In today’s economy, many businesses can’t afford to manage customer relationships the same way they always have. They don’t want to operate in a reactive mode. They can’t just rely on intuition to deal with customer issues or opportunities. Instead, they need a better way to proactively manage customer behavior.
Have you heard the comment that companies are “data rich and insight poor?” There is so much data available that there has been lots of press regarding the need to manage the avalanche of information. In fact, that’s a key premise of the book Drinking from the Fire Hose which encourages customer strategists to narrow things down and focus on what really matters.
Beyond that need to focus is a desire by many companies to better predict customer behavior. The concept of using all that data to see what’s coming – and ideally to put strategies in place to optimize relationships – is behind the move towards predictive analytics. This is an area of statistical analysis that deals with extracting information from data and using it to predict future trends and behaviors.
This Forbes article from 2010 was on target with the point that using predictive analytics can be a game changer in terms of improving efficiency, reducing risk, and increasing profits.
Just think about the possibilities… What if your overall customer base was fairly stable, but only because you were losing customers just as quickly as you were acquiring them. Wouldn’t you want to understand what was driving attrition well enough to predict who might leave so that you could develop customer retention strategies to keep them?
