In the first stage – descriptive analytics, past data is studied to learn from past behavior and to assess how it can affect future outcomes. The second stage – Predictive Analytics uses data to predict what could happen next. The third stage which is also often referred to as the final frontier in the Big Data analytics game is Prescriptive Analytics - where data helps prescribe different actions.

Here are 4 reasons for B2B marketers to consider Prescriptive Analytics in 2018 

1. Combines the best of descriptive and predictive analytics

2. Drives informed (digital) marketing decisions

3. Improves customer-focused strategies to enhance CX

4. Helps mitigate business (even Sales and Marketing) risks

Data Informed: Please discuss the similarities and differences between predictive and prescriptive analytics.

Guy Yehiav: Prescriptive analytics is simply the next level of predictive analytics. More and more companies are now seeing the value of providing prescriptive analytics and are excited to adopt this approach.

The key difference between the two is that prescriptive looks at current pattern sets and provides actionable outcomes. Prescriptive allows a tailored approach for understanding both user behaviors and unlikely patterns that can cause organizations to lose money and waste resources. While both prescriptive and predictive analytics rely on big data for gathering and understanding customer information, what sets the two apart is who is assigned an actionable plan to fix the task.

Prescriptive solutions take predictive to the next level by providing a desired outcome and the right person to fix the problem at hand. Instead of relying solely on predictions based on educated guesses and past results, prescriptive analytics provide pattern seeking machine algorithms that promote positive customer experience and provide resolution.