5 Easy Steps to Predictive Analytics
For years, predicting customers' behavior involved a lot of guesswork. Today, the economy is changing the way customers act and companies must be responive and cognizant of those changes.
During yesterday's Engage Summit, sponsored by Allegiance, Gary Rhoads, co-founder of Allegiance, said he sees a growing interest in predictive analytics. Companies no longer want to be reactive--they want to uncover relationships with their customers.
Rhoads said organizations no longer need to depend on a statistician to conduct predictive analytics. He listed five "easy steps" to predictive analytics:
1) Use proven business outcomes and key goals with leading industries. Understand their relational patterns or trends. "Find out which group is having the most success and take those best practices to the rest of the organization," Rhoads said.
2) Find the subgroup that is carrying the department. "In my experience it depends on the subgroup."
3) Review the top-box, survey, and bottom-box scores overall and get a feel of the landscape. "This should give you the confidence of where to invest your money," he said.
4) Review voice of the customer for deeper insight. "The view of employees and customers shouldn't come out of left field," he said.
5) Review the hot items that impact key goals. "If you're reviewing analytics without quality data, that's a mistake," he added.
Lastly, Rhoads advises that every company is different. What works for one, may not work for another. So a "pet score" in one organization may not serve as the metric that will effectively affect another. "Every company is unique and every company has a different culture."
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