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Queen Bees, Elephants and Big Data

A good friend has recently embraced bee keeping and has been posting pictures and videos on line (together with a live web cam from the hive). One of his videos he posted the other day showed the queen bee’s interaction with the other bees in the hive (which I was aware of but had never seen).  It reminded me of how on a recent interview with a journalist, despite me sharing several anecdotes about useful discoveries thanks to Big Data, the one that made it into the article was the one about queen bee analysis. It involves analysis of information using Big Data technologies like Hadoop that allows you to spot people that have a disproportionate impact on the users around them.

The first time I came across this kind of analysis was when working with a telco – the chief architect had noticed some interesting things about his teenage daughter’s interactions with her friends. Even though she was on the lowest cost plan with the network and had very few talk minutes, it included unlimited SMS and text messaging and she was using them extensively. She had also created a friends group where with a few clicks anything she wanted to share could be forwarded to a large distribution list. As a result, the company viewed her as a low value customer given her limited revenue, but when her dad got her a new handset and she started updating her friends about the new features, many of them upgraded (some even switching networks to do it).

The ability to recognize these users requires the combination of a large number of different indicators − often housed in a variety of different systems − it’s not enough just to find users that send a lot of messages as often the highest volumes come from spammers.  So you need to find users that interact with other users and create a response. Also interactions can switch, for example, an SMS message may then result in a Facebook post or tweet which could then cause a phone call.

The interesting thing about queen bee analysis is that it’s not constrained to a single vertical – the same interactions that occur in telecommunications are relevant in retail, financial services, life sciences etc. and can also identify “queen bees” that could have dramatic impact ─ both positive and negative ─ on a company’s bottom line. This is clearly an interesting topic, so it might warrant some more detailed explanation or comments from one of our internal experts. Please reach out to me and let me know if you’d like to know more.

The article that included the mention from me is located here

Queen Bee


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