What Side of the Hustle?

Some time ago I watched one of those tradicional movies about people who instead of gamble in a cassino use a systematic way, or if you prefer cheating, to beat and win a lot of money. The movie that I am talking about is the 21 and in this movie some guys from MIT with their teacher created a system of counting cards and starting to act following some roles where some of them loose some money but other members of this group  wins a lot.

Ok, this is an old fashion Vegas movie script I confess but if you go further there is a valuable talk involving a man that´s probably the cassino owner and the chief of the security (interpreted by Laurence Fishburne) called Cole Willians. Cole is an old school professional that knows how to count cards to win in blackjack and while he watches the monitors he identify this group cheating, he starts a conversation with the cassino owner (the talk that happens in minute 2):

"Let's just say I like being on your side of the hustle". That is the point. This cassino assumes that if someone who is analysing some data is cheating but in the other side it is also analysing a lot of data about his customers to create a "sistematic way of" rise his profits.

One example of this that I extract from Super Crunchers is about the Harrah´s cassinos. They knows exactly how much money you can loose in their cassino in one night and still come back. They call this amount of money of the Pain Point and when a custumer is almost hitting this point they send you a "luck ambassador" and offers something "for free", e.g. a dinner, to force you stop playing in the right time and everybody have a happy "end".

This is just one example of a company that is thinking with numbers instead of having only the "old school" skills and no matter in what side of the market you are, you should also do this. The movie also talk about old companies that did not upgraded its way of work and because of that are loosing a lot of customers, this is really happening and the main dangerous trap is that if you aren´t counting your cards probably when you discover it, that your customers had gone, it will be late.

Crunching True

A common question that is in a lot of minds today is how can someone obtain an advantage doing  data analyses, you can call this data mining or in other way, maybe in a deeper one, just like Ian Ayres says becoming a super crunchers. Once I´m intent to reveal things that aren´t so public yet  my first post will be about this question, who knows with some answers.

That are many examples of companies that uses information to achieve market advantage and in some cases a unique kind of service to grow its market share. I can mention companies that are already doing this like Amazon does with the session "Frequently Bought Together" or even "Customers Who Bought This Item Also Bought" or companies that has the potential of doing this like Google (you can see more examples in Super Crunchers).

Today I won´t discuss about the beliefs and faiths in this subject (that are a lot of pros and cons) but I will talk about how to start doing this, massive data analyses in your bussiness. The first thing is: It´s not something that you can do overnight. Selecting data digging trough hidden truths is something that you must first design what you planning to discover with this, all the companies that have successfull implementing this didn´t start its business with this subject in mind, they had its main business, its products, its services and saw an opportunity of start analysing all the data they captured during the time.

Once you already have you established business it is easier to start, and as a second advice you should always think in how can you get more data during the lifecycle of your product/service, never is enough when you think of data, get as much as you can. It is also important to identifiy any gaps that you have to fulfill your statiscal models, the data and truths around it are always changing so you must change too.

My final suggestion here is to give some steps backward and try the see the whole scene, try to imagine what data or information usefull are missing, what services you can build to aggregate more data, qualify them, something like a master data management and don´t get yourself frustrate, first look can be deceiving and nothing is so hard that you can´t give it a try, just like I am doing right now.

As you can wonder this subject is far from finish, but that is all for today folks!