The retail industry is undergoing a dramatic shift, as today’s technologically empowered consumers find new ways of transacting with retailers. Online shopping, Mobile commerce and Social media have provided the consumers with an interconnected network for sharing opinions, reviews with each other on brands and products - in turn creating vast volumes of Data. These and other changes in the retail industry are creating important opportunities for retailers. But to capitalize on those opportunities, retailers need ways to collect, manage and analyse a tremendous volume, variety and velocity of data. Simply put, adopt new approaches to keep customers engaged, maintain a competitive edge and maximize profitability.
1. IBM Software
Big Data
Retail
Capitalizing on the power
of big data for retail
Adopt new approaches to keep customers engaged,
maintain a competitive edge and maximize profitability
2. 2 Capitalizing on the power of big data for retail
The retail industry is changing dramatically as consumers
shop in new ways. With the growing popularity of online
shopping and mobile commerce, consumers are using more
retail channels than ever before to research products,
compare prices, search for promotions, make purchases and
provide feedback. Social media has become one of the key
channels. Consumers are using social media—and the
leading e-commerce platforms that integrate with social
media—to find product recommendations, lavish praise,
voice complaints, capitalize on product offers and engage in
ongoing dialogs with their favorite brands.
The multiplication of retail channels and the increasing use of
social media are empowering consumers. With a wealth of
information readily available online, consumers are now
better able to compare products, services and prices—even as
they shop in physical stores. When consumers interact with
companies publically through social media, they have greater
power to influence other customers or damage a brand.
These and other changes in the retail industry are creating
important opportunities for retailers. But to capitalize on
those opportunities, retailers need ways to collect, manage
and analyze a tremendous volume, variety and velocity of data.
When point-of-sale (POS) systems were first commercialized,
retailers were able to collect large amounts of potentially
valuable information, but most of that information remained
untapped. The emergence of social media and other
consumer-oriented technologies is now introducing even
more data to the retail ecosystem. Retailers must handle not
only the growing volume of information but also an
increasing variety—including both structured and
unstructured data. They must also find ways to accommodate
the changing nature of this data and the velocity at which is
being produced and collected.
If retailers succeed in addressing the challenges of “big data,”
they can use this data to generate valuable insights for
personalizing marketing and improving the effectiveness of
marketing campaigns, optimizing assortment and merchandising
decisions, and removing inefficiencies in distribution and
operations. Adopting solutions designed to capitalize on this
big data allows companies to navigate the shifting retail
landscape and drive a positive transformation for the business.
Imagining the possibilities
How can solutions for big data help retailers? They can
improve the effectiveness of traditional retail processes by
generating new insights while creating new capabilities that
drive better business outcomes. For example:
• Personalized shopping experience: To help serve a customer
shopping for a new TV, a retailer could analyze data from
previous transactions, clickstreams, social media, geospatial
services and other sources to understand the customer’s
preferences and push a highly targeted, real-time promotion on
to the customer’s smartphone as he or she shops in a store.
Retailers can also examine broader customer search patterns,
preferences and purchases to generate meaningful and
interesting offers and suggest complementary products to
provide greater value to the customer while boosting revenues.
• Optimized merchandising: A retailer could better determine
which products will sell best through each retail channel, at
each store location and at what price. For example, a retailer
could analyze fast-changing social media buzz about an
upcoming superhero movie to gauge demand for particular
action figures across multiple geographic locations. With
insights into which specific product will sell best in each
location, the retailer can ensure that stores in each area are
well stocked with those products when the movie is released.
Real-time competitive price comparisons can help the retailer
set pricing or launch promotions that attract consumers away
from rival retailers.
3. Retail 3
• Operational excellence: Analyzing communications, traffic
patterns, weather data, political news and consumer demand
signals could help a retailer manage retail distribution
networks in real time to ensure timely delivery of products
and achieve high-quality operational performance.
Creating a personalized shopping experience
Effectively analyzing the large volume and variety of
customer data opens new opportunities to gain a deeper,
more complete understanding of each customer and create a
smarter shopping experience.
What if you could:
• Increase the precision of customer segmentation by analyzing
customer transactions and shopping behavior patterns across
all retail channels?
• Enrich your understanding of customers by integrating
multichannel data—from online transactions to social media
and third-party data—to develop a 360-degree view of each
individual and identify emerging trends?
• Optimize customer interactions by knowing where a customer
is and delivering relevant real-time offers based on that location?
• Predict consumer shopping behavior and offer relevant,
enticing products to influence customers to expand their
shopping list?
Marketing teams can use solutions for big data to collect and
analyze customer information from a wider range of sources
than before—including POS systems, online transactions, social
media, loyalty programs, call center records and more. That
information deepens their understanding of customer
preferences, helps them more accurately identify shopping
patterns and enables them to generate more precise customer
segmentation. Marketers can then use new insights to deliver
highly targeted, location-based promotions, in real time.
