What if the Predictive Model goes wrong?

Predictive models are used to predict future outcomes on the basis of data collected from past. Many organizations take their crucial decisions based on the foundations laid by the predictive models. But what if the model goes wrong? "BOOM"- crash of a significant part of the strategy! Though each predictive model has some scope of error. There are chances that the input variables considered in the model were not appropriate. But we need to find out what kind of error and to what extent it is acceptable. There is a need to work on the foundation of the predictive models to prevent failures. Read more about it in the article written by John Bates (Senior Product Manager for Data Science & Predictive Marketing Solutions) at: http://blogs.adobe.com/digitalmarketing/analytics/what-to-do-when-your-predictive-marketing-is-wrong/

Take Customer Experience ahead of the field, using Data Driven Marketing.

It's all about customer experience - make it better using Data Driven Marketing!                                   It's important to treat them like true customers by taking them through personalized life cycles. Normally, customers are expected to feed the website with lots of data regarding their preferences and personal details. So there is a lot of data in the hand of an owner. But the value lies in effectively scaling data and analytics to enrich their journey. Thus, planning the marketing strategies by keeping in focus the results of this data analytics. 

The article written by Kevin Lindsay digs deeper into the power of Data Driven Marketing at: http://blogs.adobe.com/digitalmarketing/personalization/strength-in-numbers-best-practices-for-data-driven-marketing/