Key learnings from the panel discussion with Karl Wirth, Chief Product and Technology Officer, and Luma Dahlbacka, Senior Director, Digital Experience Management at Treasure Data.

Questions from Amit Erande, Partner at Artefact US.

About Karl Wirth: At Treasure Data he enhances their Customer Data Platform (CDP). He co-founded Evergage, a real-time marketing and CRM solutions company acquired by Salesforce, and managed Salesforce Personalization.

About Luma Dahlbacka: She is an experienced professional specializing in strategic communications, public relations, and marketing. With a demonstrated history of working in the technology industry, she brings a wealth of expertise in brand development and corporate communications.

About Treasure Data: Treasure Data is an enterprise CDP provider that unifies and analyzes customer data to create connected experiences and drive business value. It supports numerous Fortune 500 companies with its innovative data management solutions.​

Customer expectations in the digital age

Customer expectations are rapidly evolving due to advancements in digital experiences across various industries. In financial services, customers demand real-time updates and seamless processes. This expectation drives the need for greater transparency and efficiency in financial transactions and services. In addition to that, AI plays a critical role in addressing industry challenges in retail banking, particularly in enhancing customer experience and ensuring regulatory compliance.

Challenges of data management and regulatory compliance

Managing extensive customer data is a significant challenge for financial institutions. This data, both implicit and explicit, must be effectively utilized to provide value and ensure compliance with complex regulatory environments. Effective data management involves recalling relevant information at appropriate times and demonstrating adherence to customer best interests.

Enhancing customer experience through AI

AI plays a crucial role in enhancing customer experience by focusing on acquiring, onboarding, retaining, and upselling customers. The key to successful customer interactions is relevance. AI and machine learning analyze vast amounts of data to tailor interactions to individual customer needs, ensuring that communications and offers are timely and pertinent.

Leveraging Customer Data Platforms

A Customer Data Platform (CDP) unifies disparate customer data into a single profile. This unified data is augmented through ML to predict customer behavior and preferences. The CDP then activates this data to drive relevant interactions, such as sending personalized emails or making tailored offers during customer service interactions. Standardizing and unifying data profiles are essential for delivering timely and personalized customer experiences.

AI-Enabled use cases in financial services

Common AI-enabled use cases in financial services include marketing automation, fraud detection, and risk management. Developing real-time personalized experiences requires scalable data strategies. Effective AI implementations can streamline processes and provide significant value to customers, from personalized marketing campaigns to enhanced customer support.

Acquisition and retention strategies

AI-driven CDPs can identify and target potential customers with personalized marketing campaigns, enhancing customer acquisition efforts. Maintaining relevance throughout the customer journey, from personalized homepages to targeted email campaigns, is crucial for customer retention and preventing churn.

Case studies and real-world applications

Practical applications of AI and CDPs in financial services demonstrate their effectiveness. For example, AI capabilities can streamline marketing campaigns, significantly improving conversion rates. Building comprehensive customer profiles enhances retention through personalized interactions, resulting in better customer engagement and satisfaction.

Future of personalization in financial services

The future of personalization in financial services hinges on trust, relevance, and ownership. Building customer trust, achieving one-to-one relevance at scale, and maintaining ownership of customer data are critical factors for success. Partnering with dedicated AI providers ensures data is used effectively and ethically, supporting the overall goal of enhancing customer experience through AI-driven personalization.