Building a web analytics stack: packaged vs modular

Packaged analytics tools like Google Analytics are popular for their quick setup and all-in-one capabilities, making them ideal for organizations early in their data maturity journey. However, these solutions come with limitations such as lack of customization, data silos, and limited control over data quality, which can impede an organization's ability to fully leverage its behavioral data for advanced use cases. As companies recognize the strategic value of owning and controlling their data, there is a growing trend towards building modular, best-in-class data stacks that offer more flexibility, transparency, and assurance in data quality. This shift requires organizations to evaluate various options for data capture, visualization, transformation, and monitoring, while also focusing on developing a data team and processes that align with their goals. The transition to a more tailored data infrastructure is demanding but can provide long-term benefits by unlocking the full potential of web analytics and other data-driven insights.