The Fifth Marketing Revolution?
For centuries, it was print - from Ancient Greece and Rome with outdoor posters and murals - finally mass produced with the advent of magazines during the Industrial Revolution. Followed nearly a half a century later with television that brought brands to life in your home. Then the digital revolution and the internet changed everything with personalization and search. Followed with what could be considered the fourth revolution with social media and influencer marketing. Today the landscape of marketing content is undergoing a seismic shift, driven by the rapid advancement and integration of AI. This feels like the next revolution. Couple this with brands building ‘digital twins’ in order to surround every aspect of their business with data, this transformative phase is not just redefining the tools and techniques used by marketers but also reshaping the very fabric of how content is conceptualized, created, and delivered. As we peer into the future, it’s evident that AI will play a pivotal role, offering both challenges and opportunities for brands and their marketing partners.
The Rise of the Digital Twin and How It Will Drive Marketing Strategy
In the era of digital transformation, businesses across industries are increasingly investing in digital twins to innovate, optimize operations, and enhance decision-making processes. A digital twin is a virtual replica of a physical object, process, or system that can be used for various purposes, including simulation, analysis, and control. “What organizations are ultimately trying to do and what we’re trying to do in media marketing is create a digital twin of our organization, which is a simulation of the flow of goods and services across our supply chain,” says Daniel Hulme, chief executive officer Satalia and chief AI officer at WPP. As artificial intelligence continues to evolve, its integration with digital twins is set to redefine the boundaries of digital simulation and real-time predictive analytics, offering unprecedented opportunities and challenges for companies worldwide. Everything from using real-time data from media and point of sale platforms to drive personalization in product development to developing the customer journey virtually and testing brand messaging and content in a simulated environment to better optimize the message at every customer touchpoint. How many times have we heard truly tone deaf messages from brands and wonder who reviewed them? homes.com from this years Super Bowl? The Kendall Jenner Pepsi debacle from a few years ago? Yikes! However, extracting the data is not the exciting part it’s the human ability to leverage that data to explain the world that is new and innovative.
How are brands leveraging this data and AI to improve the performance of content?
The revolution in content creation is driven by the necessity for brands to produce content that is not only creative and engaging but also personalized and scalable. AI's role in this transformation cannot be overstated. It offers unprecedented opportunities for enhancing creativity, streamlining production processes, and achieving personalization at scale.
Enhanced Creativity and Efficiency
At the forefront, AI technologies are set to enhance creativity and efficiency in content creation. Through AI-driven tools, marketers can now generate ideas, create drafts, and even produce finished content pieces faster than ever before. These tools leverage natural language processing and machine learning algorithms to understand context, mimic human writing styles, and generate content that resonates with target audiences. This increased efficiency allows marketers to focus on strategy and creativity, rather than getting bogged down in the mechanics of content production. However, with AI quickly acquiring buzzword status, there has been an enormous leap in the quantum of just average work, particularly through the course of the last year. Jacqueline Pavich, Publicis global client lead, Publicis APAC said to Campaign Asia, “It can’t be just left to the machine. There has to be a human element. AI can expedite and accelerate how we reach consumers, but generative AI ensures that we can create content that is entertaining and hyper-personalized. My hope is that the combination will result in infinite possibilities to engage our end consumers.”
Personalization at Scale
AI’s ability to analyze vast amounts of data in real-time means that personalized content creation is becoming more feasible at scale. By understanding individual preferences, behaviors, and interactions, AI can help marketers tailor content to meet the unique needs and interests of each consumer. Constant advancements in technology are getting the delivery of truly personalized video and text content in real-time within reach. One McKinsey report estimates that companies that excel at delivering personalization generate 40% more revenue than average. Research has shown that personalized digital assets can consistently deliver more than 30% higher rates of in-market performance, including CTR and VTRs. This level of personalization not only enhances user engagement but also significantly improves the effectiveness and also significantly reduces the time and cost involved in content production.
Visual Content and Beyond
As mentioned above, the impact of AI is not limited to text-based content. AI-driven tools are also revolutionizing the creation of visual content, including images, videos, and interactive media. Through techniques like generative adversarial networks, AI can create realistic and engaging visual content, opening new avenues for marketers to capture audience attention. Additionally, the rise of AI in areas such as virtual reality and augmented reality offers novel ways to create immersive experiences that can elevate brand storytelling to new heights. Garrett DeLorm Head of production at Camp + King told LBB recently, “I’m particularly interested in tracking the progress of generative AI for video, 3D asset generation, and model training. These advancements will enable us to develop creative solutions that were previously cost-prohibitive or even impossible”
But what’s next?
