Marketing, Consumers and The Rise of Big Data Analytics

Copyright © 2013, SAS Institute Inc. All rights reserved.
MARKETING, CONSUMERS AND
THE RISE OF BIG DATA ANALYTICS
PREPARED & PRESENTED BY
LOUIS M FERNANDES, DIPM, MCIM, CHARTERED MARKETER
DIRECTOR, MARKET DEVELOPMENT, SAS UK
PRESENTATION DATE: 12 AUGUST 2013

TODAY’S TALK AGENDA
• Defining “Marketing”?
• “Above”, “Below”, “Inbound” and “Outbound”
• What is Big Data?
• What is Analytics?
• Marketing Themes & The Consumer
• Customer Relationship Management
• Content is King
• Context trumps Content
• The goal: Joined-up Customer Experience
• Tomorrow’s World, Today
• The Internet of Things

1976
>13,00098%>45,000Partner
Growth$3bn24%
Privately owned
since formation
Employees
worldwide
Global 2000
companies use
SAS
Sites deployed
globally
Long-term
customer
relations
Revenue
invested in R&D
Worldwide
revenue
Year-on-year
since formation

Providing the right product,
at the right price,
in the right place,
at the right time,
to the right person,
using the right communication,
for the right return.

Products Channels Consumers

When the volume, velocity and
variety of data exceeds an
organisation’s storage or compute
capacity for accurate and timely
decision-making

Copyright © 2013, SAS Institute Inc. All rights reserved. Copyright © 2012, SAS Institute Inc. All rights reserved.
FORECASTING
DATA MINING
TEXT ANALYTICS
OPTIMISATION
STATISTICS
Finding treasures in unstructured data
like social media or survey tools
that could uncover insights
about consumer sentiment
Mine transaction databases
for data of spending patterns
that indicate a stolen card
Leveraging historical data
to drive better insight into
decision-making
for the future
Analyse massive
amounts of data in
order to accurately
identify areas likely to
produce the most
profitable results
BUSINESS
INTELLIGENCE

“You’re at a party with 22 other people, what are the odds
that two people in the room will share a birthday?”
Remember there are 365 days in a year….

“Better than 50:50”

 





Brighton
Hove
Portslade-by-Sea
Rottingdean
Shoreham-by-Sea
Southwick
Falmer
Fulking
Moulsecoomb
Stanmer
Income £30-39,000
Income £0-9,999

 





Brighton
Hove
Portslade-by-Sea
Rottingdean
Shoreham-by-Sea
Southwick
Falmer
Fulking
Moulsecoomb
Stanmer
The Sun Readers
The Telegraph Readers

Reactive Analysis
Fail & Fix
Proactive Analysis
Predict & Prevent

YOUR
COMPETITIVE
ADVANTAGE
Orient
Observe
Act
Act
Orient
Decide
MARKET
OPPORTUNITY
Decide
BUSINESS IMPACT

Strategic
Impact
Across Consumers Across Channels Across Actions Across Products
Enabling Capabilities Around People, Process, and Infrastructure
Return on Consumer Investment
Maximising Customer Lifetime Value
Level 1
Strategic Segment
Management
Level 2
Lifecycle
optimisation
Level 3
Multi-Channel
Optimization
Consumer
Value
Time
Acquisition Strategies Growth and Retention Strategies Attrition Strategies
Strategic
Impact
Y 2Y 1
Y 0
Y 2 Y 2
Nursery Strategies
Lengthen and Deepen
Consumer Value
Intelligently Prospect
to Minimise CPA
Identify and Address
Potential Attriters

Strategic
Impact
Across Consumers Across Channels Across Actions Across Products
Enabling Capabilities Around People, Process, and Infrastructure
Return on Consumer Investment
Maximising Customer Lifetime Value
Level 1
Strategic Segment
Management
Level 2
Lifecycle
optimisation
Level 3
Multi-Channel
Optimization
Level 4
Single Value Proposition
Consumer
Value
Time
Acquisition Strategies Growth and Retention Strategies Attrition Strategies
Strategic
Impact
Y 2Y 1
Y 0
Y 2 Y 2
Nursery Strategies
Lengthen and Deepen
Consumer Value
Intelligently Prospect
to Minimise CPA
Identify and Address
Potential Attriters

+
=
( )

Fresh insights from customer data allowed Tesco to meet consumers'
needs faster and more accurately, growing market capitalisation 10-fold
in eight years while its chief competitors' market value fell.
Sir Terry Leahy

Big Data Analytics
+Multi-channel CRM
+ Content
+ Context
= Customer Experience

61

62

63

Company
Unit/Channel
Manager
Business Unit/
Communication Channel Customer
Email & Direct
Mobile & Digital
Web Personalisation
Point of Sale/Service
Social
LEGACY DATA
(e.g. Purchase History,
POS, etc)

CUSTOMER
EXPERIENCE
PLANNING
QUESTIONS
1. Who are my customers?
2. What do they “look” like?
3. What customer needs am I
satisfying?
4. What is the market
opportunity?
QUESTIONS
1. How does my value
proposition relate to my
various customers?
2. What aspects of its utility/
service will they value?
3. How should I position it?
4. How should I engage with
my prospects and
customers?
CUSTOMER
STRATEGY
QUESTIONS
1. How do I find new
customers?
2. What are the best
channels to reach them
through?
3. How do I execute
campagins?
4. How do I optimise
campaigns?
CUSTOMER
EXPERIENCE&
ENGAGEMENT
DESIGN
QUESTIONS
1. How do I interact with my
customers?
2. How do I ensure
consistency across
interaction channels?
3. How do I optimise the
customer experience?
4. How do my customers
engage with me?
CUSTOMER
INTERACTION&
EXPERIENCE
QUESTIONS
1. Who has interacted with
my campaigns?
2. What have they done?
3. How much have I sold?
4. How much will I sell
tomorrow?
MARKETING
MEASUREMENT
&ANALYSIS
SINGLE CUSTOMER VIEW

Email & Direct
Mobile & Digital
Web Personalisation
Point of Sale/Service
Social
SCV
Business rules
Reporting /
Analytics
The “Closed loop”
Modelling“Sandpit”
Content Distribution
Dataclean,merge&append

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Marketing, Consumers and The Rise of Big Data Analytics

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