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Look before you leap into big data analytics
by barry ooi
ONE of the most widely discussed topics in the marketing fraternity today is big data. Everybody
recognises that there’s a lot more information today than ever before.
The amount of data available is no longer in gigabytes but terabytes and zettabytes. How big is a
terabyte? It is equivalent to 333,333 songs, if your average MP3 is three megabytes. A study by IDC
predicts that overall data will grow by 50 times by 2020 and it’s commonly acknowledged that the rise of
social media, the Internet and multimedia is fuelling this exponential growth.
Organisations may not necessarily have that much of data but it will have truckloads of information to
deal with! All companies have information of its customers such as name, address, telephone number,
email, date of purchase, types of purchase, how and where the purchase took place, and first-time
customer or repeat.
In addition, it will also have industry information, eg. industry growth and trend on where the industry is
heading.
Another common piece of data in a company’s arsenal of information is sales. Typically, the details are
sales by product type, by salesman, by customer segment, by region or area and by channel. There’s
also data on media spend, distribution, promotion. I could go on to add on the list but I believe you get
the picture.
Everybody understands that data on its own is ineffectual. The value lies in turning these huge junks of
information into insights.
Big data analytics is about examining large amounts of data of a variety of types to uncover hidden
patterns, unknown correlations that will enable the organisation to have a deeper understanding of its
customers or consumers’ purchase behaviours. The primary goal of big data analytics is to help
companies make better business decisions and at a faster pace. Such information can provide
competitive advantages and more effective marketing and increased revenue and market share.
Most companies today do not have the right tools and platforms to put big data into practice. The most
common practice is: an executive is assigned to compile the disparate data files or sources into a
common application, usually an Excel spreadsheet. The tabulations will then be exported into
Powerpoint for management attention. This process could take a week to several weeks, depending on
the number of data sources and complexity of the output required. This routine is too long in today’s
intense competition and the organisation would have missed out on some tangible opportunities.
Before you embark on big data initiative, consider the following points:
1. It’s not an IT Solution: Big data is complex and tricky. Yes, you do need great software but this is
just an enabler. You need to involve people who are familiar in working with large data sets ie Data
Experts, as well as consumer behaviour professionals.
2. It’s not about data but insights: The potential of big data is in its ability to generate new insights and
provide new opportunities from existing data. So to get the most from your big data, focus on the
questions you need to answer. This mindset is important as it will alter your perspective; changing big
data from a technological problem to a business solution.
http://www.thestar.com.my/Business/Business-News/2013/11/23/Look-befor...
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3. Proven applications: There are quite a number of tools and software that are designed to handle big
data analysis. Select the application that meets the following:
·Already a working platform and system with solid credentials
·Ability to integrate and harmonise multiple data sources
·Has data visualisation capabilities in order to deliver results in a visually engaging manner
·Has statistical functions which will allow for sophisticated statistical analysis
4. Take a journey approach: Big data is new territory. Build your platform over time instead of all at one
go. This will help to mitigate the risk in investment costs and avoid major disappointments in big data
implementation. Begin by defining the types of decisions that are critical to your business, eg. Are our
investments in customer service paying off? Why are our customers defecting? What is the best channel
to communicate to our customers?
5. Deliver business value: In order to justify the expense and further investment into big data, you need
to deliver its value very early on.
The goal is to show how big data can deliver tangible results to business objectives. Use the findings
from big data analytics, implement a project and measure its results. Communicate the results to not
only the senior-level managers but those all who are involved in its success.
Adopting big data must go beyond data warehousing and information security. The value is in the
analytics and it’s about generating business trends and insights from the reams of data created.
BARRY OOI is Marketing Research Society of Malaysia president and Potentiate Malaysia MD.
http://www.thestar.com.my/Business/Business-News/2013/11/23/Look-befor...
25/11/2013