Deciphering Customer Voices with Gen AI and CDPs (Customer Data Platform)
By Gowtami Mohanty and Vinay Mony
In today’s rapidly evolving digital landscape, the traditional boundaries of businesses are being redrawn. More businesses, across sectors, are migrating online, transforming the ways companies interact with customers. While this shift offers unprecedented convenience and scalability, it also presents the unique challenge of replicating the personal touch associated with face-to-face interactions. It’s this human element, the feeling of being recognized and valued, that businesses can recreate with Customer Data Platforms (CDP) and generative AI (Gen AI).
A CDP is a sophisticated tool that is used to collect, orchestrate, segment, and analyze customer data whereas Gen AI is a technology capable of generating text data within a given context and interpret customer feedback from various sources such as surveys, social media, reviews, and customer support interactions and extract customer insights. Integrating Gen AI and a Customer Data Platform (CDP) can create a powerful synergy for understanding customer voices and enhancing overall customer experience.
Think of a local shopkeeper who greets you with a smile, asks about your day, and knows exactly what you came in for. That’s the kind of personal touch we are talking about. Imagine if businesses could do that for every customer, no matter how many there are. That’s where customer data platforms (CDP) play a pivotal role.
Think of CDP as a digital shopkeeper that not only remembers your past purchases and preferences but also predicts what you might need next. Businesses use all this information to make sure every interaction with you is personal, just like with the local shopkeeper, making you feel valued.
But understanding people’s emotions isn’t always easy because emotions are complex and vary from person to person. Sometimes it’s even hard to tell if someone is happy or sad just by looking at them. Deciphering emotions in the digital realm can be equally challenging.
Imagine trying to understand a friend’s feelings through a text message. Sometimes, the words they use might not fully convey their true emotions. They might say they are fine, but their tone or choice of words could suggest otherwise. It’s like trying to read between the lines. This becomes even more complicated because marketers are trying to connect with a large and diverse audience to provide this audience with personalized experiences.
Within the context of customer data platforms, the Next Best Experience, Offer, and Action (NBx), typically relies on one-way data streams flowing into the CDP from various channels like web and mobile. However, this one-way flow neglects the crucial aspects of bidirectional feedback and siloed reviews. This oversight results in higher churn rates, decreased conversion rates, and missed opportunities for precise personalization. Without the capability to discern sentiments, CDP struggles to identify at-risk customers, leaving them vulnerable to disengagement.
Leveraging Customer AI for Long-Term Engagement
An automobile company is preparing for the sustained success of its latest electric vehicle (EV) in the market. Anticipating the need for a prolonged customer engagement strategy, the company aims to identify and nurture potential customers over a 90-day period, particularly those with low propensity scores, to increase the car’s sales. The automobile company seeks to maintain a consistent and effective approach to engaging potential customers over an extended timeframe of 90 days. By targeting customers with low propensity scores, the company aims to convert these leads into EV car buyers through personalized marketing efforts and incentives.
The automobile company continues to utilize Adobe Sensei’s customer AI to address this long-term engagement challenge. By extending the prediction timeframe to 90 days and focusing on customers with low propensity scores, Customer AI enables the company to develop tailored marketing strategies aimed at nurturing these leads and ultimately driving EV car sales.
Through the strategic utilization of customer AI and a tailored 90-day engagement strategy, the automobile company strengthens its position in the electric vehicle market and secures long-term success for the EV car. By targeting customers with low propensity scores and nurturing them through personalized marketing efforts over an extended timeframe, the automobile company maximizes conversion rates, enhances customer satisfaction, and solidifies its competitive edge in the industry.
By combining Generative AI’s capabilities in understanding and responding to natural language with CDP’s ability to manage and analyze vast amounts of customer data, businesses can achieve a deeper understanding of customer needs and preferences, leading to more personalized interactions.
Gen AI can help analyze extensive datasets, unveiling concealed patterns and deciphering drivers of customer behavior, facilitating well-informed decision-making. Bespoke propensity models can be engineered with Gen AI, enabling precise segmentation and targeted outreach based on individual behaviors. Predictive analytics and automated decision-making can be integrated within the CDP to forecast customer churn, optimize lifetime value, and automate real-time personalization. Generative AI algorithms can be employed to craft personalized customer experiences, generating tailored recommendations, messages, and offers. Generative AI models can assess historical data to derive predictive insights, enabling proactive engagement with personalized offers and marketing campaigns. AI-enhanced insights can be leveraged to empower developers with profound understanding of customer data, facilitating trend identification, insight refinement, and informed decision-making in their development endeavors. Natural language interfaces can be powered by AI to streamline data access and analysis for developers, fostering quicker and more intuitive interaction with customer data and boosting productivity. Gen AI technology within the Customer Data Platform can be implemented to dynamically segment audiences and elevate customer experiences.
While the integration of Gen AI into CDPs promises to revolutionize marketing effectiveness, it also presents a horizon of future trends and challenges. With emerging technologies such as real-time sentiment analysis and hyper-personalized recommendations, the landscape of customer engagement is undergoing a seismic shift. However, navigating through the evolving regulatory environment, data governance issues, and the demand for continuous innovation poses significant hurdles for businesses. Yet, by proactively addressing these challenges and embracing emerging trends, companies can harness the full potential of Gen AI within their CDP strategies, propelling them to new heights of success in the ever-evolving marketing landscape.
With Gen AI and customer data platforms by our side, we embark on a mission to make every online interaction a deeply personal and meaningful experience. Let’s turn the digital world into a place where genuine connections flourish, where each click and tap feel like a conversation with an old friend.
So, as we journey forward, let’s keep innovating in the vast expanse of the digital marketplace. Because in the end, it’s not just about bytes and pixels – it’s about touching hearts and brightening souls, one click at a time, let’s weave threads of lasting connection.
(The author is Gowtami Mohanty – Director, Customer Data Platforms, Merkle and Vinay Mony – Vice President, CXM – Insights & Analytics, Merkle, and the views expressed in this article are his own)
