FORRESTER blog repost Social Network Analysis: Going to Become Too Ubiquitous for Its Own Good

Social Network Analysis: Going to Become Too Ubiquitous for Its Own Good

By James Kobielus

Social networks are the future of online life, whether we like it or not. Before the end of the coming decade, relationships with everyone –including family, friends, colleagues, employers, merchants, suppliers, and government agencies—will hinge on your access to these parties, and theirs to you, through online communities of all shapes and sizes.

Social networks are becoming much more pervasive than today’s mass-market communities—such as Facebook, Twitter, and LinkedIn—would lead you to believe. Before long, many will be embedded in the full range of business and personal applications. In ten years’ time, today’s social networks will have evolved into a powerful, seamless worldwide infrastructure for collaboration, sharing, interaction, and transactions. Many will be integral features of the mobile, broadband, and streaming media services that shape business and consumer life. Many will be secure, robust environments that span across federated public and private clouds.

From an enterprise perspective, social networks are the “buzz” that can spell the difference between success and failure in a reputation-driven online economy. Already, we see a strong interest in social network monitoring and marketing tools. Everybody wants to know whether, how, how often, and by whom they’re being mentioned in Twitter, Facebook, blogs, and the like. And everybody wants to influence those discussions in their favor and extract maximum revenue potential from sales to people who use those media. Anybody who has ever tweeted the name of a large company and been immediately greeted by an automated “we’re following you” message from that same firm knows the power—and potential nuisance factor—of this new medium.

Clearly, social networks are highly monetizable. At heart, they are continuously refreshing streams of customer-generated intelligence on requirements, needs, sentiments, and experiences. As this new way of doing business gains traction, companies will focus the full power of advanced analytics on social networks, especially those where customers live. Forrester sees growing enterprise adoption of social network analysis, an emerging discipline of predictive analytics that mines behavioral, attititudinal, and other affinities among individuals. Though it can be applied to a broad range of scientific and other topics that involve no online interactions, social network analysis thrives on the deepening streams of information—structured and unstructured, user-generated and automated—that emanate from Facebook, Twitter, and other new Web 2.0 communities.

What exactly is social network analysis? Essentially, it involves discovering, mapping, and measuring relationships among people, groups, companies, and any other entities—including products, online content, and personal computers—with which they interact. It leverages such key data mining capabilities as segmentation, clustering, and regression to identify, for example, who are the leaders, followers, influencers, and outliers in social groupings. If viewed in the time dimension, social network analysis can reveal the cultural dynamics that spell the difference between a successful marketing campaign and a flop, or that drive one group of customers to renew their contracts and others to jump ship.

It doesn’t take much stretch of the imagination to see where this all might lead. As customers reveal candid thoughts in real time via Twitter and other social networks, enterprises can conceivably cut back on structured surveys, focus groups, and other traditional approaches to gauging demand. In their place, companies can simply and automatically “listen” to social networks through complex event processing; process unstructured text streams through content analytics; aggregate all intelligence into massive analytical data marts; and drive sales, marketing, and customer service through inline social network analytics models. The “killer app” for all this becomes the real-time “next best offer” your contact center makes from this intelligence, or the marketing campaign you re-arrange on the fly to save it from near-failure.

But there’s danger in this otherwise promising scenario. The problem is that social network analysis—automatic, real-time, effective--will become too popular. Enterprises will rely more and more on high-powered social-network-analysis models to divine market trends, segment the customer base, and tune their campaigns. As this approach gains adoption, companies will be tempted to pull back significantly from traditional outreach efforts—such as focus groups—that involve direct interaction with customers and other stakeholders.

It’s not that statistical models are inherently invalid. It’s just that they can become another layer of abstraction between you and your customers, preventing you from making personal connections with them and thereby securing their ongoing patronage and loyalty. Also, those models may crowd out the intuitional approaches you should use to gauge the cultural zeitgeist within which your business creates value.

To the extent that social network analysis encourages proliferation of superficial customer-segmentation categories—on the order of “Yuppie” and “Generation X”—it will invite backlash. One might refer to these sorts of magazine-ready segmentation labels as “statgeists,” meaning that they may have some grounding in statistical models of demographics and other metrics, but are little more than cutesy consultant-speak.

Beware of sexy statgeists. When you use these too-clever-by-half verbal concoctions, you gag a little, as do the real people to whom they ostensibly apply.