Create memorable, personalised content that meets consumer demand with Adobe GenStudio for Performance Marketing
Patrick Brown
10-14-2024
Study: scale personalisation, enhance engagement, and build consumer trust with generative AI.
Marketing teams are under major pressure.
Demand for personalised content is skyrocketing while marketing budgets are tightening. Marketers must deliver engaging, effective campaigns with timely and relevant content across audiences, channels and platforms. Simply put, they need to do more — and they need to do it faster.
Generative AI represents a transformative force for enterprise content production, offering vast potential to scale creative output and unprecedented opportunities for brand differentiation and business value. It can help organisations accelerate content velocity, drive competitive advantage and realise previously unachievable marketing goals, such as true 1:1 personalisation — if it’s implemented strategically.
We surveyed 310 marketers and 702 consumers to help marketers leverage content personalisation tools and meet the growing demand for campaign personalisation. This research explores their perceptions of tailored content, including the use of AI in marketing campaigns, and analyses how these views differ across demographics and marketing channels.
Key findings
80 percent of marketers surveyed believe that creating personalised content at scale is achievable, yet nearly two in three find it daunting.
Almost one in five (19 percent) marketer respondents agree that AI-powered personalisation will increase consumer brand loyalty.
Consumers studied want to share past purchases (56 percent) and products viewed (53 percent) for personalised content.
Three in four (75 percent) consumers surveyed agree that knowing content was AI-produced would either improve or not impact their likelihood of engaging with it.
Content personalisation through the eyes of marketers
As businesses strive to connect with their customers online, the importance of content personalisation to meet individual needs cannot be overstated. To capture and hold their audience’s attention, brands must personalise their messaging and scale their marketing campaigns to deliver personalisation for a variety of segments and personas across multiple products and sub-products. While nearly two-thirds of marketers surveyed find content creation at such a scale daunting, 74 percent of small business marketers surveyed believe it is achievable. AI-powered content generation tools, such as Adobe GenStudio for Performance Marketing, offer an effective solution for creatives and marketers to streamline, accelerate, and scale the creation process.
Adobe research reveals that marketers believe digital personalisation stands on three pivotal pillars: crafting relevant content (74 percent), achieving targeted delivery (69 percent) — delivering the right message to the right person at the right time through optimal marketing channels — and gaining a deep understanding of customer profiles, desires, and behaviours (52 percent). These insights empower marketers to tailor their paid social ads and enable them to forge more meaningful connections with their audiences, leading to increased brand loyalty.
Insights and personalisation are intertwined when it comes to strengthening consumer relationships. 97 percent of marketers surveyed agree that personalisation leads to stronger customer relationships. But what do they believe are the most valuable data points, and how do they expect content creation for personalisation to shift in 2025?
Our study asked marketers which data they find most valuable for precisely targeting their customers. Insights such as past purchases (48 percent), products viewed (45 percent), life stage (44 percent), website visits (37 percent), and location (37 percent) were all highlighted in the top five. Enterprise marketers surveyed rank website visits and products viewed as the most critical data points for content personalisation (48 percent). Understanding these data points can make a significant difference in crafting personalised and impactful marketing campaigns.
How personalised content will evolve in 2025
Looking ahead, respondents shared their predictions on how personalised content will evolve this year. The future of personalised marketing is tied to advancements in technology, particularly in AI. Over a third of predictions referenced generative AI trends, with AI-generated visuals and text tailored to individual users and AI-powered recommendations leading the charge (both 55 percent), illustrating a significant shift towards more nuanced and responsive content personalisation tools.
Generational differences
Examining generational differences, over one in three Gen Z marketers (37 percent) agree that we will see the development of ethical guidelines for AI-powered personalisation in 2025. This highlights a growing awareness and prioritisation of ethical considerations in the use of AI amongst younger marketers. As AI technologies evolve, so does the critical conversation around privacy, bias, and user trust.
AI-powered personalisation
This emphasis on ethics is balanced by the clear benefits of AI-powered personalisation. When asked about the potential of AI-powered personalisation to improve customer experiences, over three in five marketers (62 percent) surveyed pinpointed increased efficiency and speed of service as the top benefit. This was closely followed by more relevant product recommendations (55 percent), highlighting the importance of marketing efficiency tools. The emphasis on efficiency demonstrates that marketers are continuously seeking ways to optimise and streamline their strategies.
These advancements in AI, combined with strategic campaign personalisation, allow marketing professionals to enhance customer experiences and refine their journeys. As a testament to this evolution, nearly three in 10 (29 percent) marketers surveyed expect AI-powered personalisation to reduce friction in the customer journey, and almost one in five (19 percent) believe it will significantly boost brand loyalty. Integrating these insights into several marketing channels, such as paid social ads, can further optimise marketing campaigns, ensuring they are more effective and impactful for your desired audience.
