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Network World - Kevin Walker's sales team was buried under information. Internal records, news reports, third-party data sources.
Take a simple question like “Which customer should I call first?” The sales team might want to reach out to a customer who has just hired a hundred new employees, or the one whose equipment is ready to be replaced – but that requires going through all those information sources and then prioritizing.
The information is coming in fast, at high volumes, in a variety of formats. It's too much for human beings to handle – it's a job for Big Data analytics.
Walker could have explored building an in-house analytics solution from scratch. He's the director of integrated marketing at Dell, and the company has plenty of computing resources at hand.
But instead he decided to get his Big Data analytics from SaaS vendor Lattice Engines. Going with the cloud, he says, allowed him to get up and running faster and cheaper. The entire setup process took just two weeks, he says. In addition, he says, Lattice Engines specializes in just this one area.
“The fact that you're doing something within a vendor's core competency is going to have a better outcome,” he says. “It allows us to scale globally, as well, and aggregate data from other cloud-based services.”
Today, sales people can prioritize their work based on how likely it is that a customer is ready to make a purchase. The system can even make suggestions about what, specifically, the customer may be looking for. Or what a customer might need and not even know.
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“Maybe other customers like them have purchased a certain security tool,” Walker says. “The customer might not even know that they have that security weakness.”
And the analytics began paying off quickly. According to Walker, for every dollar he spent on the tool and associated expenses, he's gotten $30 back. “I expect to see even better returns when I roll out globally,” he adds.
These kinds of results are making a lot of companies look at Big Data analytics. Cloud-based Big Data services can work well for small companies and startups that don't have the budgets for building their own systems, says Joe Pignatello, senior manager of business information management at Capgemini. But they also be a good fit for larger companies, especially those who need to move quickly to take advantage of business opportunities.
There are some downsides, however. As with any cloud service, companies have to do their due diligence for security and compliance. In addition, they have to be careful not to end up with a collection of Big Data silos from different vendors that don't play well together.
Most large enterprise vendors have general-purpose Big Data analytics, but specialized vendors are springing up with focused solutions that address just one part of the Big Data puzzle.
They tend to tackle the lowest-hanging Big Data fruit, are fast and inexpensive to deploy, and have easy-to-use dashboards or fit themselves easily into existing corporate workflows.