Category : Analytics & Real LIfe

Analytics & Real LIfe

The world we live in is meeting us with data analytics products, applications, correlations and sometimes causations. It is interesting enough to share some findings.

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.

When a computer understands more than you do

It was 1997 when the Deep Blue computer beat the world chess champion, Garry Kasparov. It was the first machine over human victory while playing the mother of all strategic games. Well, even though the Deep Blue computer was created specifically to play chess versus human, it took just a few years more for standard desktop computers to dominate our brains on the chess board. Now there are smartphone chess apps have been able to defeat exceptionally good players.

This was the first time when the machine ‘outminded’ humans. By declaring that AI software scored a better result than humans in a large-scale reading and comprehension test, it seems we are witnessing the second breakthrough.

2018: Data Analytics Trends

It is that time of the year when you take a look back and take an educated guess on what is going on to be in the very near future of data analytics. There is no doubt that in 2018 analytical industries will be not just hot but also rapidly changing. Here are the top trends that will prevail within the New Year.

Scary Data Analytics

Most commonly applied in boosting the efficiency of a measurable processes, data analytics is hardly scary by any means. Well, just like the machines or any product of the human knowledge at all, data analytics can be a scary tool. The frightening element within data analytics is not the power of data but its usage. Prior to Halloween, we would like to share a few scary data analytics applications out of real life.

Coca-Cola Case Study: How spatial analytics makes perfectly targeted product sampling campaign

We all love nice product samplings. This is the best way to meet a product, to experience it from first hand. There are no words or even a picture capable of depicting particular taste. That’s why product sampling campaigns are deeply loved by marketers of foods & beverages. Because they work as nothing else.

Since the A4E blog is dedicated to all thing data analytics, we are willing to share our own experience on how to enhance the performance of such sampling campaign. The Coca-Cola Company representatives approached us with a pretty interesting case regarding their new 0.75l product pack. It is aimed to households consisted of 2-3 members which had to receive the sample during dinner time, providing a meal pairing experience in the comfort of their own home. Nice and sweet, isn’t it?

Why AI can`t beat the fake news?

As data analytics company, at A4E we are more than familiar with the capabilities and potential of Artificial Intelligence widely known as AI, especially combined with some kind of automation. As society members, just like you, we also know that the fake news is not just pieces of information heavily disliked by politicians with disputable reputations. This is why we are curious whether AI is capable to help users and media businesses to distinguish the real news out of fake ones.

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?


4 tips for improved sales forecast accuracy

We already discussed how important sales forecasting is to any business, not matter B2C or B2B. Proper forecasting is an efficiency booster since it is enabling proper recourses planning like staff, stock, financials, logistics, production, etc. This is especially important for businesses producing limited shelf life products.

One single KPI makes the sales forecasting good or bad. It is the accuracy. The accuracy is the crucial indicator paving any business plan to the road of success or failure. In this blog post, our data analytics team at A4E is sharing tips and hints on how to boost your sales forecasting accuracy.

How data analytics might reduce food waste

Like it or not, we all are living in a world where many people are starving while in the same time a tremendous amount of food is wasted by consumers, retailers, manufacturers, etc. Food wastage is a problem not just because is a missed opportunity for people in need. It is an issue because wasted food is incinerated in combustion facilities or is stored in landfills. Once in landfills, the food breaks down to methane, which is a strong contributor to the greenhouse effect boosting hazardous climate change. Speaking of food waste we should know that throwing an apple means we are spilling about 100 liters of water, needed for its growth. The water footprint of a beef is more than 7 tons of water.

When Data Scientists Race Some Fast Cars

Elon Musk and his Tesla Model S started it all. The premium electric sedan was equipped with advanced and self-learning Autopilot system, which can take the chauffeuring work out of the driver. It was a complete breakthrough because if it works as good as it should; it is going to change driving forever. It is all because of Artificial Intellect (AI) and the way it works fueled by data sensors and powered by video analytics. And since we have, to be honest, it wasn’t started by Elon Musk but the automotive industry itself. It doesn’t matter if we talk about rain sensing wipers (Cadillac) or adaptive cruise control (Mitsubishi) or lane departure systems (Mercedes-Benz). Such systems work with predefined events with some variables in the input data and one particular, predefined outcome.