Let’s look at how Adobe GenStudio redefines performance marketing.

Adobe GenStudio for Performance Marketing is designed around the needs of performance marketers, whose roles often require scaling content creation and delivery. For larger organizations with well-established marketing teams, this solution can support tactical initiatives or even serve as a foundation for dedicated performance marketing groups. For corporate-level organizations with smaller marketing budgets, it offers a way to enable more in-house services, driving greater agility and efficiency.

Adobe has likewise recognized the critical role agencies play in helping organizations navigate the creative space. Teams like ours are uniquely positioned to support clients in two vital ways: first, by implementing tools and adapting business processes to harness the potential of generative AI; and second, by ensuring strong alignment with organizational and regulatory frameworks. As the GenAI landscape is evolving so quickly, the implementation of these frameworks needs to be revisited frequently.

GenStudio for Performance Marketing puts powerful features at marketers’ fingertips.

Looking at the tool, I was keen to understand where it fits into the existing Adobe GenStudio and Content Supply Chain toolset. The existing toolset (with applications such as Adobe Workfront, Adobe Creative Cloud, and Adobe Experience Manager Assets) provides a comprehensive, scalable, end-to-end solution for any business. With GenStudio for Performance Marketing, Adobe brings together key features across all these solutions to support performance marketing teams create content within the context of its content supply chain workflows.

The main menu of GenStudio for Performance Marketing is divided into two sections: one for actions and utilities, which the Performance Marketer can use to create and measure outbound content, and another for shared resources, including brands, personas and products. There are currently two roles, marketer and system manager, although I expect these to become more granular before release. The marketer creates outbound content and can review its performance, while the system manager can configure the shared resources such as brands, products, and personas and approve content for publication.

The setup of the shared resources provides critical guardrails for AI-generated content. A System Manager can drag and drop their existing approved organizational brand guidelines into the interface. The system will detect from the document key information including tone of voice, brand values and other guidelines. These can also be edited manually. Similarly, personas or brands can be created manually or by upload. Currently there is no mechanism to connect to a PIM or data file for a list of products.

A marketer can create content from a template, similar to creation in Adobe Experience Manager. When a user creates content, they are presented with options to select a brand, persona and product. Additionally, they can select an image from the asset library and enter a prompt that will be used to generate the content. The system will then generate four versions of the content. Each version is individually scored for compliance to the brand guidelines and can be edited or regenerated. A marketer can then select one or more for approval for publication or export. This supports a case where multiple versions may be delivered for A/B testing.

The asset library simplifies content reuse by saving variations for future campaigns, making it easier to manage and organize creative assets. Assets can be assigned directly to campaigns, streamlining the process for marketers. While template configuration currently relies on HTML, the tool makes it easy to scale and customize content for different needs.

Future updates will further enhance GenStudio for Performance Marketing’s impact.

Adobe Firefly integration for asset generation is expected in upcoming updates, further expanding creative possibilities. Unlike other generative AI options on the market, Firefly is purpose-built for enterprise use. It offers commercial safety and provides precise controls to ensure training data is accurate and responsibly sourced, making it a standout choice for businesses.

The activation mechanism is not yet enabled in the current release. Still, the product documentation suggests that publishing to existing Adobe products will be supported, as will a generic CSV export. Adobe has also announced activation partners including Google’s Campaign Manager 360, Meta, Microsoft Advertising, Snap and TikTok.
 

The real power of the solution will come by providing data and to marketers on the performance of their content—for example, tracking impressions, click-throughs and the ROI of each—enabling them to make decisions in real time. The current release allows connection to Meta, but future connections to the Google Marketing Platform, TikTok, and Adobe platforms will give the marketer real-time insights into campaign and content performance. This would also be a great candidate for automation so that the marketer can define boundaries to change or publish, such as the ability to push winners via Auto-Allocation in Adobe Target.

Adobe has embraced interoperability in all its enterprise platforms, and GenStudio for Performance Marketing is no exception. In my ideal world, customers and partners could then build their own interfaces for publishing and insights. If these extensions can be made available on Adobe Exchange, the power and leverage of the platform will grow very quickly. Additionally, I feel there are options for external tools to integrate and extend, such as a wider generative integration or finely grained workflows such as those provided by our own solution Monks.Flow.

