Are Universal Social Engagement Standards Possible?
Business needs a better barometer of audience interaction in social media.
What if you could look across all of social media and truly understand what's taking place -- particularly those things that are relevant and impactful to your organization? Many companies now realize the opportunities inherent in being able to see the global conversations that take place about their products and services online every day. But, for varied reasons, many also are uncertain how best to access these opportunities.
This column continues the discussion from Social Business By Design (2012, John Wiley and Sons), the book I recently co-authored with Peter Kim on the methods that organizations can use to better prepare strategically for social business.
As a strategic business practice, there's no longer any question of whether there's business value in measuring the way customers socially engage with us. It's now reality, as growing numbers of firms are prepared to acquire the necessary skills and put them to good use. Yet, despite significant early success stories, there are also real challenges along the way.
Consider a compelling recent example of social analytics: Experiencing fierce competition, mobile communications giant T-Mobile USA discovered last year that it could correlate social media activity with its CRM database. By analyzing links between the two, and what was being said, they found they could identify when customers were unhappy and planning to defect to another carrier. By then building an operational process to reach out to and address the issues before the customer abandoned the company, the mobile communications giant was able to dramatically reduce defections -- cutting them in just one quarter, according to the Financial Times.
Clearly, this is a very substantial result, and it comes from having the ability to turn analyses of social media engagement into actionable business intelligence, something that many contend is still more art than science, given the inherently slippery nature of unstructured human conversation in the online world. However, this is becoming an increasingly solved problem and hasn't prevented steady progress in a certain industries as they learn how to combine the technologies and approaches of big data with social media to produce often hard-hitting results.
Big Data: Key To Unlocking Social Analytics?
The tech industry's current fascination with using big data to facilitate much better access to corporate information has led to a whole raft of innovative new products and services in just the last year alone. Enterprises can use these tools to make sense of their rapidly growing piles of digital information. While social media is just part of the big data story, it's a particularly important and largely untapped data source for many organizations.
Looking at it this way, it's clear we now have two critical parts of the equation needed to better tap into global customer insights: 1) Powerful new analytic tools with reach into and understanding of social media, and 2) visible global online conversation, i.e. the real-time flow of information from the billion plus individuals engaged around in the world in social media today.
In fact, it can be argued that the only thing missing at this point for achieving results is the necessary imagination and willpower to apply social analytics to our businesses.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.
InformationWeek Tech Digest, Nov. 10, 2014Just 30% of respondents to our new survey say their companies are very or extremely effective at identifying critical data and analyzing it to make decisions, down from 42% in 2013. What gives?