With the help of predictive analytics, marketers can predict future sales. With this prediction information, companies can now decide on their campaigns. Analytics is mainly used for correlation and causation. A lot of vendors pay maximum attention towards correlation but causation underlying a pattern is important to predict a customer’s purchase behavior. Thus predictive analytics analyzes customer behavior and offers them promotions according to their behavior so as they intake those. Hence if used properly, it can be of great importance. Predictive analytics can help marketers across the entire customer lifecycle, said Fern Halper, director of TDWI Research for advanced analytics. Read more about this article by Katherine Noyes (IDG News Service) at:  http://www.computerworld.com/article/2934086/business-intelligence/marketers-are-betting-big-on-predictive-analytics.html 

“If you live long enough, you'll make mistakes. But if you learn from them, you'll be a better person.”

- William J. Clinton

Trial and error are part and parcel of our everyday work. But, learning from mistakes and performing better, is what that makes the difference. In this article, Rachel Sprung, Product Marketing Manager at HubSpot, has shared some of the mistakes in the field of analytics that she had experienced. They are:

• Thinking low numbers are always a bad thing
• Confusing correlation with causation
• Confusing visits with views (and vice versa)
• Equating more time on a page with higher engagement
• Counting internal website visits toward your goal

 To know more and avoid such mistakes, visit the following link:

http://blog.hubspot.com/marketing/marketing-analytics-mistakes