Final thoughts.

Overall, GenStudio for Performance Marketing embodies a genuine shift in Marketing Operations. It is built with the user and organization in mind and matches the modern-day enterprise's goals. It is still early, and the gen AI platform will evolve quickly, but it is refreshing to see Adobe's investment prepared for the next stage in the GenAI journey.

I always look forward to Advertising Week LATAM as it’s a rare opportunity to catch up with old friends and colleagues face-to-face—and in the city I call home, no less. Despite partially coinciding with the Day of the Dead, I have to say the event was more alive than ever, as I bumped into every imaginable brand manager, marketing director, client and podcaster. Representatives from world-class brands like Netflix, Spotify, Toyota were in attendance, and not a single seat was empty by the time Sir Martin Sorrell stepped onto the stage. Needless to say, our time spent in meetings and attending (and hosting) a diverse range of sessions has left us with some valuable insights. Here are some of those takeaways. 

As digital environments expand, AI is the key to maintaining brand relevance.

In today’s changing landscape, CMOs need to align strategies with transformative technology to optimize operations, improve customer engagement and drive conversion. That was the theme explored by our Co-CEO, Content Bruno Lambertini and Associate Vice President, Innovation Technology Carlos Tejeda as they took the stage on October 31. Rather than a conventional session, their discussion served as an exploration, beginning with an overview of the challenges that businesses encounter in the present day. 

"We surveyed top CMOs from major global brands, and they all agreed on four key points,” Lambertini explained to introduce the topic. “Firstly, the complexity of making decisions and seeing short-term results. Secondly, the fragmented media landscape makes it difficult to determine which channels truly yield outcomes. Thirdly, the delicate nature of brand reputation. And last but not least, how do we take advantage of AI?”

The truth is that as digital environments expand, driving conversions can feel like finding a needle in a haystack. For Lambertini, social media is the key (and I wholeheartedly agree).  As marketers, we constantly ponder how brands can secure or expand their market position, enhance brand equity and drive business performance in today’s technological context. The answer lies in two key aspects, the first of which can be summed up in one word: intimacy. No, not the romantic kind, but the kind that harnesses the power of genuine human connections and community. Audiences crave a sense of belonging, and by establishing a brand that fosters this feeling, we lay the foundation for success. An important consideration: social media is the only space where this can happen on a large scale. The second aspect involves how we achieve this.

AI helps us understand what is organically happening online, what people care about and the spaces where they connect with each other, both within and outside the brand context. We can then use these insights to inform the creation of assets. “Working with Meta, we analyzed input drivers for our AI algorithm to generate the best result. This allowed us to produce 500 assets, so when the brand noticed creative fatigue in the campaign, we already had these new assets prepared and sorted by their probability of success,” Tejeda exemplified.

Furthermore, AI assists community managers by handling repetitive queries at scale, in real-time, and in a personalized manner. The cherry on top? AI enhances measurement by enabling us to extract learnings from a centralized source that connects platforms and contains information from all our marketing efforts.

In times of global uncertainty, activation and performance take center stage.

Speaking of the nature of AI, S4 Capital Executive Chairman Sir Martin Sorrell sat down with Insider’s Director, Matías Stetson, to chat about this particular topic as it relates to the prevailing macroeconomic and political conditions in the region. Amid global uncertainties and geographical fragmentation, Sorrell explained, businesses need to carefully pick their territories. He went on to say: “If I look at the world now, I’m very bullish on North and South America.”

The second consideration is digital transformation. With businesses becoming more cautious not only in choosing their markets but in their general spending, we need to look at digital platforms. “Clients are becoming much more short-term in their thinking, so activation and performance are important,” said Sorrell. “It is quite extraordinary that platforms are growing by 6-11% this year. The money from package goods companies has gone into the platforms, and the reason is that they see better performance, better activation, better measurements and better results from those platforms. AI is going to make them even more important than they are today.”