Predictive & Generative Content Creation
AI can not only predict the type of content that will resonate with a specific audience but also generate textual, visual, and video content tailored to those predictions. Advanced generative AI could create highly personalized and engaging content at scale, something that is just beginning to be explored. Imagine someone is scrolling through IG after they just looked at the latest Nike configurator and Lebron is wearing the exact version of these custom configured shoes in your social feed? Every element that it takes to do this, is currently available. The challenge is the process of connecting these signals in real time and delivering without latency.
Emotion Detection & Sentiment Analysis in Real-Time
Beyond analyzing text for sentiment, AI technologies are advancing in detecting emotions through voice tones, facial expressions, and even biometric signals. This can enable marketers to adjust their strategies in real-time during campaigns or customer service interactions to better suit the mood and emotional state of their audience. Every personal device has an HD camera. Connecting that input to technology that can detect emotions can better serve customers from everything to personal shopping to customer service interactions.
Hyper-Personalized User Experiences
While personalization is not new, AI has the potential to take it to an entirely new level. By analyzing data from a wide range of sources, AI can help create hyper-personalized shopping experiences, product recommendations, and marketing messages that adapt in real-time to user behavior and preferences. By connecting the data coming from consumers with those created by the brands digital twin, hyper-personalization could drive the product design.
Augmented Reality and Virtual Reality Experiences
By integrating AI with AR and VR, marketers can create immersive experiences that are personalized and interactive. This can transform how customers interact with products before purchasing, offering virtual try-ons, tours, and more, which is still underutilized in marketing strategies.
Behavioral Prediction and Influence Modeling
AI can be used to develop sophisticated models that predict consumer behavior and identify the best ways to influence decision-making processes. This could include identifying the optimal timing for marketing messages, understanding the impact of social factors on consumer choices, and more. This is the element of AI that no one is really doing at scale. Driving and informing decisions is the true power of AI. Receiving data signals as they are happening - news, weather, etc - using machines to analyze and predict what behaviors will occur and then delivering personalized content in real-time? That’s pretty powerful stuff.
Challenges and Considerations
Computational Power
Advanced AI models, especially those involving deep learning, require significant computational resources for training and inference. Real-time applications, such as emotion detection or hyper-personalized experiences, demand rapid processing that can exceed the capabilities of current hardware, especially in mobile or edge computing environments.
Data Storage and Management
AI systems rely on vast amounts of data to train and operate effectively. The storage, retrieval, and real-time processing of this data can be challenging, requiring sophisticated data management systems and significant storage capacity, which can be costly and complex to maintain.
Energy Consumption
High computational demands also translate to high energy consumption, which is a concern both from a cost perspective and an environmental impact viewpoint. Running large-scale AI applications continuously can be unsustainable without efficient energy use solutions.
Latency
For applications like AR/VR experiences and real-time customer interactions, low latency is critical to ensure a seamless and responsive user experience. However, processing large volumes of data in real time can introduce delays, especially when relying on cloud computing resources that are physically distant from the end-user.
Network Bandwidth
Transmitting large amounts of data between servers, cloud infrastructure, and end-user devices requires high network bandwidth. As AI applications become more data-intensive, existing network infrastructure may struggle to support the necessary data flow without lag or disruption, affecting the performance of AI applications.
Scalability
Scaling AI applications to accommodate growing data volumes and an increasing number of users can be challenging. It requires not only more powerful and efficient hardware but also software that can dynamically adjust to changing loads without compromising performance.
Security and Privacy
Processing sensitive user data for personalized marketing raises significant security and privacy concerns. Ensuring the integrity and confidentiality of this data while leveraging it for AI applications requires robust security measures, which can be computationally intensive and complex to implement.
Adaptation and Skill Development
Content creation with AI necessitates adaptation and continuous skill development for marketing and brand professionals. Understanding and leveraging AI tools will become an essential skill, requiring marketers to stay abreast of technological advancements and their implications for content strategy. Shifting from traditional marketing strategies and production practices to data-led and customer-centric content principles should go hand-in-hand with re-education - for agencies and brands. Moreover, the ability to blend AI capabilities with human creativity and insight will become a critical differentiator in crafting compelling marketing narratives. Paraphrasing from one of the many panels on AI in Marketing at Cannes last year - AI won’t take your job but someone who understands it will.
The future of content creation is intrinsically linked with the evolution of AI technologies. As AI continues to evolve, it promises to unlock unprecedented opportunities for creativity, personalization, and engagement in marketing. However, success in this new landscape will depend on marketers’ ability to harness AI’s potential responsibly and innovatively, balancing technology’s power with the human touch that resonates with audiences. Embracing the future means embracing AI, not as a replacement for human creativity but as a partner in pushing the boundaries of what’s possible and delivering the sheer scale of what’s needed. Ensuring that we are ready for how quickly this will become the new normal - from education and up-skilling, managing ethical challenges, to investment in the infrastructure required to power this new world - requires close collaboration between brands, platforms and tech providers.