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www.stirlingretail.com
Big Data and Retail
Professor Leigh Sparks,
Institute for Retail Studies,
University of Stirling
www.stirlingretail.com
Structure
• What do retailers do?
• How is this changing?
• “Big Data”
• What are the retailer
problems?
• Beyond retail problems
www.stirlingretail.com
What do retailers do?
• Sell stuff (often single item) to
the final consumer
• Mainly through the notion of the
shop
• The shop is not a static concept
• Retailers are consumer not
production oriented
• How do we get consumers to
keep patronising our business
over other businesses?
www.stirlingretail.com
How is this Changing?
• Retail is Big Business
– WalMart, $482 bn sales
(2015)
– 7-eleven, 57K stores
worldwide
– Inditex, 6.8K stores in
c90 countries
– Tesco, 3.5K stores in the
UK
– Amazon, $89bn
ecommerce sales (2014)
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www.stirlingretail.com
How is this Changing?
• Retail is omni-channel
business
– Amazon
– Asos – now global brand
– Tesco, £5bn e-commerce
business
– Retail sales now 14%
online, predictions are
20% by 2020
www.stirlingretail.com
How is this Changing?
• Consumers in control
– Multi-channel, multi-
access
– Always on and social
media
– More volatile and less
loyal
– Discerning and
questioning
– Patterns of behaviour
have changed
www.stirlingretail.com
Marks and Spencer
• Retail Week Consumer
Experience Conference,
October 2014
– 100m store visits to M&S
per week; 250m website
visits per week
– 52% of women’s clothing
searches done on a
mobile device
www.stirlingretail.com
How is this Changing?
• Differences
– Types of data
– Patterns
– Tracks
– Views
– Interactions (P2P)
– Capabilities
• Volume, Velocity and
Variety
• Data “in motion”/”at rest”
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www.stirlingretail.com
Big Data as Panacea?
• Retailers always sought
information and data
• But not all have
understood why they
need this …
• … or now the range of
data that might be
available or needed
• Data as a cost not an
investment
www.stirlingretail.com
What are the Retailers Problems?
• What
– Prices
– Promotions
– Locations
• In what
– Context(s)
– Channel(s)
• Addressed to what
segment or target or
individual
www.stirlingretail.com
What Retailers Most Need
• Predictive consumption
• Effectiveness of
promotions
• Target pricing precisely
• Understanding the
value of the network
• In store customer
activity
www.stirlingretail.com
So Where does Big Data fit in?
• Increased speed and agility
– Using predictive analysis
– Supporting faster decisions
– Real time marketing
• Projects
– Optimizing delivery of
messages to shoppers
– Mining for shopper insights
– Demand and assortment
planning
• Personalization/more
shopper solutions
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www.stirlingretail.com
Big Data Issues
• Sources
– Social media
– Website
– Item level sales
– Transaction data
(personalised)
– Mobile devices
www.stirlingretail.com
Big Data Issues
• Why?
– Dialogue (or
communication)
– Rapid reaction launches
– Effect measurement
– Performance – “store”,
supply chain, inventory
www.stirlingretail.com
Big Data Big Issue
• Privacy
• Acceptability
• Brand and trust
implications and
consequences?
www.stirlingretail.com
Big Problem? Personalisation
• Personalisation is a goal
• But is it acceptable – or
more accurately when is
it acceptable?
• When is personalisation
too personal?
• The “Uncanny Valley”
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www.stirlingretail.com
Are We Upside Down?
• Retailer focus is only one
side of the story
• Consumers have changed
also
• Sugar: we discuss “old style”
remedies alone – info and
tax
• Make consumer lives easier
• How do consumers achieve
goals?www.stirlingretail.com
EPSRC Neo-Demographics Project
www.stirlingretail.com
EPSRC Neo-Demographics Project
• Aims
– Address systemic failure
of UK industry in
entering emerging
markets
• Identify, acquire and
analyse behavioural data
• Surrogate market
intelligence and novel
data mash-ups
• New business models
• Outputs
– Integrate big data streams
in a privacy preserving
fashion
– Apply novel algorithmic
approaches to behavioural
information fabric
– Use covariate and crowd
sourced data to test
computational behavioural
groups
www.stirlingretail.com
Whose Data is it Anyhow?
• Big Data Retail
• Engagements
• Loyalty cards
• From Cards to Apps
• Rewards, Nudges,
Reinforcement, Peer
Groups, Games etc etc
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www.stirlingretail.com
Beyond Retail
• Tesco Employees
• Pre-diabetes (so GP
records?)
• Purchase
records/loyalty points
• Nutritional content
labelling for every
product
www.stirlingretail.com
A Finnish Example
Source: Saarijarvi et al (2016) Unlocking the transformative potential of customer data in retailing. International Review of Retail, Distribution and Consumer Research
www.stirlingretail.com
Mi-Connex Perth
• Place Based Solutions
– Gift cards
– Till intercepts
– Independent retailers
• Place Questions
– Who, what, where
– Incentivise e.g. parking
• Retailer Questions
– Who, what, where
– Spend Uplifts
www.stirlingretail.com
ESRC Consumer Data Research
Centre
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www.stirlingretail.com
So…
• Retailers have data
• Context data becoming
available
• Linking/understanding/acti
on
• Solving retailer problems
• Beyond retailing – retailers
part of the solution and not
the problem
www.stirlingretail.com
Web: www.stirlingretail.com
Email: Leigh.sparks@stir.ac.uk
Telephone: 01786 467384
Twitter: sparks_stirling
Contact Points
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