After fan-favourite playlists like Discover Weekly and the annual Wrapped campaign, Spotify unveiled its AI DJ earlier this year. In Spotify’s words, “The DJ is a personalised AI guide that knows you and your music taste so well that it can choose what to play for you.”
At the heart of the AI DJ’s personalisation are Generative AI and Voice AI technology. Fashion ecommerce site Myntra transformed the ways of online shopping by announcing its ChatGPT-powered search feature, MyFashionGPT. Instead of browsing through the app for different options, users can simply type in relevant keywords, like “wedding function” and the feature will curate results best matching the shopper’s unique preferences. Another AI-based intelligent companion in the Myntra app, MyStylist, provides users with styling tips and advice in 11 languages, making fashion more accessible.
Spotify and Myntra are just two of many successful cases of leveraging Generative AI to enhance customer experiences. Visually appealing content is an essential part of present-day marketing, and brands are focusing more of their investments in this technology to elevate their customer experiences. Let’s examine how Generative AI can help companies automate their processes and increase customer engagement and satisfaction.
How can companies use Generative AI to enhance customer experience?
Here are some ways companies can utilise GenAI technology to create meaningful customer experiences that leave a lasting impression.
GenAI for Personalisation
In a recent BCG survey of CMOs, 67% of respondents said they are exploring Generative AI for personalisation. Based on customers’ browsing history and purchases, GenAI can offer product recommendations. “It can analyse customer data to create highly personalised content, including marketing messages and emails tailored to individual preferences and behaviours,” says Anas Hemaid, CX Director at Lucidya, a CXM platform.
Improved Customer Satisfaction
When offering hyper-personalised content based on customer data, the shopping experience becomes more satisfactory for the customer. Additionally, GenAI can identify areas where satisfaction is lacking and take targeted actions to address these issues. Brands can also use it to monitor real-time sentiment and react promptly to any negative feedback.
Increased Customer Engagement
Generative AI can use customer preferences to offer their engaging content—65% or marketing teams are already using the technology for content creation. The types of content can vary from blogs to social media posts that keep the customer intrigued and drawn towards the brand. Further, brands can implement GenAI-powered chatbots and virtual assistants for instant and round-the-clock customer engagement. Customers appreciate speed in today’s era of digital communication.
GenAI for Customer Service
Customers do not like to wait in long queues or on call lines to get their complaints resolved. Since the onset of Generative AI, chatbots have replaced human customer service representatives and call centre agents to offer service 24*7 and efficiently and quickly resolve basic issues like billing enquiries, etc. This frees up human agents to focus on more complex tickets. Additionally, GenAI tools like Lucidya can help companies get real-time sentiment analysis, helping agents adapt their responses and improve the customer service experience.
Enhanced Customer Journey
Gartner reported that 48% of organisations are using Generative AI to build customer personas and enhance customer journeys. A customer’s journey starts from the step of discovering a brand and goes all the way to making a purchase and recommending to more people. Through this entire process, a customer could drop out due to multiple reasons, identifying which is a complex task. As Generative AI automates the entire customer journey and identifies patterns, it becomes faster and easier to gain insights at all stages and address the customer’s pain points. This leads to an overall optimised customer journey.
Challenges in Using GenAI for CX
The “set and forget” approach isn’t the best when it comes to leveraging Generative AI, or AI in general, for marketing functions. Marketers must take time to understand the purpose they are trying to achieve with the use of AI, and what would the best methods be for their brand’s goals. It’s essential to set realistic expectations and be mindful of implementation and scalability challenges.
Privacy and Security
While Generative AI is adept at processing vast amounts of customer data at speed, the sheer volume of information, if not managed with care, can lead to risks to data privacy and security. Hemaid suggests brands should invest in robust data encryption, comply with data protection regulations and be transparent with customers about data usage to avoid security breaches.
Biases in Generative AI
Large language models are fed upon massive arrays of data from around the world, and it is very easy for bias to creep into their databases. In fact, ChatGPT has been in the news constantly for displaying inaccuracies and biases in its responses. “Generative AI models are not infallible,” says Hemaid, and this can be reflected in their recommendations. To avoid this, he suggests, brands must continually monitor AI accuracy, refine models, and provide diverse training data to minimise biases.
All said and done, Generative AI has shown to be more beneficial than to have caused challenges. For instance, Lucidya’s AI-powered assistant Luci has impressed brands with its ability to provide recommendations based on real scenarios and logically organising pain points. “Luci can complete a week’s worth of work in just a couple of minutes,” says one of Lucidya’s clients. With AI-based assistants, companies can accurately monitor interactions instantly, which helps provide better services and improve social presence.