Table of Contents
Introduction
1. GenAI as a New Storyteller
1.1. Lexus Using GenAI
2. Why do Marketers Need to Focus on a Customized Approach?
2.1. Personalization at Scale
2.2. Sentiment Analysis
2.3. Churn Rate Reduction
3. Ethical Implications for GenAI
3.1. Copyright Obscurities
3.2. Downside of Deepfake
Between the Lines
Introduction
In recent years, generative AI (GenAI) has revolutionized the marketing and communication industries as it enables B2B businesses to connect with their customers and clients in brand-new ways. This change enables marketing professionals to generate AI-based content, and target-oriented ads, along with predicting customers’s behavior. By harnessing the capabilities of GenAI, you can unlock a new realm of innovation and eradicate the traditional paradigm of storytelling.
We are well aware that storytelling is not just an art but a strategic tool that has the potential to captivate specific target audiences, build trust and loyalty, and establish a brand in this competitive world.
In today’s exclusive MarTech Cube, we will learn about the emergence of generative AI in storytelling and how it can be used to revolutionize the marketing and communication industries.
1. GenAI as a New Storyteller
The emergence of GenAI in storytelling will make it easier for marketers to organize their thoughts and optimize their writing, designing, and video editing work, but it will not replace the traditional methods of human creativity and organization.
The good part of GenAI is that it can nurture and develop a better story by understanding the audience’s data, such as qualification levels, regional languages, ethnicity, or demographics.
When we talk about Gen AI storytelling, we must not forget the two most important technologies that help in generating content: natural language processing and machine learning.
Natural language processing (NLP) can understand and interpret human language; this implies that machines, tools, or software can recognize words and phrases and understand the meaning behind them. For instance, when we say “beat around the bush,” a human can understand the meaning, but machines, tools, or software need to be fed and trained to understand such idioms and terminologies.
Machine learning (ML) allows the machines, tools, or software to form the data provided by the data operation team, improve the data, or feed more data over time to make correct predictions and informed decisions in the future.
1.1. Lexus Using GenAI
For a better understanding of how GenAI works as a storyteller, let’s consider an example:
In 2018, an automobile company, Lexus, revealed an advertisement that was entirely scripted by artificial intelligence (AI).
According to Lexus’s general manager for Europe, Michael Tripp, this was an experiment on how advertisers and marketers can use AI in the creative process. This experiment was pulled off beautifully by Oscar-winner Kevin McDonald, technical partner Visual Voice, ad agency The & Partnership, and IBM Watson.
The company started by feeding the AI model data from 15 years of Cannes Lion award-winning ads and 10 years of the best ads in the ‘luxury’ sector and comprehending how humans make decisions and the use of appropriate human emotions in every action or reaction.
After inputting the data, the script was out with footnotes and details of each scene; the GenAI software also explained why the scene was added and what the emotions behind it were. The script also specifies the main character’s emotions, camera angles, and audio elements to accentuate the advertisement.
The Lexus team was quite impressed and surprised by the potential of such a clear and clarified script written by AI, which was popularly acclaimed by audiences.
2. Why do Marketers Need to Focus on a Customized Approach?
As a marketer, it is essential to learn and understand the best use of GenAI algorithms to elevate business output while being aware of the transformation they can leverage when used at the right place and time. It is often witnessed that AI tools produce content without a deep understanding of your audience and brand, which implies missing the mark of touching the audience’s pain points.
The power of transforming the GenAI model is to give a detailed structure to your business, such as values, statistics, market positions, customer interaction, products and services, and many more.
This level of customized approach will ensure that every piece of content authenticates your brand and speaks to a heart-to-mind conversation with your audience. In this section, we will focus on the customized approach that manufacturers need to interact with a well-fed GenAI model:
2.1. Personalization at Scale
Marketers can scale up their marketing campaigns by using GenAI. By feeding online advertising and social media data, which will help you understand your potential customers and content needs, and keep up with your competitors, you can feed GenAI models for a personalized approach. In the long run, marketers can use GenAI to approach each user with individual content such as text notifications, images, or specific IP addresses to promote your brand’s products and services that cater to your audience’s needs and desires.
2.2. Sentiment Analysis
The most common use of GenAI is to detect how clients and stakeholders are responding to your brand’s value and story on social media and other communication channels. This AI-generated approach will give you the power to drive meaningful conversions around the most trending topics and nudge your customers to buy your products and services, developing an emotional bond with your brand.
2.3. Churn Rate Reduction
It is important to know your customers, react to their preferences, and stay a step ahead to keep them engaged with your brand. With the help of advanced language models, you can eliminate the risks of higher churn rates by identifying and analyzing customers’ values, churn risk, and tenure, tackle these issues with the right set of actors, and retain existing customers. The role of GenAI is to identify these potential churn drivers, help manufacturers define the KPIs along with specifications for the customer journey, and reduce the risk of customer churn by 20%.
3. Ethical Implications for GenAI
As GenAI can craft compelling narratives without understanding the consequences, marketers have to come to terms with ethical concerns. For the longest time, we have witnessed the potential threats that this technology can bring, such as manipulating consumer perceptions, spreading misinformation, or data bias.
To curb such instances, marketers need to understand ethical practices and adhere to government rules and regulations on data privacy and data security before proceeding with implementing any GenAI model or tool. This section would be an exemplified version of the ethical implications that manufacturers need to follow before adopting generative AI in their B2B manufacturing business:
3.1. Copyright Obscurities
The most ethical concern around genAI is the unaccountability of the authorship and copyright of contents generated from AI tools and software. Marketers are always in the loop about who has the creative rights to the AI-generated work, as GenAI models often use references and complex logs to propagate themselves and update with the times. The use of copyright-generated data could lead your company to copyright infringement and a penalty of more than $500. However, the persistent issue of copywriting content can be partially eliminated if your GenAI model is fed with proper data and good training by AI professionals. For the other half, marketers have to be vigilant and double-check every piece of content to make sure it is not pirated.
3.2. Downside of Deepfake
Deepfake is one of the most recent technologies that emerged as a promotional and innovative tool or piece of software in the field of B2B marketing, which allows marketers to create highly realistic video, audio, and images without the need for actual and authorized recording. However, the ethical dilemma behind deepfake content is simply to create and spread misinformation that will affect people’s mindsets while purchasing any products or services from a certain brand. The solution is to check and update your company’s privacy and data security terms and conditions regularly and add robust security measures to detect any content on social media posing your brand name or logo with deepfakes.
Between the Lines
The effectiveness of GenAI relies on the quality of the data it receives and the prompt requests it receives from the other end. However, the data pool that is used to feed the AI model contains many opinions and falsehoods that need to be filtered out in layers to get the best brand story, just like Lexus.
As we continue to explore the synergy between storytelling and Gen AI, marketers will unlock new potential in developing a strategic plan while keeping in mind ethical considerations and limitations. With this vision, the future of storytelling through GenAI will provide more insightful and interactive content than ever before.
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