Irrespective of the time period or nature of the business, leaders have been leveraging techniques and technologies to gain a competitive edge in their market since time immemorial. However, in the modern age, there is one particular science which provides businesses with an advantage that they simply cannot say no to!
Yes, you guessed it! That science is big data analytics! With changing times and technologies, companies from diverse sectors are banking on big data and are incorporating it in their operations, marketing and market research, product design, business optimisation, enhancing cybersecurity and many more applications.
The unique thing here is the above-mentioned diversity. The sheer number of companies that use it are incredible, and today you’re going to find out just how unique the applications of big data analytics really are!
Here are some companies which have made a killing exploiting the benefits of big data.
With over 100 million users, Spotify is a completely data-driven company and has truly and completely incorporated big data. Spotify uses data intelligence of factors such as the playing time of a song, where it is being streamed, devices used to stream the song, when are they being played etc. giving the Spotify team captivating insights to impact listener experience.
Also, data analytics techniques are used in Spotify’s artist application feature, which gives data access to the artists so they can enhance their marketing and content.
In addition, the music streaming provider utilises big data for its ‘fans first initiative’, which allows an artist to reward their dedicated fans with special offers on purchase of their music, merchandise etc. and also at times give fans free concert tickets or backstage passes to concerts and live events in their cities! How cool is that?
Traditionally, dating sites use surveys and personality tests to determine a person’s preferences and utilise algorithms to match people with a high probability of being compatible.
eHarmony is bringing about a change in how couples can be matched. eHarmony is banking big on big data to help its user find a partner/date. The platform utilises data intelligence gathered from wearables, which can record sleeping patterns, physical activity levels etc. as these factors can be essential while matching a partner.
Also, people tend to provide false data on dating websites such as being physically active, not being a night owl etc. to make their profiles look impressive. By using actual data, eHarmony can pair people based on their actual honest habits!
3. IBM SlamTracker
IBM SlamTracker is helping elite sports-persons track, analyse and improve their performance on the field by using real-time bio-mechanic data. IBM SlamTrackers use sensor technology embedded in sports equipment such as a basketball, baseball bat, golf clubs, tennis racquets etc. allowing players and team management to access real-time data. This real-time data is used to design training programs, thereby helping players to adapt to modified actions, which can improve their on-field performance.
For example, a golf player can gain a few extra yards on the green by adjusting their swing by a few degrees. This is then incorporated in their training routine to achieve the desired angle to be replicated in sporting events. It is one of the ways data analysis is providing sportspersons with a competitive edge which can be the difference between winning or losing a tournament.
Amazon has a large customer database recording customer data, their buying history, search history etc. Results of statistical analysis of customer data are used to design advertising algorithms and Amazon frequently uses this information to improve customer relations. For example, when a customer contacts the Amazon help desk, the employee handling the call already has required customer data, which allows faster resolution.
This entertainment streaming service has a treasure of data and banks heavily upon data analytics to understand consumer viewing habits. Decisions related to buying rights of movies and films and commissioning original programming are made based upon data analytic results, which help predict acceptance within an audience demography and accordingly target them.
For example, even though Adam Sandler had been unpopular in the US and UK markets, Netflix commissioned four new movies with the actor as his previous movies had been quite popular in the Asian and Latin American markets. This decision was purely based on data analytic results arming Netflix with knowledge of the performance of previous Sandler movies.
There you go then! Quite a diverse range of applications, right? And the list goes on and on. So, if you have a natural liking for all things data, you too can make waves in your industry of choice by taking up a data science training course – something which will help you understand the dynamics of this incredible field!