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First Impressions on Adobe GenStudio for Performance Marketing

First Impressions on Adobe GenStudio for Performance Marketing

AI AI, AI Consulting, Data, Digital transformation, Platform 4 min read
Profile picture for user Tim.Goodman

Written by
Tim Goodman
CTO Solutions

A keyboard being showing behind ripped paper

We live in an interesting time marked by the rise of AI, economic challenges, and the pressure of compliance and security on budgets. The proliferation of multiple channels, diverse formats, and the need for personalization at scale has created an ever-growing demand for content.

Generative AI provides a clear opportunity for Adobe to innovate around performance marketing use cases to address these increasing demands with solutions like Adobe GenStudio for Performance Marketing. I’ve had the privilege to try the product early, getting a sense of how it enables marketers to leverage GenAI to produce fresh, relevant content themselves—often at a micro level—while still adhering to organizational requirements. Below are my impressions, including both the features I’m most excited about and additions I hope to see in the future.

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 prompt selection

The prompt selection

Initial image generations

Initial image generations

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.

Monk Thoughts 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 gen AI journey.
Tim Goodman
A review of Adobe GenStudio for Performance which helps marketers understand how to use generative AI to do performance marketing. Adobe GenStudio for Performance A first look at Adobe GenStudio for Performance AI Generative AI performance marketing Adobe adobe experience cloud Platform Data AI Consulting Digital transformation AI

Delivering Data-Driven Experiences Through WeChat

Delivering Data-Driven Experiences Through WeChat

4 min read
Profile picture for user Ron Lee

Written by
Ron Lee
Technical Director

Delivering Data-Driven Experiences Through WeChat

Consumers around the world crave personalization. In fact, 40.6% of Chinese millennial consumers don’t mind paying a premium for a personalized product. In discussing consumers’ attraction toward luxury goods with Jing Daily, Longchamp Creative Director Sophie Delafontaine hints at why personalization resonates so well today. “Nowadays, people are not looking for a bag, they’re looking for something special, something which really reflects who they are,” she said. “And this is particularly true when speaking of customers buying luxury bags.”

But if people look for products or experiences that reflect themselves, developing those impactful experiences can seem particularly challenging in a country so wide and vast as China: just 15% of its population is equal to the UK, Germany and France combined. By investing in personalization, your brand becomes better fit to further segment those audiences into actionable demographics that inspire and co-collaborate in new, emotionally resonant experiences.

To start, consider how to make a more meaningful impact throughout the customer decision journey (CDJ) and strategize around how that builds into a first-party relationship with individual users. This mindset is key for the approach we take in the work that we do, utilizing the full suite of Adobe’s Experience Cloud to deliver memorable experiences that emotionally resonate.

The Need for Data-Driven Creative Experiences

Some might see “data-driven creative” as an oxymoron, but that couldn’t be further from the truth. Brands exist to serve their customers with the utmost care through the following simple reminder: behind every data point sits a real human being with a voice. That said, the aggregated data from your Adobe Analytics backend can help you better understand what resonates with consumers across the WeChat ecosystem, preparing your team to better understand the growing needs of Chinese consumers and confidently optimize their journeys.

Monk Thoughts Behind every data point sits a real human being with a voice.

It’s obvious that analytics can help determine which product design performs best or whether KPIs have been met. But more interesting—and this is where brands must direct more attention—is how you can use consumer interaction data to pre-test and iterate upon an idea, essentially turning users into contributors to your product design.

This process enables you to focus your efforts on key strategic areas that build both innovation and momentum in incremental steps. In developing an app or web platform, you can use these analytics to identify and remove steps that don’t add value to the user experience and adopt a more customer-obsessed approach as you go.

Here’s a breakdown of the process that has worked for us in A/B testing audiences and specific experiences built for them, using Adobe Target in a four-week sprint cycle. First, spend the first week building a hypothesis around your user—this is where personas and research come into play. Next, test and learn your prototype by launching it for the audience segments matching these personas. Once you have a minimum of about 15,000 data points, you should have enough insights to build and launch the app. Post-launch, make sure to continue to test and iterate for effectiveness. Be mindful, as this bond creates a conversation between the user and the product designers and helps inform upcoming consumer needs.

Identify Triggers and Intent for Impact

Effective personalization requires you to rethink what you thought you knew about demographics. What’s important isn’t just what Tencent UserID provides—what matters is the content that clicks with a user, and any personalized platform should recognize these preferences across a creatively differentiated experience. Adobe does this seamlessly via its Experience Cloud’s Visitor ID: a fixed, persistent identifier per WeChat user that visits your mini-program, WeChat Ecom Store or other digital properties of the brand. This allows you to build comprehensive profiles of your visitors based on their actions and interests, augmenting the data from WeChat.

IMG_6815.00_02_06_13.Still007(1)

Consumers are more comfortable providing data when they understand there’s a fair tradeoff. From a user experience perspective, aim for transparency in how your platform translates user interactions into recommendations and new content. The PUMA “run my way” campaign began by acquiring the user’s OpenID via a QR code scan, allowing for personalization by giving each user a choice in the color and finish of their puma avatar as well as options for the soundtrack. After running through the scene via a treadmill, users conclude the experience with a personalized video takeaway.

So, how can you execute with a platform that achieves something similar? First, move away from a one-size-fits-all mentality. Adobe Analytics and Target let you identify and segment audiences for testing, leveraging touchpoints throughout the customer decision journey to inform creative design and tailoring the user experience toward business outcomes. By turning successful tests into perpetual personalization activities, you can continue to serve your audiences their preferred experience through Adobe Target.

This part of the process trips up those who haven’t properly set up an attribution model or strategy for success, leading some to consider abandoning personalization altogether. It begs the question: if businesses continue to inundate users with the same, irrelevant ads again and again through careless retargeting in external channels, were they ever really personalizing in the first place?

Personalization is your chance to build the experience your users have always wanted on your own properties. With the right toolset, this is a tangible and practical thing to do. The mighty size of the Chinese consumer market truly enables even the most sophisticated personalization powered by machine learning in Adobe Target. It requires a lot of data, but in return offers automated targeting of your experiences to just the audiences most likely to respond. And it has the power to change the messaging and creative of any experience to the options that work best for a particular segment of the audience — all without a data analyst’s involvement.

Personalization done properly actually empowers the user to craft their own product and design their own journey to their own liking. Through a data-driven creative process that focuses its strategy on assisting your WeChat users, you can drive more meaningful, impactful, memorable user experiences.

Oleg Sidorenko, Solutions Director EMEA at MediaMonks, contributed to this piece.

As an important conduit between consumers and brands in China, brands can personalize WeChat experiences to built impact in ecommerce and retail. Delivering Data-Driven Experiences Through WeChat Turn audiences into active participants in the experiences they enjoy.
WeChat adobe adobe experience cloud adobe experience manager social commerce ecommerce retail social payments

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