How Generative AI and Machine Learning Are Revolutionizing Customer Engagement

2023 was the year of AI. With over 100 million weekly active users, OpenAI’s ChatGPT is easily one of the most popular sites on the internet and demonstrates just how much of an impact generative AI technology has had on our world. Part of that impact took place on the business front. In fact, in a McKinsey global survey, 40% of C-suite execs said their organizations will increase their investment in AI. Big brands have already begun to make big bets on AI, like Allstate’s ABIe, a chatbot aimed at helping business owners find the right insurance for their needs, or Coca-Cola’s “Create Real Magic” campaign which used DALL-E to power user-generated images that could be featured on their digital billboards in New York and London. While these usages sought to innovate using generative AI, the real power of this technology begins to appear when we look at how it can be used to completely transform the customer relationship.

The Rise of Generative AI and Machine Learning

Generative AI and machine learning are not new concepts. The technology has been around and in use for decades, dating back to the 50’s and the days of Alan Turing and Arthur Samuel, pioneers in computing and artificial intelligence. Machine Learning is a branch of computer science that focuses on building systems that learn or improve performance based on the data they consume. It’s a type of Artificial Intelligence that tries to imitate the way humans learn to gradually improve itself. Generative AI is a brand of Artificial Intelligence that uses machine learning algorithms to generate new content based on the patterns and insights learned from its training dataset. It tries to imitate the way humans create and communicate, developing content that feels and sounds like a human was behind it.

While both of these have been around for years, Generative AI has really only been a recent development. The first generative pre-trained transformer (GPT), which is a type of large language model (LLM) was created back in 2018 by OpenAI, but it wasn’t really until the release of GPT-3 in 2020 that these programs began to make real waves. By putting this powerful tool in the hands of the general public, imaginations began to run wild with what was possible with the assistance of this type of AI. With the introduction of DALL-E to generate images based on natural language text prompts released a year later, people knew this technology would change the world as they knew it.

Bringing AI into the Business World

Generative AI has certainly brought a lot of fear to people when it comes to the business world. Many were afraid their jobs would be made obsolete and their business would be overrun by AIs. While it certainly has made an impact and will still have further implications for how businesses are run and the types of jobs they can perform, more than anything else, Generative AIs can be immensely useful tools when deployed properly.

With the employment of robust data platforms like BigQuery and Redshift, customer data has never been more attainable. Businesses can learn everything about their customers, from basic demographics to deep behavioural and psychographic attributes, to really understand who their customers are, what motivates them, what challenges they face, and how their business can help them. This ties in closely with how businesses engage with modern customers and how personalized that experience is. Right now that personalization is… ok. It’s certainly better than no personalization at all but for most brands, there is still a lack of human touch that is critical to effectively engaging their consumers.

This is where generative AI’s true power comes out. Instead of mass-deploying a coupon code to a certain segment of customers, you can personalize it on an individual level. The message, the product, the discount, all of it can be presented to the customer in the way that most effectively aligns with what you know about them. It can demonstrate your business cares about them on an individual level, speaks to them like a human being, and gives them an offer that is valuable to their unique needs.

Right now these capabilities are being used on platforms like Spotify with their AI DJ and Warner Bros. Discovery with their integration of Amazon Personalize into their content app, but these are still the tip of the iceberg.

Efficiency and Innovation

With robust strategic architecture mapping, customer research, and design thinking methodologies, brands can leverage generative AI for their business in ways not possible before. Imagine completely transforming your digital ecosystem to create a unified, high-quality, and consistent customer experience powered by data-driven decision-making. Utilizing machine learning to scour through your consumer database, identifying trends, unique traits, and whatever desirable attributes are important for your business, a generative AI can be trained on all of that information, as well as your entire product or service offering, and now can connect with your customers in the most effective way, offering them value that matters to them on an individual level rather than generalized segmentation. It can provide your employees with a detailed list of motivators and detractors for prospects and suggestions for how to drive a conversation with them that will be most likely to yield a conversion. It can entirely customize a loyalty member’s experience with the program by transforming not only the text content but even the visuals and layout to better appeal to their tastes and give them the experience they prefer.

By combining generative AI with existing technology and integrating with tools you already use, you can effectively allow those systems to speak to each other, to shift and transform and adapt to each individual customer’s needs, and deliver an innovative customer experience like no other to help grow your business.

Ethical Considerations

Of course, as we navigate the complexities of AI in business, ethical AI practices should remain paramount. A commitment to transparency and customer privacy that respects user data while delivering exceptional experiences is critical for the successful implementation of AI-powered customer engagement. Considerations for artists and authors should also factor into the choice of platform to utilize to ensure no copyright materials are used when generating new images and content.

Looking forward, the possibilities for AI and machine learning in business are limitless, with the potential to redefine industries and customer interactions in profound ways. The journey of integrating AI into business strategies is ongoing, and the landscape is continually evolving. That’s why it’s important to have a comprehensive strategy in place to successfully navigate this new frontier, transforming challenges into opportunities for growth and innovation.

Engage with Us

To explore how you can leverage generative AI and machine learning to transform your customer engagement and drive your business forward, connect with me through LinkedIn or inquires@nictaylor.ca.

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