Email
Text analysis
for pattern
identification
Customer
Demographics,
transactions
and shopping
patterns
Drive marketing optimization
Data
• Customer micro-segmentation
and full 360-degree view
• Additional value and insight
from sentiment analysis
• More accurate satisfaction scoring
• Demographics, transactions
and shopping patterns
• Timely delivery of offers
to customers
Call center
Text and audio
call records
Video
Surveillance,
foot traffic
in store
POS
Transaction
logs
Geospatial
Where is the
customer?
Outcomes
• Reduce marketing cost
• Reduce churn
• Increase visits and
conversion
• Increase customer loyalty
Social media
Customer sentiment
Events
Weather,
local events
Clickstream
Online
activities
The result? Customers gain a richer, more personalized shopping
experience with promotions and offers that are more likely to
appeal to them. Retailers, meanwhile, are able to retain a
competitive edge and boost revenues by maximizing cross- and
up-sell opportunities, as well as consistently engaging customers
across channels and reinforcing their brands at every turn.
Figure 1. Retailers can draw on a wide variety of data—from transaction and
clickstream data to social media and geospatial information—to enhance the
effectiveness of marketing efforts and deliver real-time promotions.
4. 4 Capitalizing on the power of big data for retail
Optimizing merchandising and supply chains
Implementing a scalable big data platform can also help retailers
build smarter supply chains and optimize merchandising across a
multi-channel retail operation.
What if you could:
• Predict optimal pricing and maintain a price leadership
position by analyzing price and demand elasticity?
• Select the right merchandise for each channel and fine-tune
local assortment planning by drawing on insights from social
media, market reports, internal sales data and customer
buying patterns?
• Optimize inventory across multiple channels by using leading
indicators such as customer sentiment and promotional buzz
to anticipate future demand?
• Fine-tune store planograms by analyzing customer buying
patterns and purchasing trends?
• Improve logistics by using real-time traffic, weather data and
more to re-route shipments and avoid costly delays?
Today many retailers monitor average prices by competitors on
a weekly basis. With solutions for big data, they can conduct
instant, real-time price comparisons of top competitors, tracking
hourly price changes and synchronizing those changes with
demand trends. Retailers can then use new insights to set their
own pricing, initiate discounts and implement competitive
real-time promotions to avoid losing sales—and gain agility.
Figure 2. With better knowledge of competitive pricing and demand trends,
retailers can initiate sales and promotions that help avoid losing business.
Customer
Demographics,
transactions
and shopping
patterns
Data
• Ability to price by channel,
region, time of day
• Ability to move from store
cluster assortments to
individual store assortments
• Integrated execution knowing
customer’s preferred price point,
profit targets, supply and
timely offer delivery
Product
Availability,
location, margins
POS
Transaction
logs
Geospatial
Where is the
customer?
Outcomes
• Increased revenue and
margins
• Improved marketing ROI
• Fewer stock-out situations
and markdowns
• Optimized inventory
• Increased customer
satisfaction
Social media
Customer sentiment
on pricing and demand
Competitors
Product
availability,
hourly price
changes
Events
Weather,
local events
Execute dynamic pricing and create
localized assortments
5. Retail 5
Enabling operational excellence
In addition to improving marketing and merchandising efforts,
solutions for big data can help retailers realize a variety of
operational goals, from improving labor utilization to
enhancing financial management.
What if you could:
• Optimize staffing levels by predicting changes in customer
demand?
• Better match employee skills with retail store needs and create
the right incentives to drive strong sales performance?
• Facilitate better-informed financial decision making by
drawing on complete, trustworthy and timely data from a
wide array of sources?
• Improve fraud detection by analyzing large volumes of
transactions?
A flexible, comprehensive big data platform can play a key role
in improving labor utilization and performance. Many large
retailers rely on historical data to schedule their thousands of
associates and assign those associates to the thousands or
millions of tasks involved in providing a positive shopping
experience. With solutions for big data, retailers draw on
insights from price optimization, assortment planning and
marketing to improve labor scheduling. They can incorporate
employee performance analysis to optimize work assignments
according to skill sets and manage incentives.
Discovering the value of implementing
big data solutions
Leading retailers are already discovering the tremendous value
of implementing solutions designed to analyze, organize and
apply big data.
Delivering a richer multichannel retail experience
with new customer intelligence
Bass Pro Shops—a leading retailer in fishing, hunting, camping
and other recreational activities—capitalized on solutions for
big data to create a richer multichannel retail experience. The
company needed ways to increase retail shopping consistency
across a full range of channels, including its retail store, boat
dealership, Internet, catalog, wholesale, restaurant and resort
channels. The existing enterprise data warehouse could not
provide detailed analytics on individual customers or purchases
across multiple channels.
The company selected an IBM® Customer Intelligence
Appliance, which provides a single view of each customer plus
the capabilities for business intelligence and analytic reporting
on customer behavior. The solution can generate reports in
less than 10 seconds.
Bass Pro Shops can now increase customer satisfaction and
improve loyalty by providing a consistent experience no matter
how customers choose to shop. New customer insights enable
the organization to tailor offers and fine-tune each of the
customer channels to maximize the appeal of products and
drive more sales.