In summary, technological advancements and the current political and economic uncertainties have led brands to focus more on their short-term return on investment. Now, the competition revolves around acquiring and leveraging first-party data, which plays a crucial role in understanding consumer behavior and making informed business decisions. “To my mind, the best model is the Netflix model. They are the greatest proponents of hyper-personalization at scale,” said Sorrell.

That’s one of the areas where AI will have the most impact, as it transforms the way first-party data and platform signals are harnessed, decoded and utilized. When it comes to the realm of personalization and data-driven decision-making for brands, AI enhances brands’ ability to tailor their strategies to individual customers with precision and effectiveness. “We thought the web would drive personalization, but AI will take it to a totally different level. We may produce one and a half million creative assets. What took us three weeks, takes us three hours,” said Sorrell. This, coupled with the overall efficiency in areas like media buying, broadcasting and knowledge sharing, will shape the business models of brands and agencies in the years to come. 

Across industries and platforms, creative effectiveness reigns supreme.

During the two-day event, Advertising Week emphasized the importance of creativity in exploring fresh opportunities for growth across various industries and sectors. An illustrative panel by Eucerin, featuring our very own VP Creative Pablo Tajer, showcased how creativity in retail media can yield impressive returns, even when collaborating with third-party ecommerce platforms.

To distill the role of branding in retail, the speakers used a recent example of our work with the brand on the Mercado Ads platform. “We used storytelling to demystify the abundance of information we see on social media and provided consumers with accurate recommendations based on their skin type,” said Tajer. “This sector thrives on ideas and creativity. That’s why we partner with Mercado Ads and constantly push the boundaries of creativity, working on different proposals for major advertisers in the region.”

To emphasize a similar point, our VP Creative Francesco Vicenzi joined our partners at KFC Mexico and representatives from IAB to spill their secrets on creating award-winning campaigns that gain international acclaim. The key ingredients? Data, which uncovers valuable insights; creativity, which generates captivating concepts; and a comprehensive vision that brings everything together. Vicenzi exemplified this through our work on KFC’s The Battle of the Chickens: “We began by noting two important observations. Firstly, rap and freestyle ranked among the top three genres for Gen Z. Secondly, Gen Z has a fondness for promotions and discounts. These served as our starting points, and we recognized that to effectively engage with Gen Z, we needed to empower them. Thus, we provided them with a platform and space to express themselves.”

Striking a balance between short-term results and long-term brand growth.

If there’s one thing I learned from this massive event, it’s that CMOs face numerous challenges that demand immediate results without sacrificing long-term brand development. They must find a way to achieve short-term goals while also making significant contributions towards a larger impact. Those who establish robust data pipelines and effectively leverage new technologies are gaining a competitive edge, propelling their brands far ahead of the competition. It’s time to seize every opportunity within the social and digital landscape in order to become more agile, perceptive and responsive.

Performance marketers have been an underutilized resource to date, but their years of experience using AI for marketing success make them well suited to play a large role in broader AI adoption. Blind disciples of every generative AI shortcut will get burned and those resistant to change will become irrelevant. Nobody knows this more than performance marketers. 

As it relates to the digital marketing AI arms race, Google, and to a lesser extent Meta, weren’t nearly as proactive at highlighting their work relative to Microsoft (the largest investor in OpenAI, the company responsible for GPT-4). The irony is that Google and Meta had been at the forefront of incorporating their long-standing investments in AI, which was already deployed in almost every corner of Google and Meta Ads platforms and products.

Google and Meta represent nearly half of all digital ad spending in the US and represent an even larger share of the typical performance media budget. AI integration in Google and Meta has most prominently centered around machine learning algorithms for bidding and ad serving. That said, there are examples of generative AI as well (suggesting ad copy and creating distinct ad copy from permutations of existing headlines and body copy), and AI’s tentacles can be felt everywhere in the Google and Meta ad ecosystem. Prominent examples include:

• Performance Max (Google) and Advantage+ (Meta) are effectively end-to-end automated campaigns that use AI to target, generate ads and optimize toward set goals.
• Automated bidding sets dynamic bids in real time using machine learning to more efficiently optimize toward the highest ROI.
• Responsive Search Ads (Google) uses AI to mix and match different portions of copy to deliver the best permutation for the individual searcher (right ad to the right audience at the right time).
• Recent Google Marketing Live (GML) and Meta Connect 2023 conferences announced products around AI-powered assets, AI-generated images, generative AI to create ad copy and auto enhancements to text placement, brightness, etc.

