Real-time data analytics from customer interactions

the ghosts in the machine by MelvinSchlubman (cc) (From Flickr)
the ghosts in the machine by MelvinSchlubman (cc) (From Flickr)

At a recent EMC product launch in New York, there was a customer question and answer session for industry analysts with four of EMC’s leading edge customers. One customer, Marco Pacelli, was the CEO of ClickFox, a company providing real-time data analytics to retailers, telecoms, banks and other high transaction volume companies.

Interactions vs. transactions

Marco was very interesting, mostly because at first I didn’t understand what his company was doing or how they were doing it.  He made the statement that for every transaction (customer activity that generates revenue) companies encounter (and their are millions of them), there can be literally 10 to a 100 distinct customer interactions.  And it’s the information in these interactions which can most help companies maximize transaction revenue, volume and/or throughput.

Tracking and tracing through all these interactions in real-time, to try to make sense of the customer interaction sphere is a new and emerging discipline.  Apparently, ClickFox makes extensive use of GreenPlum, one of EMC’s recent acquisitions to do all this but I was more interested in what they were trying to achieve than the products used to accomplish this.

Banking interactions

For example, it seems that the websites, bank tellers, ATM machines and myriad of other devices one uses to interact with a bank are all capable of recording any interaction or actions we perform. What ClickFox seems to do is to track customer interactions across all these mechanisms to trace what transpired that led to any transaction, and determines how it can be done better. The fact that most banking interactions are authenticated to one account, regardless of origin, makes tracking interactions across all facets of customer activity possible.

By doing this, ClickFox can tell companies how to generate more transactions, faster.  If a bank can somehow change their interactions with a customer across websites, bank tellers, ATM machines, phone banking and any other touchpoint, so that more transactions can be done with less trouble, it can be worth lots of money.

How all that data is aggregated and sent offsite or processed onsite is yet another side to this problem but ClickFox is able to do all this with the help of GreenPlum database appliances.  Moreover, ClickFox can host interaction data and perform analytics at their own secure site(s) or perform their analysis on customer premises depending on company preference.


Marco’s closing comments were something like the days of offloading information to a data warehouse, asking a question and waiting weeks for an answer are over, the time when a company can optimize their customer interactions by using data just gathered, across every touchpoint they support, are upon us.

How all this works for non-authenticated interactions was another mystery to me.  Marco indicated in later discussions that it was possible to identify patterns of behavior that led to transactions and that this could be used instead to help trace customer interactions across company touchpoints for similar types of analyses!?  Sounds like AI on top of database machines…