SMBs Seek Enterprise-Class Predictive Analytics
Simple and adaptive solutions can reduce costs and improve profitability for small companies.
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Predictive analytics is not just for large enterprises, and growing interest by small and midsized businesses (SMBs) is pushing the boundaries of the technology.

Forty percent of U.S. midmarket companies are interested in predictive analytics as a means to reduce costs and improve profitability in their businesses, according to a Techaisle survey of SMBs. But because they do not produce the same volume or complexity of data as the much larger firms, SMBs are looking for predictive analytics vendors to incorporate simple and adaptive algorithms into their products.

"One of the biggest differences between SMB and enterprise predictive is that large organizations often have the internal [talent] to do the analysis and calculate the numbers," says Thomas Oriol, CEO of sales visualization and analytics company SalesClic. "For SMBs, you have to incorporate interpretation into the product itself."

In response, IBM, for example, launched Analytic Answers to give SMBs access to predictive analytics as a service through IBM Smart Cloud. An insurance company might want to know what percentage of its customer base is most likely to purchase a certain kind of insurance plan. Analytic Answers lets the business user type in a question and then instantly analyzes the company's data sets to present a reasonable answer.

Not to be outdone, SAP launched its own SMB-friendly solution when it unveiled its Business One application available through SAP HANA, its real-time, high-speed, in-memory platform.

In addition, more than 150 software start-ups are using SAP HANA as a development platform to service their own customers. One company, Liquid Analytics, uses the platform to create iPhone, Android, and BlackBerry apps for wholesale sales reps with predictive and "gamified" features built in. Laurie McCabe, cofounder and partner at the SMB Group, a consulting firm that specializes in understanding the technology requirements of smaller firms, says this kind of deep-rooted analytics is still relatively "underpenetrated" but growing.

Although SMB Group research has found a wide gap in demand for big data analytics between small businesses and large enterprises, McCabe maintains the gap will close as both types of companies share very similar needs.

Companies large and small need to acquire customers, find out how to prevent customer churn, ensure customers are buying the right kinds of products, and drive value, says Shashi Upadhyay, CEO of Lattice Engines, a provider of big data analytics solutions. "The real question is what tools, data, and resources do you have available to actually go after those problems."

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