6. 6 Capitalizing on the power of big data for retail
Enhancing analytics to improve merchandising
decision making
A large discount apparel and home fashion company
capitalized on the potential of big data to optimize
merchandising. The retailer needs timely insights on consumer
demand and changing product prices over the course of a
clothing season to purchase the right inventory for its stores.
Unfortunately, the company’s existing analytics solution
required an entire weekend to generate results, leading to
missed supply chain and merchandising opportunities.
The company implemented an IBM Customer Intelligence
Appliance and deployed analytics capabilities to deliver key
insights rapidly to buyers. Because the solution was a pre-
integrated appliance, it was up and running in just weeks,
without requiring excessive IT services.
The solution’s performance enables the company to run queries
20 times faster than before, producing results to some queries in
just seconds. Now 500 employees across the company use the
analytics capabilities to quickly identify new opportunities and
make key merchandising and supply chain decisions.
Expanding customer analytics to optimize marketing,
merchandising and operations
For a global electronics retailer, solutions for big data helped
expand its customer analytics efforts. The company needed to
replace its 13-year-old CRM system, which offered only a
store-centric view of customer patterns, required more than six
weeks to build new models and generated reports too slowly to
keep up with business demands. The retailer needed a solution
that could analyze customer information across a widening
array of customer data, including social media posts and
clickstreams. The goal was to improve customer satisfaction
and loyalty, allow marketers to create personalized offers,
enable merchandisers to optimize assortment and pricing, and
help managers to optimize the placement of in-store displays.
The retailer replaced its existing CRM system with a new
solution that combines an IBM Customer Intelligence
Appliance with SAP software for analytics and reporting. The
company now has a single view of each customer across
channels, plus analytics capabilities to build segmentation
models, score customers and run campaigns in hours.
Figure 3. The IBM Big Data Platform offers an array of integrated capabilities to
address the tremendous volume, variety and velocity of big data.
IBM Big Data Platform
Analytic applications
Applications and
development
Visualization
and discovery
Systems
management
Accelerators
Stream computingApache Hadoop
system
Data warehouse Data exploration
Information integration and governance
Cloud | Appliances | Mobile | Security
BI/Reporting Exploration/
Visualization
Functional
Application
Industry
Application
Predictive
Analytics
Content
Analytics
7. Retail 7
Marketing and merchandising teams can draw on that single
view of the customer to deliver more personalized offers and
loyalty rewards, fine-tune merchandising for customer
preferences and optimize the store layout. Predictive analytics
capabilities enable the retailer to anticipate the next customer
actions and improve interactions across channels and at each
step of the customer lifecycle.
Creating a data-driven retail enterprise
Offering a broad portfolio of solutions and capabilities, the
IBM Big Data Platform is helping retailers capitalize on the
vast potential for big data in retail. The platform-based
approach allows organizations to leverage their investments in
technologies and skills by allowing them to start with
capabilities for executing one particular use case and easily add
others using the same platform. Pre-integrated capabilities
help accelerate the time to value.
Leading retailers can adopt IBM InfoSphere® BigInsights™ to
collect, process, analyze and manage a large volume and variety
of customer data from multiple sources. They could analyze
everything from transactional data to unstructured social media
data, learning more about customer preferences and future
behaviors. Using IBM InfoSphere Data Explorer would enable
these retailers to rapidly search massive volumes of historical or
unstructured data.
By implementing IBM InfoSphere Streams, retailers can
continuously capture, analyze and cleanse data in motion to
facilitate real-time decision making. A marketing team could
gauge the success of a campaign by analyzing trending topics in
social media. Merchandisers could analyze customer calls,
e-mails and social media posts to assess rapidly changing
demand for particular products by location.
Using the IBM Customer Intelligence Appliance, retailers can
integrate information from multiple retail channels and
customer touch points to build a complete view of each
customer. The more complete data set also enables retailers to
produce more accurate models. Employing predictive analytics
could help better anticipate future behaviors and optimize
customer interactions.
Keeping retail focused on the customer
The multiplication of retail channels is empowering consumers,
providing them with access to more information and new ways
to research, compare, purchase and provide feedback on
products. For retailers, the customer data produced through
these multichannel interactions presents valuable opportunities
to optimize marketing, merchandising and operations.
The IBM Big Data Platform offers a comprehensive array of
capabilities for addressing the growing volume, variety and
velocity of available customer data. Whether they are enabling
one, two or multiple retail processes by analyzing big data,
retailers can implement IBM solutions that help protect existing
investments and allow retailers to scale as needed. With IBM
solutions for big data in place, retailers can build a foundation
that supports a customer-centered, data-driven enterprise that
helps them sustain a competitive edge.
For more information
To learn more about how IBM solutions help you capitalize on
big data, visit:
• ibm.com/bigdata
• ibm.com/smarterplanet/us/en/consumer_advocacy/ideas