Monthly Archives : November, 2017

3 Ways Retailers Can Use Data Analytics For More Successful Black Friday

Black Friday is marking the beginning of the X-Mass shopping hysteria since 1952 when it was created as a retailer campaign aimed to clear stock on promotional prices. More than half century later, Black Friday and the entire weekend after Thanksgiving, including Cyber Monday transformed into a shopping spree, helping retailers to generate more sales and revenues. Since data is one of the key assets for any retailer, its analysis is helping to boost the efficiency and overall campaign performance. As Black Friday revenues are estimated at billions of dollars, it is worthy to get aware how to take a bigger piece of this retail pie. In this blog post, we are going to share 3 different analytics applications helping retailers to achieve more on Black Friday.

Data Scientists are 30 years old average and Python is their most used tool

Worldwide known data science community Kaggle did something nice and sweet as industry-wide survey sharing interesting and valuable information on data scientists from around the globe. More than 16 000 data scientists, analysts, experts, and statisticians joined the Kaggle survey which is full of interesting insights. Among the most important is the fact that 3 of every 4 participants rely on Python, followed by R and SQL and the logistic regression is the most commonly used data science method, followed by decision trees and random forests.