A recent post on The Modeling Agency blog discussed some practical examples of data mining. Now from the headlines comes another example: data mining may equal salvation for struggling record labels.
The Guardian Media Network writer Lucy Fisher explains how record labels are suffering from a lack of CRM, or customer relationship management, and how data mining is the key to developing an essential CRM framework. She writes:
In the digital world, there’s a need to reach out to millions of music lovers, for whom accessing tracks involves just the click of a button. “There are various social media properties for artists but these don’t represent proper CRM,” he says. “True CRM is where they need to get to. If they don’t own the data and the customer relationship across the various touchpoints, they won’t succeed.”
The acid test, says Uttley, is: do you know the 100,000 biggest fans and do you have their contact details?
Building a CRM through data mining with the amount of data a large record label possesses is no small effort. And restructuring daily operations so that they are data-friendly has proved to be something of a challenge. The music industry is heavily entrenched in gut instinct and decision making based on educated guesswork. Data mining, on the other hand, is a precise science.
But data mining can be used not only to identify brand ambassadors and key influencers, but to form predictive models to estimate future customer behavior. That is, after all, not so far off from the way record labels have traditionally operated – making often major business decisions based on a prediction, however based in intuition, about how customers will react.
The Guardian piece is revealing and intriguing, and worth a read for anyone who is a fan of data science, or just looking to understand data mining through concrete examples of how it can be used in business.
If you think data mining could help your business but you’re not sure where to start, try one of The Modeling Agency’s free webinars. You’ll learn the foundation of successful data mining practices and get your next campaign off on the right foot.