The world of Hollywood is full of worldwide fame, glamour, and big bucks but there is an entertainment industry which is way bigger. Please welcome video games! The revenues generated by all kinds of video games are more than twice than the financial results of the movie industry. And it is growing at a constant pace. On top of this, gaming is generating a huge amount of data. Electronic Arts have 275 million active users generating 50TB data a day. It is no surprise that gaming industry is utilizing data analytics in its full scope. Technology, financials, gameplay, marketing, strategic, just name an analytics domain and you`ll find it working on high revs in the gaming industry.
The modern business world is on hype about data analytics and there is a reason. Digging deep into historical data strings is a way to valuable insights that might generate new revenue streams to boost efficiency and to discover improved ways of doing things. Does this mean data analytics cannot fail? Of course not.
In this blog post, we are highlighting 5 different cases where data analytics failed one or another way. Not matter it was because of wrong presumption, bad execution, missing variables or wrong numbers – the results were at least surprising and definitely not nice.
Regardless of its size, any fashion or apparel manufacturer is confronted with challenges related to predicting the future.
Unlike the big brands that manage to create and impose trends, smaller players try to foresee what will be the forthcoming changes in consumer tastes. Trends might arise even from occasional events, take for instance Converse sneakers which became a big hit after rock bands like The Ramones wore them onstage on their gigs at the late 70s and early 80s.
Apparel manufacturers often can do nothing but to follow and adapt according to trends. Discussing fashion and apparel, such shifts affects everything – size, color, shape, fabric, price, etc. are a piece of the equation for success or fail.
Running retail business of any kind might be extremely tricky process full of unknown variables. Full scale analytics service provider is able to offer you a lot. But in depth analytics projects demand lot of recourses, hence money. Big retail businesses already benefit from analytics services because of their large scaling and that’s how they improve their profitability even more. This is raising following question:
Are small retailers able to benefit from data analytics?
Beyond the basics, modern sports has nothing in common with what it was, let’s say 50 years ago. One of the many, many reasons for this is the data analytics and forecasting.
We are living in a world full of data and everyone can benefit of it with proper analytics modelling. Speaking of sports it helps decision making in player selection, customer/fan relationships, business management, game and players performance and even injury prevention.
The coffee shop industry is making billions dollars a year. Even though opening your own coffee shop looks like a piece of pie and definitely profitable enterprise, it is not exactly like this.
The value of a cup of coffee is around $0.50 and the retail price is between $2 and 3, depending on the market. It sounds like profitable margin. But you have to keep in mind that operational costs for a coffee shop are quite high. On top of this you have to add the fierce competition by well-established chain of coffee shops with strong marketing and huge advertising budgets.