Tuesday, July 10, 2012

Moneyball for sales and service

With the buzz around Big-Data it is important to keep in mind what can be done with the data. For those of us who have read or watched Money Ball it is apparent that you can use insights derived from data and combine that with your intuition to make better decisions.

Glassbeam gives you the tools to make such decisions in your business, based on unfiltered machine data.

Once products are sold to customers, the product manufacturer has very limited visibility into how a customer uses the product. The customer feedback is always filtered through the words of the field person or the call center agent or the customer themselves. And not all data is captured. This is not the way the internet companies work. Web based product companies are constantly collecting data on consumer usage and mining the data to make their web pages better, to provide a better experience to their customers or to help realize additional value to simply provide a better performance by knowing and acting on issues proactively. Physical product manufacturers are reactive because the tools to collect and mine log data are not geared towards business users.

Any product executive needs to be on top of how customers are configuring and using their product and find issues before their customer does. As one of our customers put it, “It is embarrassing when my customers know more about what is happening to my product before I do”.  Many product manufacturers log or collect tons of data but don't have tools to make sense of the data being collected.

With Glassbeam, sales and service people can arm themselves with detailed customer intelligence before an account call – based on actual machine reported data. Everything can be logged and should be logged – machine usage, performance metrics, specific configuration and customer specific settings, various events across all the components that make up the storage box. Glassbeam’s customers are realizing the power of data by capturing machine chatter and mining the data for to make better decisions on support models, account management, product roadmaps and licensing.

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