The Polyglot of Social Data and the rise of the Social Media Revenue Officer

The rise of cloud computing has enabled large and small enterprises to scale up and maintain big social data stores, Oracle provides a combination of services as well as many other vendors. So as the economy of scale bares down on cloud services,  expect price, availability, and convenience to drive more and more companies to begin collecting more and more data.

As a result, we are entering the world of the Polyglot of Social Data. A polyglot is something containing many languages. In social we are seeing that enterprises are needing to combine social engagement analytics, with social opt-ins or social identities, and enrich that with clickstream or beacon tracking data. While Oracle has a set of solutions for this which we term the “Social Cloud”, the role of the person in charge still has some daunting challenges.

Let’s take a look at this Polyglot of Social Data occurring in the enterprise that has given rise to a new role in the enterprise's org-chart.

First, There is no EOF for Social Data. Every vendor including Oracle, will always deliver different social numbers for any query, simply because the data is stretched across clusters, so there is No End of File. Because these NoSQL data sorts are unstructured and continuously being fed new data, when they do collect the data into a structured format, its dated and frozen to some extent at that point. That’s why any “Keyword/Phrase” search gets you different numbers for any vendor... (Note this excludes structured data like number of Opt-in Advocates or Social IDs)

Once you realize that there is no correct sample size as the social data universe is ever expanding and changing continuously, different responses to metrics must emerge.

So, If the sample size is in constant flux, then rather than how wide, its better to ask "HOW DEEP CAN WE GO?".  So you want to begin looking at what I call “Social DNA”. Pick a definable target and measure the speed of message uptake in that target set, and observe how that Social DNA morphs over time. If you cast wider and wider nets, all you get is a feeling of did I catch all the fish? And more importantly, what do I do with an "Ocean of Fish Metric" aka 10,000 more Likes this month?

Go Small. It sounds counter-intuitive. I am not suggesting ignore “Wide Data Metrics”, I am suggesting the following: 1) Break down data silos, 2) Sift the Data to reveal personas, 3) target personas, 4) decrease social surface friction for Call To Action’s of those personas, and finally 5) Measure all CTA’s. Yet, these are very heavy lifting activities for the enterprise, on multiple levels, so who is going to be in charge of this?

As the technology changes so do the roles. These new set of Big Social Data Tools are creating a new role, where someone is becoming responsible for utilizing and leveraging Social Data to create Revenue. As the role of managing social media in real-time changes, I suggest that the forces that will affect the enterprise as it tackles the Polyglot of Social Data will force a new role to emerge as well.....

Emergence of the new SMRO:

The Social Media Revenue Officer arrives. She is in charge of social engagement & analytics, with social opt-ins or social identities, and enrich that with clickstream or beacon tracking data to deliver big results.

Someday, someone must be in charge to turn all the Big Social Data collected into revenue or actionable data... Just as the Email Marketing Manager has been responsible for delivering results, so will someone have to on the Big Social Data side as well...

Overall, we are moving in that direction, advocate programs are great at gathering Social DNA. But the merging of internal silos, sifting of current clickstreams, and managing Social ID Opt-Ins is just barely underway. And joining, digging, and testing those samples is where the real heavy lifting is, especially when asked what is actionable and getting the enterprise to act on those emergent social personas on social channels; via 1v1, social ad marketing, and content marketing.

In my conversation with the VP of IT at a major entertainment conglomerate of how to deal with the oncoming “Polyglot of Social Data”, I realized there was a job description already forming.

There is a difference between Real-Time Insight, Deep Analysis, and Social DNA Sampling. As we collect data from website traffic, social conversations, branded communities, mobile check-ins, and so on, these three job functions come into view.

Real-time Insight Vs. Deep Analysis Vs. Social DNA Collector: There are three separate roles that could be combined into two or could be brought under the control of a Social Media Revenue Officer.

(A) Real-Time Insight aka Short Term Trend Spotter. The Real-Time Insight worker needs flexible tools to respond quickly to changing enterprise needs. Their tool of choice: Oracle's SRM. This person experiments with terms, segments in the real-time space. Looking for opportunities to focus on unique segments to test for Social DNA. Her Aha! Moment is “Our Product X is Big in J-Pop Blogs”.

(B) Deep Analysis aka Long Term Trend Spotter. The Long Term Spotter needs to understand statistics effectively, enjoys data analysis tools like Oracle’s Endeca Insight Discovery Tool. This person has a repository of over a year’s worth of data, experiments with large data sets in house, as well as clickstreams combined with Social DNA samples, along with various data feeds. Her Aha! Moment is “We are gaining in white collar ex-urbs around our brand X”.

(C) Social DNA Collector aka PII(Personal Identifiable Information) Collector and Management. The Social DNA Collector needs to be very security savvy as they work with agencies and vendors to collect Social DNA aka emails, Facebook IDs, and Twitter-handles. Her tools of choice are both SRM & Eloqua. This person formerly called the Social Media Manager, comes up with novel and interesting ways to get Social DNA and most importantly insures the privacy, security, and opt-in compliance for other campaign specific insights. Like adding questions like “When do you watch TV”... Or managing advocates to help recruit and increase Social DNA samples and sample types. Her Aha! Moment is “We can get emails addresses via our “Video Engagement App”.

Ultimately the three processes, Real-Time Insight, Deep Analysis, and Social DNA sampling would work well together in parallel. Real-time Insight may provide new Social DNA opportunities and track current campaigns, Social DNA sampling hands samples off to Long Term Analysis, and Long Term Analysis builds new models and finds new target markets now and in the future.


Therefore, these responsibilities of Real-Time Insight, Deep Analysis, and Social DNA sampling will be combined at some point. Social Media technology provides capabilities to model and track Facebook content to commerce. And in some enterprises are beginning to converge. The result is that the tools contained in this blog show this convergence is already happening. So whether enterprises develop or change their organization, the technology may already be ahead of the curve. 


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This is the working journal of Christopher David Kaufman a Senior Consultant working with Mobile Applications, Social Media Dynamics, IoT-Sensors and the big data that comes from collecting the small data from mobile tablets or phones, business contexts and crowd-sourced dynamics.


« June 2016