Customer Data Platform (CDP) projects can often fail to meet expectations due to a variety of complex factors. One of the primary reasons is the sheer scope and ambition of these initiatives — CDPs are designed to unify and centralize a company’s entire customer data ecosystem, which inherently involves integrating numerous disparate data sources, systems, and technologies across the organization. This level of technical complexity can quickly become unwieldy, especially if proper planning, scoping, and project management practices are not rigorously followed. Another common pitfall is a lack of organizational alignment and buy-in — CDPs require cooperation and collaboration across siloed business units, data teams, and marketing/sales functions, but getting everyone on the same page about goals, data governance, and usage can be a major challenge. There are also often underestimations of the resources, skills, and ongoing maintenance required to properly implement and operate a CDP at scale. Companies may lack the necessary in-house expertise in areas like data engineering, identity resolution, and advanced analytics, leading to over-reliance on external consultants and vendors. And even when a CDP is successfully launched, many organizations struggle to drive meaningful, long-term value from the platform if they fail to evolve their customer data strategies, integrate the CDP into critical workflows, and continuously optimize the technology based on business outcomes. Overcoming these hurdles requires a holistic, enterprise-wide approach to CDP adoption — one that balances technical capabilities with organizational change management for lasting success.