Unlocking ROI with Adobe GenStudio for Performance Marketing’s AI-powered content generation
Within Adobe’s Global Marketing Organisation (GMO), like other modern marketing organisations, we face some daunting content challenges, including customer expectations, channel growth and ROI optimisation. Unlike most others, though, we have a unique ability — and responsibility — to build marketing solutions to solve real marketing problems with our product teams.
Adobe’s GMO needs to generate huge amounts of fresh content, launch global campaigns across regions, test assets at scale and track real-time performance, all while maintaining efficiency. Tasked with personalising campaigns across hundreds of customer segments and creating demand for enormous content volume, we realised that traditional production and delivery methods couldn’t take us where we needed to go. So, we looked to our creative and digital experience experts and collaborated to turn a vision into a reality.
Adobe GenStudio for Performance Marketing is a generative AI-first application that helps teams quickly create, activate and measure on-brand campaign content. The technology’s agility and scalability, combined with brand guardrails, allow marketers to self-serve on-brand content to deliver relevant, personalised experiences built on performance data and executed at speed.
The tool supercharges creatives and empowers marketers, enabling creative ownership and unlocking the power of team partnership. Creatives are free to focus on bigger things — less rote production, more strategic ideas — while marketers can think more deeply about the brand and how they work with creative teams.
“Across all industries, there is an insatiable demand for content as customers expect every encounter with a brand to be personalised,” said Heather Freeland, chief brand officer at Adobe. “Marketing teams are struggling to keep up with the volume of visuals and copy needed to deliver campaigns at greater scale and speed across audiences, channels and markets.”
“Just when this challenge seemed insurmountable, the emergence of generative AI is presenting creative and marketing teams with a new way to keep pace with customer demands while also breaking through with their brands.”
The content challenges we faced
Adobe's GMO is a massive operation. The team orchestrates sophisticated campaigns across multiple channels and markets, sending billions of emails every year and targeting diverse audience segments worldwide in more than 40 languages.
Like many other enterprise marketing organisations in today’s content-hungry world, we faced obstacles. Our traditional production methods bottlenecked our workflows and slowed our entire marketing ecosystem. We could not effectively produce the sheer content volume required to deliver personalised, timely and effective marketing at scale.
Among other limitations, the inability to generate enough content and variations meant:
Challenges in conducting comprehensive testing and using sophisticated optimisation algorithms
Difficulty serving diverse audience segments because of insufficient relevant content and limited resources
According to Adobe research, 59% of marketing teams report content creation challenges similar to the ones we faced due to overwhelming demands and requests on creative teams.
“There is an insatiable demand for content as customers expect every encounter with a brand to be personalised. The emergence of generative AI is presenting creative and marketing teams with a new way to keep pace with customer demands while also breaking through with their brands.”
— Heather Freeland, Chief Brand Officer, Adobe
Consumer perceptions towards personalised content
For marketers to create successful, personalised content — whether paid social ads or comprehensive marketing campaigns — they need to understand it through the eyes of the consumer, as different demographics will have different preferences. Understanding what content personalisation customers value most enables marketers to craft materials that resonate, build trust, and foster loyalty, positioning them as the brand of choice in a competitive landscape. But what matters most to consumers?
Personalised promotions/sales were ranked the most important by those surveyed (60 percent), followed by relevant product recommendations (35 percent), early access to new releases (24 percent), and access to exclusive content/experiences (21 percent).
Consumers recognise the value of brands using their data to personalise content, but they also actively set boundaries for how brands implement this. An overwhelming 98 percent of consumer respondents revealed they desire personalised experiences but demand control over the process. For these purposes, the top data points consumers surveyed want to share include past purchases (56 percent), products they’ve viewed (53 percent), their gender (47 percent), age (41 percent), and language (37 percent). While most generations are comfortable sharing their past purchases, Millennials uniquely prefer to share the products they have viewed (54 percent).
Transparency in content personalisation tools and AI is also advantageous to consumers. According to our survey, three in four (75 percent) respondents agree that knowing content was AI-generated would either improve or not impact their likelihood of engaging. Additionally, the majority — 52 percent — feel confident that they could identify AI-produced content, with Gen Z being the most confident (63 percent) and Baby Boomers the least confident (32 percent).
How to reach each generation with personalised content
The research provides valuable insights into the reasons for content personalisation and practical strategies for reaching different generations across various industries and marketing channels.
