The Shape of Things to Come
Martin Block
Integrated Marketing Communications
Northwestern University
CADMEF/Chicago
May 14, 2004
Contemporary Marketing World
• Data tsunami: POS, loyalty programs, accessible sales
data, and customer databases
• Management demands for accountability: Six Sigma,
Balanced Scorecard and ROI
• Measurement issue has shifted to senior management
and CFO from marketing department (major change over
the past few years)
• Debate has shifted from the value of real sales data to
the value of customer data
• Questions continue about the value of traditional media
measures
Measuring Financial Returns
Fundamental Integrated Marketing
Communication
Estimating the Baseline
Units
Store Level Data
18
16
14
12
10
8
6
4
2
0
Promotion A
Promotion B
Baseline
1
2
3
4
5
6
7
Weeks
8
9
10
11
12
13
Constructing Marketing Strategy
Base Volume up
Incremental
Volume Up
Incremental
Volume Down
Sustain
Trade Promotion
Building Program
Base Volume Down
Franchise
Building Program
Major Overhaul
Kinked Demand Curve
Total RTE per Pound
• Direction of curve changes at the kink
• Volume does not continue to increase as price decreases
• Lowering price below the kink means lost revenue
350000
300000
250000
Lost
Revenue
Kink
200000
150000
100000
Below
$3.25/lbs
50000
0
2.00
2.25
2.50
2.75
3.00
3.25
3.50
3.75
4.00
4.25
4.50
4.75
5.00
5.25
5.50
5.75
6.00
6.25
6.50
6.75
7.00
7.50
Price Promotion Response Model
Store Level Data
550
500
450
Sales Volume
400
350
300
Average Discount
TPR
15%
Feature
19%
Display
10%
Both
24%
250
200
150
100
5
10
15
20
25
30
35
Percent Price Discount
TPR
Feature
Display
Both
40
45
RTE Household Purchases
• Category very skewed to heavy users (15% of customers buy 40%
of the volume)
• RTE Usage: One time buyers (1 purchase in 6 weeks), light buyers
(2 purchases), regular buyers (3 and 4 purchases), heavy buyers (5
or more purchases)
300000
250000
Households
200000
Heavy Users
Top 15%
150000
100000
50000
0
1
2
3
4
5
6
7
8
9
10
11
Number of Items in 6 weeks
12
13
14
15
16
Distribution of RTE Usage
Percent
Volume
Percent
Customers
Ratio
One Time
13.1
36.1
36.3
Light Buyers
19.7
27.1
72.7
Regular Buyers
26.7
21.5
124.0
Heavy Buyers
40.4
15.2
266.3
RTE Usage by Household Characteristics
•
•
•
RTE usage highest among households with 4 to 10 and 11 to 17 aged
members.
Heavy buyers have larger households.
Regular and heavy buyers spend more on RTE, spend more at the chain,
and shop at more different chain stores (8.6% of heavy buyers shop at 2 or
more).
HH
Size
Income
One Time
3.6
54.8
Light Buyer
3.8
54.7
Regular Buyer
3.9
Heavy Buyer
Total Market
Shop 2+
Stores
RTE $
Total $
3.54
60.12
2.5
6.97
86.05
55.8
6.6
11.88
144.10
4.3
57.5
8.6
25.31
270.57
3.8
55.4
3.4
9.57
117.19
Basic R-O-C-I Process
Loyal
Users
Switchers
Price
Buyers
1 Present Income Flow in Category
$
$
$
2 Share of Requirements
%
%
%
3 Customer Income Flow to Brand
$
$
$
4 Contribution Margin %
%
%
%
5 Contribution Margin $
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
12 Difference in Contribution Margins With
and Without Brand Communication
$
$
$
13 Incremental Gain or Loss
$
$
$
14 Return On Investment
%
%
%
6 Income Flow Without A Brand
Communication Program
7 Contribution Margin Without A
Brand Communication Program
8 Income Flow With A Brand
Communication Program
9 Gross Contribution Margin With A
Brand Communication Program
10 Brand Communication Investment
11 Net Contribution Margin
Measuring Financial Returns
• Basic ROCI Process is fundamental to
IMC
• Must be based on real data
• Must be strategic—Marketing
communication activity must be related to
short and long term changes in base and
incremental sales
Rise of the Retailer
Tesco Story and Loyalty Programs
History of Loyalty Programs
• Loyalty Programs started in the 1950’s
• Sperry and Hutchinson Co. developed the first program known as the
Green Stamp
• Attracted customers to the store and inspired purchases and lost
effectiveness due to “excessive” use
• Point-of-sale data combined with the frequent shopper card the
contemporary method.
– Use of loyalty programs and frequent shopper cards may becoming
excessive.
– Retailers and manufacturers must find a unique use of the loyalty
program and collected data to be distinguished from their
competitors.
