Data teams can justify investment in data infrastructure by creating revenue-driving data practices that are tied to specific business outcomes, such as increasing earnings or controlling costs. For product-led growth, data teams can use experimentation to drive "aha" moments via AB experiments, which can be implemented with minimal infrastructure using simple methods like randomizing users into groups based on the last digit of their user ID. Marketing teams can optimize marketing spend and improve ROI by analyzing lifetime value and payback periods, while sales teams can enrich lead, opportunity, and account data to create more efficient processes and maximize new deal volume and size. By demonstrating value using simple methods and a modest amount of data, data teams can enable CFOs and other gatekeepers to picture the possibilities of making analytics projects repeatable and expanding the scope, scale, and sophistication of their data operations.