What’s in a Name?

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The above video presents popular baby names for US states from 1910 to 2014, starting with girl names. In 1910, the records show that Mary was the top female name and this continues to 2014, where Emma reigns supreme. Unsurprisingly John is the #1 name in 1910, but by 2014 it had dropped off the top 10 entirely. In the 1990’s the girl’s name “Mariah” became increasingly popular for a short time, perhaps due to the popularity of the pop singer Mariah Carey.  While trends like these and creative ways of visualizing data re fun for everyone, what does this have to do with Black Oak Analytics?

Traditional matching is a business process often seen in marketing spaces that uses name and address to define simply, “who’s who?” In the world of Big Data however, there are more things to look at than simply “name” and “address”. Using our entity resolution software for Big Data, called HiPER, we can look at name, address, gender, history with the company, purchasing preferences, geographic information, and so on, all of which are simply more “attributes” about the individual in question.

Trends in entity resolution include using these more detailed attributes helps us make better matching decisions, and can help business better reach their customers. In this case of the baby name video, the producers considered the attributes of time (date of birth) and location (state) in addition to first name. This most likely used what we would call a “robust matching engine” that can take a look deeper into data and take context into account. It could look at a record and see that while “Marc” and “Marcus” were different, they were close enough to be counted together for the purposes of this sample study. Business can find great value in this sort of matching, as it can help identify problems in supply-chain management, or perhaps help them find the best customers for their products.

If we wanted to market to a specific audience, say 4×4 owners in the Little Rock area who have an affinity for duck hunting, a phone book isn’t going to provide us with many leads on who to contact. However, if we look deeper into that book and see purchasing habits of consumers, types of vacations that are likely to be taken, and other economic factors, we could begin to construct a profile of the prospective customers.

If you or your organization are having difficulty matching identities, or are using existing name/address systems for your matching, contact us to find out more about how we can help you analyze your current matching processes and improve them with our high performance entity resolution software. Black Oak is all about finding connections in the data through analytics, and making sure it produces value for our customers. And why wouldn’t we? Analytics is in our name.

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