Technology

An app maker approached RCOR with the goal of predicting the lifetime value of each user by install date and location. The company was collecting data on the interaction of users with online revenue producing content, but was unable to tie install dates to revenue. They wanted to use this information to target their marketing budget more effectively. To help the app maker achieve their goal, RCOR developed a series of Excel models that could be used to analyze the data and predict the profitability of new products based on their first few days of use. The models were designed to smooth revenue data over weeks to eliminate noise caused by differences between weekdays and weekends. Using these models, RCOR was able to provide the app maker with valuable insights, including the identification of two types of users: 'short tail' and 'long tail'. The majority of users provide a short burst of revenue, but a small minority continue to use the apps for a much longer period of time. Overall, the Excel models developed by RCOR have helped the app maker better understand and predict the lifetime value of their users, enabling them to target their marketing efforts more effectively.