The marketing landscape is undergoing a rapid transformation, with data and AI serving as the primary catalysts for change. Chief Marketing Officers (CMOs) must develop a comprehensive strategy for implementing Generative AI (Gen AI) to modernize their marketing operations and achieve excellence. In a recent roundtable, industry leaders explored various experimental applications of Gen AI in marketing.
In recent years, the marketing environment has evolved dramatically. The rise of data from social media platforms and IoT devices has flooded organizations with vast information—often overwhelming in volume. Gen AI tools such as ChatGPT and DALL-E are revolutionizing content creation, enabling the generation of text, images, and even code on demand. Businesses increasingly adopt Gen AI to scale content operations efficiently, empowering marketers with greater agility. Furthermore, both the competitive landscape and consumer behavior have shifted. Brands now face the challenge of extracting valuable insights from data to personalize consumer experiences. However, as the use of data in marketing expands, concerns about privacy, AI bias, and ethical considerations intensify. Organizations must navigate these challenges carefully to maintain compliance and build trust.
In collaboration with Deloitte and Google Cloud, ETBrandEquity hosted a roundtable discussion in Mumbai to explore how CMOs leverage Gen AI to drive marketing transformation. The session brought together leading industry experts who shared valuable insights on how Gen AI is reshaping the marketing landscape. Participants included Gayatri Iyer, Strategic Growth Manager at ICICI Prudential AMC; Akhil Duggal, Head of Digital Transformation at Crompton Greaves; Meha Parekh, Brand Head at Samsonite; Akshay Salaria, Director of Acquisition Growth & MarTech at Tata Digital; Mousumi Lahiri Roy, VP & Head of Customer Experience at Aditya Birla Capital; Varun Rajwade, Vice President of Digital at ABFRL; Ishan Khare, Head of Digital Revenue at HDFC Securities; Vikram Jeet Bhayana, VP & Head of Marketing at Bajaj Allianz; Narendra Singh, VP of Products at HDFC Credila; Tanushree Jain, Head of Digital Marketing at Polycab; and Smita Salgaonkar, Principal Architect of MarTech at Google.
Marketing technology (MarTech) is essential in engaging customers and gathering actionable insights, even when direct transactions are not involved. For example, a consumer packaged goods (CPG) brand successfully created a community centered around snacking, allowing for a deeper understanding of consumer behavior and strengthening brand connections. This demonstrates how leveraging MarTech can provide a more comprehensive view of customer preferences, leading to more effective marketing strategies. Salgaonkar highlighted, “MarTech is crucial for creating customer engagement opportunities, even without direct transactions. It involves activating various MarTech pillars to enhance customer interactions.”
Directed by data-driven insights, marketing automation is key to improving targeting and personalization. Tools like data warehouses and marketing automation platforms enable businesses to analyze customer behavior and refine their marketing strategies. One example discussed involved using processed data to optimize marketing campaigns, although not in real time. The challenge lies in balancing cost-effective targeting with precise segmentation; refining this approach is ongoing. Rajwade shared that his team uses a traditional data warehouse to calculate derived variables and run models like propensity and churn analyses. While this system is not real-time, it plays a pivotal role in preparing data for marketing activation.
The processed data is then integrated into their marketing automation platform, enabling Aditya Birla Fashion and Retail to update attributes approximately every half day, facilitating targeted marketing based on customer behavior. The increasing costs associated with precise targeting are a significant challenge in personalizing media segments. By integrating personally identifiable and anonymous consumer data, companies can build more nuanced customer profiles, improving segmentation and personalization. Duggal differentiated between two types of brands, stating, “We have A to C brands like Pivotal, where we have consumer data, including personally identifiable information (PII). Then, we have core brands like Parachute and Polar, where we lack that level of detailed data.”
Parekh noted, “Samsonite is a detail-oriented brand with a long history. We are still at the beginning stages of our journey, but we are seeing positive results in terms of growth.” Financial institutions, meanwhile, must balance the need for personalized recommendations with the legal and ethical responsibilities related to data security and privacy. By integrating robust compliance measures with data-driven marketing, financial services can enhance customer engagement while protecting sensitive information. Khare emphasized, “In finance, where rates are sensitive, every recommendation must be backed by research to ensure compliance and avoid misguidance.”
Data sharing in the interconnected marketing ecosystem presents significant compliance challenges, especially regarding customer privacy. Maintaining the delicate balance between using shared data for marketing insights and ensuring compliance with privacy regulations is crucial to maintaining customer trust. Iyer shared concerns from a management perspective about data sharing, particularly with third-party platforms like Google, noting, “If we’re sharing data, Google is consolidating it, which can be used by other companies to target similar audiences.”
AI’s potential to streamline creative and research processes is transforming marketing efficiency. It reduces bottlenecks such as lengthy approval cycles and slow content production, allowing brands to launch campaigns on time with high-quality content. Jain explained, “The creative process can be slow and cumbersome, leading to missed opportunities or subpar content. AI can enhance and speed up this process, providing new possibilities for creative generation.” She added that with advanced customer data platform (CDP) implementation, the goal is to support personalized engagement, mainly targeting specific customer segments for upcoming campaigns.
Advanced bot design transforms customer interactions, providing more personalized and efficient service through conversational AI. Singh discussed the importance of creating bots that understand and anticipate customer needs, guiding them through relevant journeys. He noted, “With an IVR bot, once a customer expresses interest, the bot can confirm the query and initiate the appropriate journey.”
Marketers are experimenting with innovative Gen AI applications, which could significantly alter how brands interact with consumers. The success of Gen AI adoption lies in taking a holistic approach, breaking down data silos, and addressing ethical and compliance considerations. Organizations that adopt a transparent, visionary approach to Gen AI are well-positioned to lead the way in marketing excellence in the coming years.
