Thursday, September 15, 2016

How Companies Are Using Big Data

Big Data has received a lot of attention over the past few years. Mostly retail, technology, and service companies have realized that using Big Data can help them gain a huge advantage over its competitors. Companies like Amazon have taken advantage of this situation and implemented the use of Big Data within its daily operations. For example, if you have a problem with your Kindle, you can place a service request on Amazon’s website. Then, a customer service representative will call you within seconds. The customer service representative will already have your information pulled out along with the problem you are trying to resolve. Amazon’s customer service allowed its customers to have a hassle-free experience by building trust and a relationship with them.

This article provided a fresh perspective on how companies such as Amazon will use Big Data to their advantage. I think the usage of Big Data is crucial today since many companies lack personal touch in their communications with customers. Customers are tired of being treated as a mass, since they want companies to treat customers as individuals. It’s great to see companies are improving on their customer outreach tactics. For example, Netflix actually tracks and stores the TV shows or movies that you watch most often and then builds a custom list of TV shows or movies that is recommended for you. This creates a personal touch, where the viewer would be able to see a recommended TV show they have never heard of. I’ve also seen this type of data collection from the music app, Spotify. Spotify collects data on the music you listen to and then creates a playlist of recommended songs for you. This is a great way for Spotify customers to listen to new genres and artists they’ve never heard of before.

Companies must learn how to collect and use the data from customers. I think there is a fine line on how much data companies should actually acquire of customers. There may be a privacy concern, where some customers might not feel comfortable with giving away their personal details to companies. So, there should be an option to opt-out of certain information criteria during the collection process. However, I still strongly believe in Big Data as a good thing. Big Data will help both ends of the spectrum. Companies will be able to gather valuable information on how to serve their customers better and customers will have a much more tailored experience. I feel that as long as companies keep their data collection transparent and allow customers to have control on what they share, then Big Data is the way of the future.



  1. This comment has been removed by the author.

  2. Chris has provided some tremendous examples of the application of "big data" in our everyday lives. I can certainly say that because of Spotify's ability to capture my taste in music, I've been introduced to new artists and albums which I have never heard. It's a great thing-- Spotify reinforces a satisfied customer base and learns where to develop its musical catalogue, and I receive a personal touch in musical curations!

    That being said, I would add that I think that "big data" is still very "noisy" in terms of the aggregation methods employed by companies. It's in this "noise", too, that customers may feel as if their privacy is breached.

    Upon first evaluation, it makes sense that a company would want to collect as much data on a customer/user as possible. However, in actuality, this can blur their plans for application. I'm of the camp that companies should clearly define a purpose/intent for their collection (beyond just "learning about its users/customers"), and state very explicitly the purpose of their collection. For example, maybe Spotify seeks to gather data on how users are accessing Spotify: on their smartphones, via their web client, or by using their desktop application. Or, maybe they want to learn about what genres are popular in different age groups and genders.

    In defining a purpose, a company can better focus on what types of data it should collect, eliminating excess data, or the aforementioned “noise”, from its collection (which, in turn, cuts down on analysis time and cost). Versus casting a "wide net" in search of as much data as possible, this proposed method better benefits both the customer in terms of product/service development and offerings and the company in terms of efficacy and cost-efficiency during a collection period.

    Considering that data-mining and “big data” are burgeoning fields, companies are still in search of the best way to leverage data to its advantage. There is no cookie-cutter, one-size-fits-all approach to data-mining; its application is industry and company specific. That’s the trouble. But as the old saying goes, nothing worthwhile ever came with ease.


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