Social Analytics: The Science of a Social Business
Timothy Powers 270003F3FN email@example.com | | Tags:  analytics business_analytics big-data smarter-analytics social-media decision-management decision-making ibmsoftware cognos social-analytics spss baforum business-analytics
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Guest post from Mark Heid, Program Director, Social Analytics at IBM
(Follow Mark on Twitter: @mheid)
Just over 15 years ago, authors of a book entitled, “The Discipline of Market Leaders,” asserted there were three (and only three) ways for a company to lead their market(s).
Their thesis is not complicated: invest in unmatched value (best product, best total solution, or best total cost) in the core marketplace, while meeting minimum standards across other measures of value. Focusing the entire enterprise on improvement in the chosen value to customers will result in growth in shareholder value over time.
We're seeing that increasingly "best total solution" is the value proposition of choice because of global changes over the past 15 years. Competing on "best product" is very difficult today as the horizon on an innovation-led technology advantage is shortening all the time. The market penetration for televisions 60 years ago to reach 50M users took 12 years. The internet took four. Tablet computers took just two years.
Competing on "best total cost" is a global undertaking where massive scale is frequently the core economic requirement. By its very nature, this strategy limits the field of competitors to a select few who drive globally integrated supply chains as a core competency.
So, in today's environment "best total solution" is where so many enterprises are focused.
But, it requires an intimate understanding of the customer, the customer's customer (sometimes) and the context in which they make their purchase decisions.
With the advent of social networks, we can define the "best total solution" by thinking of the social web as a massive focus group. Enterprises who lead in "best total solution" today are Social Businesses who mine insights and analyze them to precisely understand how customers feel.
Today's leading enterprises apply scientific methods to their social business activities – continuously harvesting the data associated with the process of establishing & maintaining relationships across the customer-set.
This data is priceless to compete effectively today because customers are expressing their needs in the context of their ongoing social network activities. All enterprises need to do is listen – scientifically – to separate the proverbial wheat from the chaff and uncover the core insights that lead to happier customers.
IBM has been working on applying scientific analysis to the petabytes of social network data. We are focused on enabling businesses to become more socially skilled as they engage the "massive focus group" that is the social web.
The "data exhaust" from social business engagement is the input to sophisticated Social Analytics which interpret customer sentiment, evolving topics of discussion and unmet needs.
We are working closely to help our customers improve their capabilities in Social Analytics. Many feel less well-prepared for these challenges than they would like.
Consider recent results from the IBM Global Study Chief Marketing Officer study of what CMOs feel unprepared for. Notice that the top four areas involve social analytics because it's about huge data-sets, social web content, new social channel options and a diversity of ages & geographies to consider.
I will be doing a webinar tomorrow, March 22, 2012, entitled, “Social Analytics is Key to being a Social Business,” and will be discussing how enterprises can get started on the topics above and it touches on all four areas of unpreparedness. You can register here.
One theme you'll see me strike is how our clients are focused on adding their social analytics insights to the larger corpus of datasets that they use to run their business today.
Consider this view of the typical "360 Degree Customer View." We have tried-and-true behavioral and descriptive data, and a lot of interaction data. But, the attitudes our customers have are more elusive.
We have to conduct costly, time-consuming surveys to capture their sentiment – the "Why" behind the "How, Who and What."
So, as our clients serve the needs of their clients better, it's largely through the predictive lens which comes from blending two key things:
· Scientific interpretation of social business interactions (The "Why")
· Modeling of traditional datasets, including the attitudinal data from social media and surveys
For more information:
· Listen to the webinar I recently did with BrainYard and InformationWeek, "Social Analytics - Putting the Science into Social Business." A replay is available here and the presentation is available on SlideShare here.
· Watch the video below for a strategic viewpoint from Deepak Advani, vice president of products and solutions at IBM, on social analytics and why it’s so important today