In today's fast-paced digital landscape, brands strive to captivate their audience with compelling stories and forge authentic connections. Enter generative and predictive AI, game-changing technologies that are set to transform brand storytelling and customer engagement. In the coming year, these AI-powered tools will become indispensable for marketers, enabling them to create richer narratives, understand customer preferences better, and establish genuine connections with their target audience. Joyce Kim, CMO of $12 billion tech company Twilio even predicted that “In 12 months, call it next year this time, I really think every company, every marketing team, every sales team, this generative and predictive AI is going to be a core part of every tool that they use.” Watch the full livestream here. In this article, we break down how AI can help brands tell better stories and connect with customers in a more authentic way.
But First… What are Generative and Predictive AI?
Generative AI focuses on the ability to create new and original content, such as images, text, or even music. It uses complex algorithms and deep learning models to generate content that doesn't exist previously. Think of it as an AI "creating" something from scratch, like an artist painting a picture or a writer composing a story. Generative AI can analyze patterns, learn from existing data, and generate new outputs based on that knowledge. It's like having a creative AI assistant that can produce unique content on its own.
On the other hand, predictive AI is focused on making predictions or forecasts based on existing data. It analyzes patterns and relationships in the data to forecast future outcomes or behaviors. Predictive AI learns from historical data and uses statistical models and algorithms to make predictions about what might happen next. For example, it can analyze customer behavior data to predict which products they are more likely to purchase or forecast sales figures for the coming months. Predictive AI helps businesses make informed decisions based on data-driven insights.
In simple terms, generative AI is about creating new things, while predictive AI is about making predictions based on existing data. Generative AI is like a creative artist, inventing new content, while predictive AI is like a fortune teller, using data patterns to anticipate what might happen in the future. Both types of AI have their unique applications and play important roles in different fields and industries.
Best Ways to Use AI To Tell Better Stories:
Crafting Personalized and Engaging Narratives:
Generative AI algorithms analyze vast amounts of data, customer insights, and storytelling techniques to create personalized narratives. By tailoring stories to individual preferences and interests, brands can resonate deeply with their audience. From personalized video content to interactive storytelling experiences, generative AI empowers marketers to deliver narratives that are relevant, engaging, and uniquely meaningful to each customer.
Understanding Customer Preferences:
Predictive AI algorithms can analyze customer data, including past behaviors, purchase history, and interactions, to gain insights into customer preferences. By leveraging this information, brands can anticipate customer needs and create content that aligns with their interests. Understanding customer preferences helps brands curate stories that resonate on a personal level, fostering a stronger emotional connection with their audience. Amazon is the best example of this, using AI tools to deliver personalized shopping recommendations and dynamic pricing.
Real-time Content Optimization:
Generative AI can dynamically optimize content based on real-time customer feedback and interactions. By analyzing customer responses, sentiment, and engagement metrics, brands can adapt their storytelling in the moment, ensuring the content remains relevant and impactful. Real-time optimization enables brands to create more meaningful experiences, capturing customer attention and leaving a lasting impression. Starbucks is a pro at this, using their data from over 90 million transactions a week, spread around almost 25,000 stores worldwide to inform business decisions such as where to open new stores, and which products they should offer.
Generative AI algorithms can process and analyze vast amounts of data, including customer sentiment and emotional cues that fuel engaging, data-driven storytelling. By leveraging these insights, brands can create narratives that are backed by real-time market trends, customer preferences, and evoke the desired emotional response. AI-driven storytelling adds credibility and relevance to brand narratives, establishing trust and authenticity with the audience. On that same note, delivering stories that strike an emotional chord forge stronger bonds with customers.
Enhanced Customer Journey Mapping:
Predictive AI algorithms can analyze customer touchpoints, behaviors, and preferences to create comprehensive customer journey maps. By understanding the unique paths customers take, brands can tailor their storytelling at each touchpoint, ensuring a consistent and personalized experience. With generative and predictive AI, brands can optimize their storytelling along the entire customer journey, creating a cohesive narrative that resonates with customers at every stage. Netflix does this through it’s personalized recommendations feature. Did you know that more than 80% of what people watch on Netflix is discovered through the recommendations feature? This is proof that customer journey mapping works.
Augmenting Creativity and Inspiration:
Generative AI can serve as a valuable tool for creative inspiration. By generating ideas, visuals, and concepts based on existing data, generative AI assists marketers in exploring new storytelling possibilities. This technology sparks creativity, helping brands uncover fresh angles, and craft innovative narratives that captivate and inspire their audience.