Speed Thrills: SAS soups up analytics with in-memory technology

It’s always fun to attend the annual executive conference put on by analytics leader SAS. Although there is some irony that this year’s event was held in Las Vegas, when the point of analytics is to, ahem, reduce risk in decision making.

Anyway, with all the hype about Big Data, this is about as good as it gets for analytics vendors. Because to make sense of the increasing volume, velocity and variety of data, you need analytics.

Speaking with SAS CMO Jim Davis, he agreed that the Big Data buzzword had raised awareness, but also created confusion. Because when you really think about it, it’s not really a new idea. The Big Data movement, if there is such a thing, is like Occupy Wall Street protesters, says Davis. Everyone is excited but they’re not entirely sure why they’re participating!

Still, I think it’s fair to say that companies are getting excited about new opportunities to mine website clickstream data, listen to customers via social media, and even sensor-based applications. But for now it seems most of the “bread and butter” analytics applications are based on boring old transaction data.

EMC’s Jim Bampos, who heads up the firms efforts in quality and customer experience, says they leverage Big Data to improve both Product Experience and Customer Experience. The EMC “Total Customer Experience” includes every step of the customer/partner journey (Buy-Deploy-Use-Service), as measured by surveys and customer quality metrics. EMC uses analytics to predict product failures so they can be fixed before impacting the product experience. When issues are reported, they can be very complex so getting to the right expert is critical. Analytics helped them figure out that a “chase the sun” approach wasn’t working well, so they opened a 24/7 global support center in Utah instead. And also that the time to answer the phone was not as important in customer loyalty as total time to resolve a problem.

Gilt Group’s Tamara Gruzbarg says the retailer is using analytics to influence their merchandising and promotion strategies. The heritage of the retailer is upscale “urban fashionistas,” but as the company has grown and expanded it has become more challenging to make smart decisions. Email remains a critical promotion channel even as users adopt mobile devices. One predictive model that paid off helped Gilt tune the email frequency based on engagement and age indicators, to maximize revenue while minimize unsubscribe rates.

These examples illustrate that the key business issue, of course, is deriving insight from all the data, big or otherwise. But this raises another question. What is analytics? This term is tossed around casually to mean everything from Excel-based reporting to advanced predictive models build by PhD’s. In his keynote address, Davis went to some pains to differentiate advanced analytics as being “proactive” techniques like price optimization, predictive offer models, demand forecasting and risk analysis.

The big news on the product front was the announcement of SAS In-Memory Analytics to speed up the advanced analytics processes. Instead of hours or days, apps can run in seconds to minutes with the help of clusters of inexpensive servers. For the hardware geeks this is cool stuff because for a modest sum of around $.5 million you can buy a rack full of 48 “blades,” each of which can process 3 billion instructions per section and use 128MB of memory. Total it all up and you’ve got, well, Big Computing.

Randy Guard, VP Product Management at SAS, says High Performance Marketing Optimization will be the first application to take advantage of this power. Marketing optimization means figuring out the optimal mix of campaigns, considering budgets, constraints like customer contact frequency and other business rules. It’s so complex that it can take hours to run. With the boost of the in-memory appliance, now marketers can run in a few minutes, tweak, and run again. And again. Result: a better return on the marketing budget.

Other applications are coming soon, from “event stream processing” which can be used in financial services applications, to price and revenue optimization in hospitality and entertainment. Guard says SAS sees big opportunities in banks, retailers and telcos — industries where SAS already is well entrenched. Jim Davis estimated that 15-20% of the companies 60K customers might eventually take advantage of this technology.

Exciting stuff, but the key issue is still where to focus this technology. For more on that, read my recent article From Big Data to Big Decisions: Three Ways Analytics Can Improve the Retail Experience.


Disclosure: SAS paid my travel expenses and provided a free conference pass. Selected companies and products are mentioned to illustrate capabilities and industry developments; no endorsement is implied. Please visit our sponsor page for information on companies that have supported the CustomerThink community in the past year.

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