Big Data approach and strategy for retail. A practical and pragmatic view towards Big Data in retail.

1. technology
Big Can Reap Big Returns in Retail
Big questions, big data, big
answers, big returns – this would
have been a short and sweet story for
big data in retail and that too with
a happy ending. For a generation of
retailers who have grown up on MIS
reports evolving into dashboards and
trend analytics recently, it will be a
steady and gradual journey towards
In today’s digital world, no other industry has the
Data
potential to witness an exponential rate of growth of data
than retail. More and more retailers are warming up to
draw blueprints on ways to identify, capture and harness
mountains of raw data into manageable business cases and
actionable insights with tangible business benefits
By Shijo Sunny Thomas
comprehending and realizing the influenced even before interacting manage, process and analyze can be
big-data business case. The current with the retail channels, and purchase classified as big data. Each item on a
reports and dashboards would have opinions are shared way beyond the retail invoice, customer service call,
been created out of transactional data, point-of-purchase. In such a case, it email, social media activity and each
with the data sourced from within the becomes imperative for retailers to tweet present an opportunity for data
boundaries of the retail organization. capture customer feedback from data to be generated in retail.
These sources would range from sources outside their realm of physical Consider these opportunities in
point-of-sale and customer database influence. the light of an increasing consumer
to supply chain transactions. So, the first question that many population with increasingly complex
As retail channels evolve, the retailers ask would be, how big is big demographics and a growing affinity
customer interactions transcend data? The answer is simple: any data towards digital channels and devices.
into areas outside the boundaries volume and data type that is beyond The proliferation in product lines,
of a retailer’s control. Shoppers are the current capabilities of a retailer to stores, social-media platforms and
98 . images retail . december 2012

2. technology
digital devices represent a potential variety of data can be as structured as from store-video feeds. These can
permutation to generate data of the point-of-sale data and as unstructured provide information around how long
highest magnitude. In reality, this is as store-video feeds. The volume of do shoppers spend in a particular aisle
just the beginning of things to come. data amassed by retailers can easily or their interactions with products.
We have only accounted for scenarios be a few terabytes a day depending The implications of big-data insights
where humans generate data. How on the variety. Velocity is the speed at range from customer analytics and
about a future where devices interact which data is captured from its source merchandising decisions to store
with other devices and generate and turned into meaningful insights. performance, assortment management
volumes of data? This will create a It is evident that technology decisions and loss prevention. These are areas
data heap that will make finding a depend highly on the variety, volume where it is necessary for retailers to
needle in a haystack look easy. and velocity of data. rapidly take decisions based on a
The case for big data can very often Fortunately for today’s retailer, quick understanding of the customer
get overwhelming and intimidating inexpensive hardware and innovations profile, brand interactions, sentiments
for many retailers. Often, the and basket size. The decisions can be
business value of harnessing big data in the form of accelerating product
is wrapped along with additional shipments from various locations,
layers of technology such as cloud, mark-down decisions or initiating
mobility and analytics. Since vendor replenishments in
a lot of these aspects are in advance.
an evaluation stage in many In an industry with razor-
markets, there are chances of a thin margins, defining and
big data idea being put on the executing your big-data
back burner. This often tangles strategy has the potential to
the business value and the ROI bolster the retail margins by
model becomes complicated. a significant extent. Granular
Therefore, it is important to customer insights leading to
understand how retailers can form highly personalized messages
a pragmatic strategy and approach to the shoppers will lead to an
towards big data within the retail increase in the basket size and as
organization. well as in the number of shopper
Defining and implementing a big- visits to retailer stores.
data strategy involves decisions across Another area where retailers stand
multiple technology layers to decide in processing capabilities coupled with to gain from big data is customer
on the execution model. The journey the scalability of cloud computing service where service requests can be
for a retail organization should can be ingredients to an attractive fulfilled in the shortest possible time
commence with first evaluating big-data value proposition. This way, and in the most precise manner. Big
if the organization is a big-data the retailer can concentrate more on data implementation eventually pays
candidate. The evaluation process the operational and business-oriented for itself when the ROI is measured
consists of forming a business case aspects of big data. This involves against reduced cost of operations,
and associated business scenarios. In integrating to various sources of big efficient assortments and reduced
most cases the scenarios are in the data and translating the data into a stock-outs.
area of offering highly customized manageable and analysable form. So, hopefully within a few years,
promotional offers, analysis of These are used to define analysis if a customer tweets about how
promotional effectiveness in real models where substantial inputs are a rain spoiled her day, she would
time or analysis of store space required from the business users to immediately receive a discount offer
effectiveness by analysing the shopper define the various actionable items for an umbrella. To her surprise, the
path. Breaking up the business that can be created out of the data. color of the offered umbrella would
case into scenarios helps retailers Now we are entering the realm of big match with the dress she bought two
identify current technology and skill data analytics which is ultimately the weeks earlier from the store!
limitations, investments and the wow factor in big-data management.
associated returns. Retailers can benefit from big data
Identification of various candidate to such an extent that each customer
data sources that will serve as can be classified as a separate ABOUT THE AUTHOR
inputs to the business scenario is segment. Shopper behavior can be Shijo Sunny Thomas is the
essential to get a firm grip on the data tracked across all channels and the Industry Lead–Retail & CPG at
Fujitsu Consulting India. He has
characteristics. These characteristics information can be correlated with worked extensively in advisory
are popularly classified into areas the current assortment characteristics. and operational roles with
of variety, volume and velocity. For Retailers can also tailor the store and medium to large cross-channel
each candidate business scenario, the shelf space through insights gathered retailers
december 2012 . images retail . 99