There is a good amount of
traction on Social Analytics from Marketing departments. CMO Teams are
experimenting their discretionary spending in listening platforms, sentiment
analysis, campaign impact measurement, amplification rates and competitive
intelligence metrics.
The mainstream investment is yet
to kick-in in Enterprise IT space. In my view, Social Analytics is all about
Qualitative intelligence whereas traditional analytics is all about
Quantitative intelligence.
Where do you typically need
Qualitative intelligence? When I say
Qualitative intelligence is all about something that is not measurable, not
explicit, lies as tacit knowledge in people's minds, often not expressed in
numbers, generally not quantified, subjective. By means of subjective, the
intelligence also largely depends on cultural bias as well.
Now, Where do you seek and use
such intelligence?. We all know Quantitative intelligence is something that
everybody seeks in structured financial investments/reviews or operational
improvements. But, Where do we use Qualitative intelligence?
Hitherto, We seek Qualitative
intelligence from people. We talk to people our inner circle and our networks
to figure out what is subjective opinion on certain
individuals/institutions/products and services and then We decide.
But, with arrival of social
networks, its much easier to capture such information from Social Analytics
tools.
In my view, Qualitative intelligence
is lot more applicable in relationships whereas the numerical intelligence is
applicable in transactions. What do we mean by relationships and transactions?
I remember reading the following
saying few years go...
"You focus on transactions.
Relationships will not grow.
You focus on Relationships. Transactions will
grow naturally".
Unfortunately, with intense
competition and scarcity for time, everything is a transaction now. The
responses are almost instantaneous and the relationships are volatile, as
choices are too many.
Then, When do we really have
relationships?. I think Relationships are a must-have in long-term
associations...or a series of short-term engagements. CMO team approaches
relationships from the second perspective – series of short-term engagements.
In that context, I see social
analytics are lot more relevant in relationship-centric environments such as
- Measuring customer feedback in
services' firms Offshore Delivery centers
(I recently gave a survey to my car dealer on their recent car service. They asked me to force fit my rating into only
three categories. For example, the
service executive asked "Do you want to us rate as Excellent, Good,
Bad?" I said "Average".
I explained the reasons for the same opinion. Unfortunately, they couldn't complete their
survey, because their system expects only one of the three above mentioned
ratings!. That's crazy!. I could still
force fit my survey rating. But, it would mean the auto dealer will lose the
value of my feedback. That's exactly the Qualitative intelligence I am
referring to).
- Measuring Employee Performance
for Leadership roles (Largely deals with perceptions)
- Measuring the perception of
say, a real estate firm, based on its past deliveries/customer services (again
perception driven), before somebody makes a huge investment
In all these scenarios, stakes
are high and data/information is scarce while decision making.
In all these examples, I am not
saying Quantitative metrics doesn't matter. But, Qualitative information weighs
a lot more, which is often overlooked. In
fact, Qualitative intelligence with corresponding quantitative metrics, it
could be a winner metric all the way!
In some of the scenarios, Social
analytics is also used to compute the impact in short-term transactions such as
measuring the impact of time-bound marketing campaigns (internal/external).
Its very valid, but using social
analytics in relationship management will create greater impact than transactional
scenarios.
Today, Social Analytics is all
about Marketing because that's where it gets funded and largely public data
focused such as Twitter, Facebook, etc. This
is required. But, let's not get skewed that public social is the only social.
There is good amount of social
activity happens in Intranets (beyond Twitter, Facebook, etc.). There is good
amount of social activity happens in non-digital world as well (Phone,
In-person meetings, word-of-mouth opinions)
If we depend and derive our opinions
based only on pure-play social analytics that monitors public facing sites, We should also be aware of their boundaries.
And there are tons of opportunities to employ social analytics in lots of
business and social scenarios.
Insights from Social Analytics
should ultimately help us to improve our relationship management actions!.
2 comments:
Interesting thoughts Bala. My 2 cents. While I totally agree with the essence of your post, I think, IMHO, its more complex than you put it.It would be too simplistic to categorize social analytics as qualitative intelligence. The foundation of Social Analytics is built from a fundamental tension that arises in trying to quantify qualitative intelligence. We can see this tension manifesting clearly in the case of measuring engagement and Social Media ROI, a pain point for most of the Social Analytical approaches, because they are trying to use head( quantitative) for affairs of the heart(qualitative). What I see from clients and elsewhere demanding is that they want to bring together both quantitative and qualitative aspects together. To give you an industry specific example,here is how client seem to be asking .." Can you correlate Nielsens' TV ratings with your Social TV Analytics tools and give me some "real, actionable" insights?" . This as such completes the picture in a wholesome manner, beyond the age-old schism between qualitative and quantitative which we are quite familiar with. Also, I don't think we can isolate any specific environment as relationship centric. Every business environment, at every stake holder level, beyond customers, is becoming highly relationship centric. This trend is only going to accentuate in the coming days!! (which is **good** news for social analytics professionals like me:):))
Venkat,
Its a tricky topic!. All along, we have tried to translate qualitative metrics to quantitative so that machines can understand them!. Of course, it distorted the interpretation of those metrics.
But with the advent of cloud, text analytics and big data, now we have the capability to do real qualitative intelligence mining. Using that intelligence in the context of social makes lot more sense, because social is all about unstructured communication.
Correlation with quantitative metrics is definitely a welcome move. But, again, I would say that is complimentary or another usage scenario of qualitative intelligence.
Fundamentally, We have a whole new capability to mine qualitative intelligence, and that too in social context. How innovatively we use them to our advantage is the big opportunity.
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