Treating customer intelligence data as a product is crucial in today's competitive landscape, enabling companies to make data-driven decisions, improve customer experience, enhance data quality, and increase innovation and literacy. Data can be packaged into various products, such as dashboards to understand customer behavior, AI-powered recommendation engines, and churn prediction models. To get started on this journey, organizations should assess their data assets, identify potential use cases, adopt a customer-centric approach, and hire the right talent. However, companies must also be aware of pitfalls such as privacy concerns, security threats, bias in algorithms, informed consent requirements, and data quality checks to ensure that they are using customer intelligence effectively and responsibly. By doing so, organizations can unlock endless possibilities for growth, innovation, and customer satisfaction.