Tag : data analytics

Price Elasticity: A million-dollar retail question

A DIY retailer, for instance, has the potential to increase its sales revenue by 1 – 2% annually with price elasticity of demand application.

Meeting customers’ needs is essential for a retailer wellbeing. A retail business failing to do so will be simply pushed out of the market, soon or later. Some retailers rely on their gut feeling but as data analytics experts, we are perfectly familiar with Arthur Conan Doyle who once said, “It is a capital mistake to theorize before one has data”.

How AI & Data Analytics could have prevented an amazing Spotify fraud

We`re not sure if you already have heard about this and if not, keep in mind that those couple of minutes will be more than worthy.

The Spotify Fraud

Unknown scammer, allegedly from Bulgaria generated about $3m revenue out of creating and continuously playing a couple of playlists with tracks with an average length of 43 seconds. Spotify is paying artists about $0.004 per play and the fraudster has registered around 1200 premium Spotify accounts, continuously rolling the playlists.

It is believed that such ‘performance’ was achieved via bots automating the skip and play game regarding the Spotify policy to pay for a listened track only its 30 seconds or more. This way, the playlists called ‘Soulful Music’ and ‘Music From The Heart’ became played so many times they made it to number 84 globally and 22 in the US in the playlists charts.

How to apply data analytics to call centers

The call center is perceived as the nervous system of a company. It can warn of risks and potential threats, gather information about the environment in which the company operates and last but not least – it is the direct link to the most important asset that a company can have – its customers. Like any nervous system, it processes a huge amount of information. If such information is quantified, then we have big data. The application of big data analytics within call centers is the focus of this blog post.

Before we share our understanding of the application of data modeling and analytics for call & contact centers, we want to dispel a common misconception.

Leo Messi should be the best-paid football player but he is overpaid. Data analytics explains why

Named as one of the best currently active football players in the world, Lionel Messi is also one of the best paid among them all. His Barcelona contract alone is securing him a payment of €40 M per year or €770 000 per week.

Well, recently performed data analytics model confirmed what we all suspected. Even though Messi should be the best paid, he is extensively overpaid. The model and its results are described in a study conducted by a team of Lawrence Technological University in Michigan, which used machine learning and data science to analyze the salaries of 6082 professional football players in Europe. The salary of each was compared to a set of 55 attributes, reflecting each player`s skill set. The model is evaluating scoring and passing accuracy, aggression and vision on the field, speed, acceleration, ball control, physical condition, etc.

How Banks Utilize Data Analytics. 8 Areas of Application

The banking industry is a specific one with the fact it generates and collects an impressive amount of data. Combined with predictive analytics and connectivity, data opens the door for endless opportunities of boosting business efficiency. In this blog post, we are pointing at just 8 of them. Feel free to add some more in the comments below.

Product portfolio analysis: What to do when it`s made

Product portfolio analysis is a crucial tool for any business with a stack of products or services on the market. The approach can differ but at the end of the day, the desired result is a valuable assessment of business units. Boston Matrix, also known as growth-share matrix is one of the proven methods and at A4E we`ve built a tool to simplify the task by evaluating a product contribution to the overall profit and its popularity among the customer base.

Here comes the question – what to do when our report is done? Are there recipes for successful business decision when the data is sorted and properly displayed? What are the insights we can extract out of the products categorized as Stars, Dogs, Cows, and Puzzles? How to turn a Puzzle into Star or a Dog into a Cash Cow?

Puzzles

How data analytics affects music industry and is forming new trends

We don’t know if you know but a few years ago, the major music labels had pretty sweet business. They profited from any single or album, not matter it was vinyl, CD or even cassette. It is not like this anymore. MP3, torrents, piracy, streaming, and video sharing networks killed this particular business model. What music labels did to stay afloat? They asked data analytics for some help. And they were not alone – a lot of businesses emerged and shaped their models by applying data analytics to music services. We are going to explain this.

Data analytics knows if you are going to survive the sinking of Titanic

The sinking of the RMS Titanic is probably the most tragic event in the modern maritime history. It was not the deadliest though but it became the symbol of the human bigotry in terms of technical advancement. Back in 1912, Titanic was the largest, and most luxurious ocean liner ever made. She was claimed to be unsinkable. And she sank on her maiden voyage to New York.

Dealing with multivariable analytics models

Nowadays, mankind possesses a tremendous number of data, regarding many real-life phenomena. The availability of such a source of information is the main premise for the wide spread usage of the data-driven modelling. When account for more factors in the model development, this usually leads to a better ability of the model to represent the specifics of investigated system. Naturally, in fields like economics, society, medicine, etc. the models are with many inputs and many outputs (MIMO).