This is Ozgur Kenanoglu, Digital Excellence and Data Driven Marketing Manager of Unilever Turkey, Central Asia and Iran. I am working with an ambition to “transform for the better.” Unlike mainstream marketing; I’m trying to establish a new structural strategy of the way we do marketing to reach out more people in a manner. I would like to improve my data science skill set to utilize my capability on making the world a better place in terms of sustainability and genetic conditions improvement.

useR! 2019 Toulouse - Talk Biostatistics & Epidemiology 1 - Zhian Kamvar

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Provided video remarks advanced data analytics and its correlation between work of Epidemiologists. italic The profession of Epidemiologists are people who focus on issues relation to disease outbreaks in order to avoid them. italic Zhian Kamvar has been able to hold a hacktahon with a focus on utilizing R with epidemilogists ambitions to overcome problems. Their biggest challenge was not having access to data, but they had been able to use random stimulated data from R dictionary. I believe this is the beauty of R world, one can simulate a world by simply using a random data set!

Before hackathon they had an agenda of lower burden on epidemiologists with a motto of Doctors without borders.In order to do so, they have chosen significant reports which includes surveys and outbreak reports (ie: cholera, meningitis…etc.)

After sorting out the relevant data they tried to ease their work but there was not capable packages on R, therefore they have utilized RMarkdown.

Some Intersections between R and my profession

Data Science Project – Customer Segmentation using Machine Learning in R

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This posts alludes to customer segmentation with help of some R packages. One can use them to classify bulk data with a structural design thinking to obtain marketing strategy.

Customer Segmentation for a retail supermarket using K-means clustering

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Another customer segmentation is done for a retail supermarket. The world is omnichannel and the behavior we do in offline world reacts into digital which produce significant amount of data.This project enables us to see how R can be utilized for segmentation based on customer demography with some shopper behavior.

Customer Segmentation using RFM Analysis (R)

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RFM (Recency, Frequency and Monetary Value) model is a highly used strategical touchpoint especially in Customer Relationship Management (CRM) programs. This project is utilizing R with this scope.