– Question of how the collected data should be used
Loyalty Program Customer Statistics
• 80 percent of the retail profit comes from 20 percent of the
retailer’s customers
• Top customers generally buy higher-priced items
• Bottom 20 percent tend to purchase items on discount only and
contributed little to the stores profit
• Average number of Loyalty Cards held by one customer is 3.2
• Only 20 percent of the U.S. population shop exclusively at one
store and over 50 percent shop at two stores
The Tesco Success
• Tesco share exceeded
Sainsbury share after
Clubcard launch
• Turnover up 52% since
the launch of Clubcard
in 1995.
• Floor space up only
15%
Clubcard launched
Food retailers’ market share in Britain
Tesco
Sainsbury’s
Asda
Tesco
Safeway
Source: IGD
© Copyright,dunnhumby 2002
Feb 1995
2000
Each customer has a unique “dna profile”
derived from the products they buy – “you
are what you eat”
© Copyright,dunnhumby 2003
Product DNA Typing:
Each product is assigned “important to customer” attributes
Value Oven Chips,
2.7 kg
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Big Box (+) / Small Box (-)
Healthy
Prepacked (+) / Loose (-)
Fresh (+) / Longlife (-)
Convenience
Cooking from Scratch
Branded (+)/Tesco Own Label (-)
Kids
Value
Finest
Foreign
Green
High (+)/ Low (-) Price
Vegetarian
Meat
Adventurous
Traditional
Low Calorie (+) / High Calorie (-)
© Copyright,dunnhumby 2002
1
0
0
-1
0
0
-1
0
1
0
0
0
-1
0
0
0
0
-1
We work with Tesco in many areas
Database
management
Personal
Relationships
Media Effectiveness
Pricing
Strategy
Format
Development
Customer Insight
Shopping
Analysis
Better Ranging
© Copyright,dunnhumby 2002
... making data make sense ...
Local Store Research
Customer
Acquisition
Targeted Communication
The Magnificent Seven
•Our image of customers is built from seven pieces
Lifestage
Application form, what
they buy
Basket
Typology
Vegetarian, organic,You
are what you eat!
Profitability
Primary Channel
Brand choice, packaging preference, weight ofPreferred format (Supermarket, Express, On-line,
purchase
Petrol)
Promotional Promiscuity
Cherry picking deals, bulk buying to larder fill
Brand Advocacy
Participation in extensions (Tesco.com, Baby Club, Wine
club)
Shopping
Habits
Share of shopping,
Recency & frequency
•This is how our customers behave.
•How do they see the products we want them to buy?
© Copyright,dunnhumby 2002
Tesco communicates very smartly
•Local store information
•Clubcard Statement
•Clubcard Magazine
•Recipe Magazine
•Bespoke mailings
•Baby Club
•Tesco.com
•Clubcard deals
– targeted and mailed frequently
– targeted and mailed quarterly
– targeted and mailed quarterly
– targeted and retailed monthly
– targeted and mailed ad hoc
– targeted and mailed quarterly
– targeted via the web
- targeted via the magazine
© Copyright,dunnhumby 2002
The Looming Retailer Battle
• Retailer power will continue to expand
• Some retailers will become their own
media message delivery vehicles
• The retail war will be between the “WalMart” logistical model and the “Tesco”
customer data model
Marketing Mix Models
Managing Marketing
Communication
TRENDS IN CPG MARKETING MIX
(As Percent of Sales)
23%
Total
Marketing
Spend
11%
Trade
Promotion
•
•
•
15%
5%
6%
Consumer
Promotion
6%
6%
Advertising/
Media
1978
2000
4%
Source:
Donnelly Marketing; Accenture; Zipatoni, via Promo, March 01; IBM
Strategy & Change analysis
•
•
•
•
•
Pressure for sales growth
Explosion of scanner-based knowledge
regarding price/promo lift
Advertising impacts generally are not
visible in syndicated scanner data
Money follows knowledge/information
Trade’s role in the mix has increased
dramatically over time
The “power of brands” has eroded
To increase its share of budget, and revitalize brand equity, marketing
communication decision making
processes must leverage the data
The Marketing Mix Modeling is
born
The CPG Industry Solution
Shift marketing dollars toward mix elements and tactics
that generate the strongest ROI
The Problem
"The pressure is on in most organizations because the chief financial officer
is asking 'What are we getting for what we're spending’? How do I improve
the return on investment?”
