Thursday, November 27, 2014

Big Data: Opportunities vs. Threats


As marketers, we are receiving overwhelmingly amount of data from multiple channels everyday. We all know that big data provide us with the ability to make more insightful decision. But what exactly is Big Data? 


Once upon a time, marketing is completely an art. Agencies creates ads based on guts. “Leo Burnett didn’t need a legion of focus groups to come up with the Marlboro Man”. With big data, however, marketing is now becoming a combination of arts and science.

For example, the article "Big Data, Big Opportunity" by David Murthy discovers that mobile has become a trendy devices for customers, and ad spending has been significantly increased in the recent years. You may find the full article via:


This finding tells us the consumer behavior of using more mobile devices. However, what are some in depth insight marketers may find in mobile using behavior. For example, If consumers are using mobile than other devices to engage with your brand, marketers could put more investment on mobile ad. If consumers are just browsing one or a few products from your brand, marketers may put design more ads of these particular products on mobile. If consumers are simply browsing your products instead of purchasing with mobile devices, marketers may design easily purchasing feature on mobile to encourage mobile orders, and thus to drive direct orders. Big data tells us some commons sense we might have ignored before, and we should all using the data based on our own needs.

However, marketers can be drowned by data as well. Jeanne W. Ross, Cynthia M. Beath and Anne Quaadgras' article You May Not Need Big Data After All tells that big data has been “hyped so heavily that companies are expecting it to deliver more value than it actually can.” This article illustrates that some companies, even have obtained the consumer insight that may provide them with competitive advantage, however, are not actionable at all. You may find the full article through:

For many companies, the real purpose of big data is to provide evidence for decision makers, and to utilize data to guide decision making process constantly.

Several steps were suggested to improve big data efficiency:  

1.   Making a clear business plan. It is important to define the goal of data, and have a clear vision of how could data contribute to a specific case. Understanding how data would support the business goal, ensuring your effort can be aligned with the business goal.

2.   Understanding the data you already have, and identifying those data you need. Collecting and analyzing data with a reason.

3.   Turning data into structured insight after capturing the data.

4.   Making your data and insight actionable. Based on the original plan, execute the planned project by using elements of the big data. Always keeping ROI in mind.

5.   Making strategic plans and tactics to solve the problem. Testing the market and keep track of the ROI. 

In conclusion:
Big data gives marketers both opportunities and threats. Many companies may put too much effort in collecting too much data without integrating data analysis into profitably used with a business vision. We should always keep in mind that big data is just serving for the company, and we are not serving for the data. 

The author, "Alisha" Fengzhi Chen is an integrated marketing communication graduate student at Northwestern University. She is particular interested in turning data into actionable insight and marketing strategy, therefore to improve ROI. You may contact the author via +Fengzhi Chen twitter: @fengzhichen

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