Figure 1. Using Descriptive, Predictive and Prescriptive Analytics to Make Decisions / Take ActionsAs users/customers engage with a company (their products, services, surveys), they generate a lot of data about their behaviors and interactions with the brand. Predictive analytics and artificial intelligence capabilities provide a way to extract insights from that data to help you improve the customer experience and optimize customer loyalty.

Artificial Intelligence and Predictive Analytics

Today, businesses can collect hundreds of variables about their customers. Real-time delivery of insights necessitates the quick processing of these data. Toward that end, companies are employing the power of predictive analytics and artificial intelligence (e.g., machine learning) to extract insights from data.

There are generally three types of analytics: descriptive, predictive and prescriptive. Descriptive tells you what happened. Predictive tells you what will happen. Finally, prescriptive analytics tells you what decisions/actions you need to make/take to maximize opportunities/mitigate risk. While companies employ all three types of analytics, machine-assisted predictive analytics is where the most value lies.

Simply stated, machine learning is a way to learn from historical data through statistical analysis. When we pair predictive analytics with computational power, we can surface insights quickly and reliably. That is the essence of artificial intelligence. The insights from predictive analytics and machine intelligence will impact how you market, sell and provide support to your users.

 

This article originally appeared on businessoverbroadway.com.  To read the full article, click here.