Modeling customer acquisition, retention, and revenue per user are key tasks for data scientists working in business. But getting experience working on these problems usually requires access to private business data. The focus of this talk will be how to model and forecast these three critical business metrics for subscription-based businesses using only publicly available data. Further, these models can be combined to valuate a business. Because this valuation links forecasts of measurable business metrics to business value, it can be used to create key performance indicators (KPIs) that measure actual dollar value-added. This method will be demonstrated by an example valuation of Buffer, a social media management platform, using data anyone can access online for free

These skills are useful for data scientists working in businesses anywhere from a startup to a Fortune 500 company looking to forecast growth, measure employee performance, or value themselves (or an acquisition target) for an exit or acquisition.

This talk will include:

How to model customer acquisition, retention, and revenue using public data
How to access data needed to build these models
How to use these models to valuate a business
A demonstration of this method to valuate Buffer using publicly available data