommendations on which content variation is more effective
• A confidence level of the recommendations
• A confidence interval of likely outcomes from that content
• Estimated 12-month impact on sales

These insights will highlight the most effective content for your product detail pages to boost total sales and conversions for your Amazon products. By learning from these experiments, you can optimize and improve your other product listings. You might find it beneficial to run experiments during different seasonal periods as this will provide you with a better understanding of your consumers and their expectations. 

When analyzing your results, be sure to keep your audience in mind to make the most informed decision. Although it takes time and patience to run A/B tests, the optimization is worth it if you want to dominate your market. Happy testing and selling!

In this Labs report, we tap into the unique tech, perspectives and potential of the region and share some use cases that brands and marketers can apply anywhere in the world.

In this report, you will learn:

• The most influential technologies of each region
• Regional and local trends
• Attitudes toward adopting tech and innovation in the region
• How APAC relates to the rest of the world
• Takeaways to help with brand success

Zepeto Prototype: The Metaverse Reloaded

APAC’s hunger for tech and virtual innovation create an ideal set of circumstances to build a revolutionary new platform. To showcase this, we created an experience hub in APAC’s biggest metaverse platform: Zepeto.