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Application and Opportunity of Big Data Analytics in
E-Commerce
In our last blog, What is Big Data and How Fast is it Growing?, we discussed the basics of
Big Data-
What is Big Data?
How much data is “Big Data” and how fast is it growing?
What are the characteristics of Big Data?
Examples of Big Data
So, what is the obsession about “Big Data” and “Big Data Analytics”?
“Information is the oil of the 21st century, and analytics are the combustion engine.” –
Peter Sondergaard, Senior Vice President, Gartner Research.
Big Data Analytics is taking big data, creating predictive model to obtain actionable
insights by building data products to communicate relevant and meaningful insights that
drives value. – Carlos Somahano, Data Science London. In simpler terms, make sense of
the data and draw meaningful insights.
IDC report on the study of the digital universe showed that from 2005 to 2020, data will
grow by a factor of 300, from 130 exabytes to 40,000 exabytes, or 40 trillion gigabytes. In
other words, the digital universe will about double every two years.
In our previous blog, we outlined the different types of data – structure, unstructured and
semi-structured. It is estimated majority of data generated will be unstructured data and
the real value is derived from analyzing unstructured data.
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Source: Data Science Central
Application of Big Data Analytics in E-Commerce
Big Data is being used across sectors. We will take a look at how Big Data Analytics is
changing the E-Commerce landscape.
In E-Commerce, most of their data would fall under two categories – structured and
unstructured. Their structured data is their regular data they have been able to capture –
name, address, and preferences, sex and age (in some). The more valuable piece of data
which is not captured but extremely important is the unstructured data – likes, tweets,
clicks, videos etc. The challenge is how to take the unstructured data and make it
meaningful insights to increase conversions. According to an article from Harvard Business
Review, “it is estimated that Walmart collects more than 2.5 petabytes of data every hour
from its customer transactions. A petabyte is one quadrillion bytes, or the equivalent of
about 20 million filing cabinets’ worth of text. An exabyte is 1,000 times that amount, or
one billion gigabytes.”
Big Data and e-Commerce Application – E-Commerce companies have become one of the
fastest adopters of Big Data and it’s analytics importance. The dynamics of the industry is
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changing constantly and most companies are operating in razor thin margins.So, how are
companies using Big Data Analytics to stay on top of their game?
Personalization
How can companies enhance and personalize each customer’s experience at scale?
Personalization can help companies increase conversion significantly. Gilt Groupe, one of
the leading e-commerce companies in “flash sales” has used it very effectively. According to
Zachray Tumin, Harvard University, “The company sends 3,000 highly targeted emails
each day to its 3.5 million members. These emails are based on what Gilt Groupe’s
members have shopped for and liked, matched up against luxury fashion and home
products that Gilt has thoroughly profiled by who likes them.” Research shows that
personalization can deliver five to eight times the ROI on marketing spend and lift sales
10% or more – Harvard Business Review.
Improving Customer Experience
One of the biggest expense for e-commerce companies is user acquisition. Once the user
lands in the site, it is extremely critical for them to make a conversion. The competition is
tough and most consumers have wide range of choices for the same product. E-Commerce
are using analytics to enhance customer experience. Companies are closely analyzing the
buying path for each customer and improving customer experience making it a seamless
process. Companies are analyzing data from customer service call and improving
processes. bloomreach, a startup is aiming to use Big Data to enhance the eCommerce
customer experience.
Pricing
E-commerce companies need to have the ability constantly change pricing on millions of
SKUs on a everyday basis based on competition, demand for products etc.
Predictive Analytics
How can E-commerce companies predict consumer behavior? Amazon’s third party
marketplace is an example of how it is less to do with individuals retailer’s marketing
ability and more of Amazon’s ability to use analytics to predict what the buyer is likely to
purchase. Another example is Target’s ability to predict customer pregnancy from
shopping behavior. E-Commerce predictive analytics using big data can also allows
companies to forecast external events and it’s ability to adapt to it.
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Managing Supply Chain using Data
E-Commerce companies are dealing with lot of moving parts – vendors, logistics,
warehousing, delivery, returns etc. E-Commerce companies are building efficient systems
using analytics to manage the process. Companies are using Internet of things, to collect
and communicate data on a wide range of conditions and redefining supply chain
intelligence.
Related Article:
1. What is Big Data and How Fast is it Growing?
2. Why Big Data is Next Big Thing?
Links which can be useful to you regarding this topic are
Big Data Hadoop Course in Bangalore