In that same vein, performance marketers, most of whom earned their stripes running or overseeing Google and/or Meta Ads, are particularly well suited to guide advertisers through this next major stage in digital transformation. The nearly half decade of experience most performance marketers have both harnessing and reining in AI tools justify them playing a central role guiding marketing teams in developing and deploying generative AI adoption.

What about this experience gives performance marketers an advantage? 

• Threading the needle between uncritical adoption and complete resistance to change
• Understanding of the importance of high-quality data inputs 
• Understanding the importance of setting guardrails and tweaking those over time 

Bringing healthy skepticism to the table.

Seasoned performance marketers have had to adapt and learn new types of automation many times over, and can share their war stories. From broad match keywords, Meta auto-placements and iteration after iteration of automated bidding on Google gone awry, we’ve seemingly seen it all. Google and Meta were trailblazers in incorporating AI into ad products, and reps would very earnestly push adoption of products that could be buggy and at worst underperform manual alternatives. However, Google and Meta were also diligent about refining those products over time and performance marketers who were not willing to continue testing at all over the last few years were quickly left behind. Broad match keywords, automated bidding, Advantage+ shopping campaigns and many more products delivered more scale at comparable efficiency to non-AI driven products. 

As AI plays a more permanent role across creative, customer journey, audience identification and more, this balance will be crucial. Blind disciples of every generative AI shortcut will get burned and those resistant to change will become irrelevant. 

Garbage in = garbage out.

One of the biggest distinctions in a strong performance marketer versus a mediocre one is her understanding that the inputs to automation can have a profound effect on outcomes. Performance marketers who press the easy button and switch from hundreds of manual bids per week to auto-pilot don’t get strong results. Worse yet, they’re quick to declare, “It doesn’t work!” Data volume and quality are the foundation of an effective AI deployment strategy. Knowing which data sources to use and exclude, and which campaigns to match with each specific type of automated bidding, is a crucial skill. Performance marketers know to incorporate lead quality data to B2B auto-bidding, initiate testing on campaigns with higher conversion volumes, and not to launch immediately after a strong holiday or back to school period.

In this sense, performance marketers have years of “prompt engineering” reps without even realizing there was a name for it. Marketing organizations stand to get AI into market faster, and benefit sooner from the positive results, by tapping into that experience. 

Performance marketers are masters at fine tuning.

The last level of mastery that performance marketers have achieved has to do with learning the intricacies of the algos. We have applied max CPCs, cost caps and negative keywords to rein in the occasionally deleterious effects of AI unchecked. At a high level, AI can be fickle and human intelligence is crucial to avoid these blips. We have seen a top performing ad set stop delivering seemingly out of nowhere, only to have a minor 5% increase in ROAS target return it to normalcy. We’ve learned to mine for insights around how, why and where AI is working:

• Is stronger performance because we’re seeing increased CTR or conversion rate?
• Are we getting in front of the same audience more cost effectively or reaching a better audience?
• Did we create better ads, or did the platforms get better at matching them to the right people?

We ask these questions daily. That curiosity bordering on paranoia allows performance marketers to squeeze the most out of AI, as well as limit downside risk. 

Performance marketers have a feel for AI’s rhythms, like a mechanic knowing just which bolt to tighten to get the rattling sound in the car to stop. This mileage, or put anachronistically “human intelligence,” is tough to replicate. 

This AI mileage and its broad applications are why performance marketers should have a seat at the table. As an agency leader I’m better equipped to weigh in on how we utilize AI to address tasks, reporting, data integration, scripts and implement processes around AI because of that performance DNA.