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.