Is your business ready for advanced analytics?
Building an analytics program starts with knowing what data you have. This is done through descriptive analytics. Descriptive analytics explains what has happened. Your data is your most valuable asset, but means very little in its raw unprocessed state. Using analytics you can describe your customer base, their location, their demographics, and their purchase or donation past behavior.
Diagnostic analytics seeks to explain why something in your data is the way it is. Diagnostic analytics examines relationships between variables and data over time to determine possible causal relationships between action and effect.
Predictive analytics examines historical data to determine what is likely to happen in the future. It can calculate the likelihood of an event happening an amount of something. For instance, predictive analytics can predict the likelihood of a customer responding to a direct mail campaign or purchasing a particular product. Predictive analytics can also predict the lifetime tenure of a customer or the next donation amount of a donor.
Prescriptive analytics takes information from descriptive, diagnostic, and predictive analytics and recommends specific actions to take to achieve a business goal. This can be creating a direct mail list donors based on likely outcomes, selecting campaign strategy based on revenue predictions, or making a business decision based on consequences.