The Big Data Trend and It's Importance In Marketing Research.

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4. Sales forecasting accuracy will improve dramatically as sophisticated algorithms supplant "gut feel" as the weapon of choice for predicting sales (Hollison, 2015).

5. Real-time sales data visualization technologies will emerge, empowering sales managers to adjust battlefield tactics based on live data feeds (Hollison, 2015).

Every industry is affected in some way by Big Data. Examples of important industries that are immensely affected by Big Data are: The Banking Industry, The Education Industry, The Government Industry, The Health Care Industry, The Manufacturing Industry, and The Retail Industry.

Case of Study # 1: UPS Company and ORION Initiative

As a company with many pieces and parts constantly in motion, UPS stores a large amount of data – much of which comes from sensors in its vehicles. That data not only monitors daily performance, but also triggered a major redesign of UPS drivers' route structures. The initiative was called ORION (On-Road Integration Optimization and Navigation), and was arguably the world's largest operations research project. It relied heavily on online map data to reconfigure a driver's pickups and drop-offs in real time.

The project led to savings of more than 8.4 million gallons of fuel by cutting 85 million miles off of daily routes. UPS estimates that saving only one daily mile per driver saves the company $30 million, so the overall dollar savings are substantial

Case Study #2: T-Mobile halving the number of Portabilities

The mobile operators and Internet have an impressive amount of data about their customers: the number of calls they make, the hours that take place, their favorite numbers, and the number of calls that are cut because of network problems. Then, after the analysis of the interactions of its customers in social networks, the company proposed to substantially reduce the number of portabilities to other competitors in the USA. To achieve this, T-Mobile used three basic tools: billing systems, social monitoring tools and Tableau software to present the data in a visual form.

Blending all the information, T-Mobile found that expectations of portabilities can be determined through an analysis of 3 factors: Bills, Calls that are cut due to poor coverage and customer conversations: positive, negative or neutral.

In this way the company went from nearly 100,000 portabilities in the first quarter of 2011 came to only 50,000 in the second quarter, down 50% thanks to a good use of Big Data and all data and information that the operator has of its customers.

Bibliography

Breeuwer, D. (2015). Big Data Marketing: Los 3 componentes esenciales para una estrategia exitosa. Obtenido de http://www.inboundcycle.com/blog-de-inbound-marketing/big-data-marketing-los-3-componentes-esenciales-para-una-estrategia-exitosa.

Hollison, M. (2015). 5 Ways Big Data Will Change Sales and Marketing in 2015. Obtenido de http://www.inc.com/mick-hollison/5-ways-big-data-will-change-sales-and-marketing-in-2015.html

SAS. The Power to Know. (March 4th of 2016).Big Data: What it is and why it matters. Obtenido de http://www.sas.com/en_us/insights/big-data/what-is-big-data.html

Zenith (March 26th of 2013) Big Data, tres casos de éxito: T- Mobile, Unilever y MoneyBall.Obtenido de http://blogginzenith.zenithmedia.es/big-data-tres-casos-de-exito-t-mobile-unilever-y-moneyball/

SAS. The Power to Know. (March 4th of 2016).Big Data: UPS Company. Obtenido de http://www.sas.com/en_us/insights/big-data/what-is-big-data.html

CSC: About Us (January 29th of 2016).Data Universe Explosion and the Growth of Big Data. Obtenido de http://www.csc.com/about_us