SAS announces Social Media Analytics
SAS introduced its Social Media analytics product today and, given that SAS is SAS, it will serve to give some new legitimacy to the field. Social Media analytics has been around for a long time, probably as long as the Web minus a day or two. But that doesn’t mean that SAS can’t add to the conversation in some important dimensions.
For instance, two of the major constraints on analytics have always been CPU throughput and memory. The more CPU cycles you can throw at the problem of finding a needle in a proverbial haystack the faster you can find that needle. But CPU only works on the data in memory and if you need more data from disk each seek slows you down. So SAS has done a lot to provide the highest performance possible by throwing CPU and memory at the problem.
Last night at the opening keynote, Dr. Jim Goodnight, showed what this can mean. He took an analysis process from a bank that had taken eighteen hours to load and reduced it to a couple of minutes by putting the whole shebang in memory and dividing the task among just over a thousand processors with multiple cores. The importance here should be obvious, that massive amounts of data that a large enterprise might typically generate or have generated about it can now be analyzed in time to make the result relevant for ongoing business processes.
The simple performance demonstration preceded today’s announcement of SAS’s social media analytics for a good reason. If you add together high performance and the very large datasets you arrive at a useful solution for corporate marketers trying to make sense of the twitter-facebook-blog-and-other-social-media data streams that are a fact of life today. As the demo at the press conference made clear, it’s nice to know that sentiment may be up or down but it’s even better if you can analyze it by source, season and other parameters. The result may enable a marketer to pinpoint a particular article or post and determine the most effective course of action.
In the right hands, Social Media analytics can also help you understand the unintentional information that’s given off by your competitors whenever they enter the social web or when the market reacts to something they do.
SAS is offering its analytics as an on-demand package but it’s not simple or something that you buy this morning and start using this afternoon. The company has a well thought out process for on-boarding customers and sticking with them over time to mentor, coach and occasionally perform consulting projects. This all seems very reasonable.
Several smaller Web marketing and marketing analytics companies have taken the same approach lately of providing product and ongoing service and it’s a business model that I think will become more common over time. We’ve spent decades trying to make analytics simpler to use and the results have been good. But the reality is that it will always be something close to rocket science to understand and use tools that predict what people might do with a given amount of information. Also, the marketplace is changing. In a zero-sum marketplace, like the one we’ll be in for a while, it is shrewd for a company to cross sell service rather than another product. Selling service further cements the bond and enables further discovery leading to more cross and upselling.
So the net of the SAS announcement. Interesting that SAS has put a stake in the ground in social media analytics, their enterprise customers will appreciate it and I think it’s important for the continued growth of the company to offer a service like this.