Finding symmetries in an unsymmetrical world ..

[On applied economics in business models, revenue growth & blue ocean strategies for the passer-by customers]

And then, there was a “Google” with its much coveted page ranking algorithm, but the users and the companies betting their money & resources on the web wanted more, and they wanted it fast.

So was born the Big data wave (well there was a lot more in the space between.. ). So what is this Big data wave, and what is the ecosystem behind it?

Quite simply it is this – given a piece of information, how likely is it that this behaviour will be “consistent” – or that given that I see a response A , what is the probability that it will continue to be (in some confidence intervals) , still A ? At it’s heart, Bayesian classifiers and the whole lot of Quantitative Econometrics & modelling tries to do just this – except the fact – that the data that we indeed have- is just NOT enough to MAKE scientific decisions. Now let’s understand why this is so –

Simply because  the NEED of capturing so many dimensions of data have only evolved very recently, and thus given that we cannt really back test the models, is as good as saying, well , look we have a CLO \ CDO instrument ( the ones that got the 2008 Global Financial meltdown)  – bu we do not know whether we can really bet on it – and now , surprise ! Companies value it like they value money – since everybody does, this must be WORKING .

Then is this picture true/not true ?

Well it depends, yes,  having an additional way to triangulate / benchmark the Business decisions must be  good , having a deep insight into customer buying patterns, and knowing how best to facilitate his decision making must be good too, but the fact remains simple –

“ Given that that information becomes a commodity, how do we price it ? ”   – how do we know the price points that this information can be “traded at”. This question was originally raised in a Big data talk at the Churchill club, but it has stayed on. Ever since, I have asked this question to the CEO’s of Research Analytics firms, marketing & PR firms and to people in the Big data wave. They say, well right now, we are beginning to understand to measure different dimensions of the willingness to pay of the consumer, and the more and better insight we have into this , the better will we be able to “classify this information” – it is like the intelligent filtering , the more intelligence pumps in, but more is never enough , since it is so qualitative.

On top of this wave rides another wave, which is with Social media listening tools, trying to draw trends and analysis, and adapt before being lost in the over social- connected- spilling wave. This wave relies on trusting that (Thus if you throw in an assumption that people put their best foot forward, most of the quantitative models would collapse , on the predictability count – and they, like money  is valued, solely because “everyone buys this currency” –  so while the consumers get more and more aware of the “listening” they would get more “probabilistic-ally sophisticated”  – though it is hard to say , whether it is good, or bad – surely that evolution will happen in my career trajectory, and would be wonderful to ride this wave, and not just be another “passer by” . So welcome again, to the new evolution , which si essentially “inside out” of the consumer needs, but just with some frills attached , may be because  “the consumer himself does not know what he wants ” .

 

There is one more thought that I want to leave you with – ” Those that make the choices, simpler, faster, more guilt free, and use rewarding schemes, will get there first- and ofcourse cascading through the choice paradigm of the consumer has never been as challenging as this.  So knowing I love coffee, only when it rains, and only in the evening, is a powerful information – This is the goal – knowing, when, what, how I like to consume the goods & services – this is the future of personal marketing. 

( I used to write a lot about Permission marketing, but I think the loyalty gets all time low, and so does the ROI on the same)

So, Modelling has evolved, so has revenue metrics , “customer satisfaction” and the “needs of the customer” – the age of good to have, but why pay – but the good news is though the customers spend a lot of time with differing services, they are getting less price sensitive when it come to anything digital/technology ( Controlling for the business cycle affect) . In my previous post, I also described, how passer by’s are being tricked in consumers (pun-intended) – This in my opinion is the evolution of economics – and this evolution is VERY PROMISING, indeed !

So welcome to a world where all sciences come together in this one world ! 

And businesses always want more, they value growth & blue oceans, that’s where the meat is , afterall !

 —

Ekta Grover