Breaking down the research by generation, Gen Z respondents show a higher affinity for personalised content from the consumer electronics industry, particularly music and video games (44 percent), more than any other industry. This contrasts with Gen X, who prefer personalisation in retail industry content, specifically from grocery stores (35 percent). By aligning content with generational interests, marketers can leverage tools like Adobe GenStudio for Performance Marketing to generate content at scale, enabling personalised experiences that enhance engagement and drive conversions across target demographics.
Our research shows that Millennials prefer personalised email campaigns (50 percent) and website content (40 percent), while Gen Z values social media personalisation (54 percent). Overall, respondents who favor social media for personalised content seek recommendations based on products they've viewed (62 percent). Marketers can leverage these insights by tailoring their strategies: email campaigns to engage Millennials and targeted social media ads for Gen Z.
In retail industries such as clothing, consumers prefer email-delivered (60 percent) tailored to their specific interests (61 percent) and want to share past purchase data (61 percent) to facilitate this. Similarly, electronics shoppers respond best to emails (60 percent) featuring content tailored to their interests (67 percent) and are willing to share their past purchase data (69 percent) for this purpose. Employing targeted campaign personalisation strategies enables marketers to fine-tune their approaches for each sector, ensuring their initiatives resonate with the intended audience and build long-term brand loyalty.
Generative AI applications for specific marketing use cases
Conducting large-scale email and paid social testing for large campaigns was difficult, primarily because of the lack of content variations we could generate, given budget and time constraints. Failing to optimise content from performance data led to lower engagement rates and conversion metrics. When testing was possible, we could only test two versions of the subject line and preheader rather than the whole email. For paid media, we could often only create one or two variations, making it hard to utilise social platform targeting capabilities.
Solution
GenStudio for Performance Marketing creates at least four variations of each requested asset, providing different headlines, subjects and body copy aligned to target personas and products. This solution lets us quickly generate and test multiple content variations of entire emails and paid social ads while adhering to our brand guidelines. For email, we run A/B/n tests and multivariate analyses across different content elements, including subject lines, body copy, images and calls to action. For paid social, we use Facebook and Instagram algorithms to serve the right content to the right audience.
Impact
In one of our first generative AI-powered email tests, we used the tool to quickly build and test five versions of an Adobe Photoshop email. It delivered a more than 10% increase in click-through rates and a subsequent test reported a 57% increase in click rates for an Adobe Illustrator email. This content creation speed also allowed us to test new subject lines for a campaign every two weeks, resulting in 8.5% higher open rates. Testing scale and speed transformed our approach to content optimisation, significantly enhancing our marketing performance and efficiency.
8.5% increase in open rates with email testing
2. Creating new, unique content for untapped audiences
Challenge
Limited resources made creating personalised content difficult for diverse audience segments, resulting in missed opportunities and poor engagement across our entire customer base. For example, the lifecycle marketing team needed to serve 12 distinct audiences for our North American acquisition programmes, but due to a content shortage, we were often restricted to serving only six. We could advertise 13 products broadly, but we lacked persona-specific assets to create differentiated messaging and content for each persona across social platforms.
Solution
Content creation powered by generative AI gives our marketers the speed and agility to target more audiences with content tailored to their preferences. Our tool enables easy personalisation by using the same prompt and changing the target persona, creating on-brand variations across channels for different audiences.
Impact
We’re engaging more of our customer base with relevant content, driving superior marketing outcomes across diverse audience segments. Our lifecycle marketing team has doubled the distinct email experiences they provide for our North American acquisition campaigns, regularly reaching all 12 audiences and accelerating our revenue targets. For paid media, the product allows us to create enough content for social platform algorithms to deliver the right content to the right audience consistently.
Accelerate and improve your marketing content with generative AI
Adobe GenStudio for Performance Marketing is a game changer for the modern digital marketer. Our marketing teams now produce more on-brand assets more quickly for paid social ads and marketing emails. This means better customer journeys through greater personalisation and increased ROI by reducing fatigue and increasing the volume and diversity of content in each programme.
With our solution, the GMO team can test email and paid social at scale, dramatically increasing click-through and open rates and they can also create unique content for untapped audiences, improving marketing outcomes across segments.
Patrick Brown is the vice president of growth marketing and insights at Adobe. He focuses on driving sustainable global growth through acquisition and engagement marketing motions. His responsibilities include leading a global media operation across B2C and B2B segments, a marketing performance analytics practice, a marketing planning and ROI function and a marketing engineering practice.
Methodology
We surveyed over 1,000 UK residents (310 marketers and 702 consumers) to explore how different groups perceive personalized content. At a 95 percent confidence level, the consumer study has a four percent margin of error, while the marketer study has a six percent margin of error. Because this exploratory research relied on self-reported data, it's important to acknowledge that respondents may have biases or discrepancies between their answers and their actual experiences.
