Generative AI and Digital Marketing

The Utility of Generative AI for Digital Marketing 

An overwhelming majority of us are using Generative AI in one way or the other. Does ChatGPT ring a bell? 

Tech industry bigwigs have a lot of good things to say about the purpose and potential of Generative AI, including the groundbreaking transformation for climate change, healthcare, finance, media, and so much more. 

Elon Musk talks about the significance of Generative AI in the context of creativity, underscoring that among the modern technological tools that reinforce creativity, generative AI is the culmination of them all. 

“Generative AI is the most powerful tool for creativity that has ever been created. It has the potential to unleash a new era of human innovation.” 

Elon Musk

Musk referring to Generative AI as a ‘New era of human innovation’ does highlight it as a groundbreaking tool for creativity, far ahead of anything that exists. It will supplement human intelligence to make big waves and surmount the conventional limitations of innovation and creativity. Generative AI will incentivize creative ventures, including Digital Marketing. 

What is Generative AI and how does it work?

Generative AI or Generative Artificial Intelligence are deep learning models supported by large AI models, known as foundation models. It is an incredible technology that helps users generate fresh data/ content based on the data these models are trained on. The content could be high-resolution images, text, code or other content.  

The foundation models that support generative AI can multi-task and perform creative tasks such as generating Questions and Answers, writing a summary, categorizing and sub-categorizing information and much more. These models do not require intense training and can be conveniently adapted for specific use cases with minimal demo data.

Generative AI uses the Machine Learning model for the patterns and associations in a dataset of content created by human beings. These learned patterns help develop the novel content. Supervised learning is the most popular technique to train any Generative AI model. In supervised learning, the model learns with the help of human-generated content and labels. It then produces data identical to the human-generated content congruent with similar labels. 

Techniques of Generative AI 

• Generative Adversarial Networks (GANs): GANs consist of two neural networks, a generator and a discriminator, trained in sequence. With this adversarial training process, generative AI models can improve their ability to create realistic and new outputs.
• Variational Autoencoders (VAEs): VAEs are a type of autoencoder that learns a probabilistic mapping between input data and a latent space. VAEs help with image creation and regeneration. 
• Recurrent Neural Networks (RNNs) and LSTMs: Types of neural networks that can learn sequential patterns. Among the other utilities, they help with music generation and Natural Language Processing. 
• Transformers: The most talked about one post the advent of Chat GPT- Generative Pre-trained Transformer. Trained on colossal data sets and calibrated for particular tasks. Transformers can generate meaningful and contextual text.

Application of Generative AI on Digital Marketing

Generative AI is already transforming the execution of digital marketing by changing how we create, analyze and bring the best out of digital marketing strategies. Unlike conventional marketing dependent on human prediction and machine analysis, Generative AI gives a manifold boost to the creativity and efficiency of a machine. It automates content creation, graphics and the complete marketing strategy by using algorithms and machine learning. 

Generative AI is reforming how we produce content- from simply creating personalized content towards generating content through predictive analysis. It gives brands a competitive advantage over businesses not harnessing the fascinating capabilities of Generative AI. Let’s dig deeper and explore some of the most effective use cases of Generative AI for digital marketing. 

• Predictive analysis- Starting with the use we mentioned above, predictive analysis is an immensely strong attribute of Generative AI, not to mention a total game changer for digital marketing. It facilitates marketers to build and implement predictive models in foreseeing potential consumer behaviour and trends. This helps them to fine-tune and optimize their marketing strategies accordingly. 
• Personalization- The advent of predictive analysis does not undermine the significance of personalization in digital marketing. Generative AI helps marketers create personalized data at a large scale and within seconds. It analyses customer data, tastes & preferences and accordingly creates customized recommendations, product descriptions, ads and more to resonate well with customers and prospects. This degree of customization improves customer experiences and conversion to a great extent. 
• Content Optimization- Content across social media platforms and search engines needs optimization through smart implementation of SEO practices and a correct understanding of the algorithm. Generative AI assists with the same by generating metadata and meta tags, suggesting internal and external linking and keywords, analyzing user engagement, page views, CTR and more. 
• Advertisements- Generative AI does an excellent job of generating ad creativity including graphics, videos, copy, jingles and more for well-defined targeted audiences. It analyses past performance and engagement metrics and deciphers the most relevant and effective ad attributes to create fresh versions and optimize the campaign performance. 
• Customer segmentation- Generative AI combined with data analytics can tremendously help with accurate and precise customer segmentation. As data analytics helps with customer segmentation, Generative AI produces well-targeted content and ads for every segment. This helps marketers augment the effectiveness of their marketing efforts as they deliver meaningful messages to specifically targeted consumers and prospects. 
• Enhances customer experience- Generative AI combined with data analytics offers groundbreaking customer experience, making it more personalized and interactive. The AI-powered chatbots reinforced with customer data analysis, customise product and service-related suggestions, respond to queries in real-time and give meaningful information. These AI-supported chatbots can answer common questions, provide product recommendations, and even facilitate transactions, boosting customer satisfaction and retention. 

Conclusion

How imperative is the inclusion of Generative AI in the Martech stack of any business? Businesses are already implementing and taking advantage of the speed, precision and massive quantity of data offered by Generative AI. Not implementing it would only cause businesses to lose out on one of the most important resources among many others; time. 

The continued advances in AI to facilitate marketing marks a paradigm shift from simple targeting and retargeting. Marketers can resonate better with customer intent and decipher their journey more accurately. This helps in gaining useful insights and taking prompt action.  

Although Generative AI has the potential to strengthen and change the way digital marketing is executed from scratch, it doesn’t eliminate the importance of human intervention and supervision. Without human intelligence and creativity, it is not possible to harness the full potential and drive the best results out of Generative AI.