Don Schultz
Professor of Integrated Marketing - Northwestern University
Generate
Volume Growth
Yield:
VolumeDriven
Profit Growth
Hold Marketing Spending Flat
The CPG Industry Solution
Shift marketing dollars toward mix elements and tactics
that generate the strongest ROI
Marketing Mix Model
Historical
Sales Data
Statistical Modeling
 Deseasonalizing
 Baselining
 Bump Analyses
Marcom
Spending
Assumptions and
Theories
ROI
Ten Year Financial Model
Annual Sales Revenue by Year
Short Term versus Long Term
Predictive Year
Short-term
1
2
3
Brand Equity
4
5
6
7
8
9
10
Growing Importance of Marketing
Mix Models
• Assembling sufficient disaggregate
historical data still a challenge for most
organizations
• Determining synergistic effects and the
value of IMC programs the analytical
challenge
• Importance of measuring long-term brand
value as part of the model
Time Budgets
Tracking Media and Entertainment
Average U.S. Time Budget in 1972
Minutes per Day
Minutes
1. Main Job
225
Minutes
17. Study--Clubs
28
18. Television
92
2. Second Job
5
3. Work--Other
12
19. Radio
4. Travel to Job
25
20. Newspapers
5. Marketing
14
21. Magazines
6
6. Shopping Errands
18
22. Books
5
7. Cooking
44
23. Movies
3
8. Home Chores
58
24. Social Activity
63
9. Laundry
26
25. Conversation
18
3
26. Active Sports
6
10. Pets and Garden
4
24
11. Other House
24
27. Outdoors
2
12. Child Care
33
28. Entertainment
5
13. Personal Travel
31
29. Cultural Events
1
14. Leisure Travel
19
30. Resting--Naps
19
15. Eating
81
31. Other Leisure
20
16. Personal Care
69
Sleep
459
Time Spent with Media
Hours per Week
25
Radio
Broadcast TV
20
Cable and
Satellite TV
Recorded
Music
15
Daily
Newspaper
Projection
Magazines
Books
10
Home Video
Video Games
5
Internet
0
1997
Source: Veronis Suhler Stevenson
1998
1999
2000
2001
2002
2003
2004
2005
Shifting Media Consumption Patterns
Hours/Week
Annual
Growth
Projected
Growth
2002
1997-2002
2002-2007
Radio
19.1
1.1
2.0
Cable and Satellite TV
17.6
8.0
2.3
Broadcast TV
15.1
-2.2
-0.7
Recorded Music
3.9
-5.3
-5.5
Daily Newspaper
3.4
-1.1
-0.9
Internet
3.0
43.1
7.1
Magazines
2.4
-1.6
-1.0
Books
2.1
-1.3
-0.2
Video Games
1.3
14.2
10.4
Home Video
1.1
3.7
11.1
Source: Veronis Suhler Stevenson
The Changing Media Entertainment
Environment
• Media is question of time allocation for the
consumer who can increasingly negotiate with
the provider
• Entertainment is the key to attracting and
holding audience attention
• Coming media technologies will accelerate the
change
• Media is increasingly consumed simultaneously
and should be used with this in mind
Demographic Shifts
18 to 34 Myth
Demographic Targeting
18 to 34
Growth by age of population
•
For the projectable future, the share of population
under the age of five and between five and
seventeen will never be higher than it is today.
•
Growth in population over sixty-five will remain
slow for the next decade and then increase, from
13% of the population to around 20% in 2030.
•
Eighty-five plus is most rapidly growing segment,
doubling by 2025 and increasing by fivefold by
2050.
•
The median population age is older now than it
ever has been (35.7 in 2000) and will continue to
advance through 2050.
18 to 34 Target ?
•
CPM on Network TV
– $23.50 for 18 to 34
– $9.50 for 35+
•
People aged 50+
–
–
–
–
–
•
•
•
•
•
account for half of all discretionary spending
watch more television (than young people)
go to more movies
buy more CDs
YET are the focus of less than 10% of advertising
In 1940, 6.8% were 65+, in 2000 12.4% were 65+
Real income with head under 30 fell 16% between 1973 and 1990
3 out of 4 men between 18 and 24 were still living at home in 1990 (largest
proportion since the depression)
Only 1 in 5 of “youth-oriented” Honda Civics are sold to those under 26
Brand loyalty of female household heads (Nielsen study)
– 67% 18 to 34 are willing to change brands
– 70% aged 35 to 64
Deciles
10
Customer groups
defined by
incorporating
frequency of
purchase with
spending—REAL
BEHAVIOR!
Frequency
10
9
8
7
6
5
Gold
9
S
p
e
n
d
i
n
g
8
Silver
7
Bronze
6
5
4
3
2
1
Tin
4
3
2
T
a
r
n
i
s
h
e
d
1
In one retailer, 19% of shoppers are classified as
Gold, 20% as Silver, and 21% as Bronze
Shoppers
25%
20%
15%
10%
5%
0%
Gold
Silver
Bronze
Tarnish
Tin
These 19% of Gold customers account for
nearly 70% of total sales
Total Sales Dollars
80%
70%
60%
50%
40%
30%
20%
10%
0%
Gold
Silver
Bronze
Tarnish
Tin
New Marketing Thinking
• Markets must be defined in terms of real
behavior to show financial return
• The youth myth and mass demographic
marketing need to be left in the past
Thank you!