Marketing Strategy.pptx

© Robert Palmatier 1
Marketing Strategy
Chapter 8
Marketing Principle #4
All Resources Are Limited  Managing
Resource Trade-Offs

Agenda
 Introduction
 Approaches for Managing Resource Trade-Offs
 Evolution of Approaches for Managing Resource Trade-Offs
 Anchoring – Adjusting Heuristics Attribution
 Attribution Approach
 Response Models
 Marketing Metrics
 Framework for Managing Resource Trade-Offs
 Inputs to the Managing the Resource Trade-Offs Framework
 Outputs of the Managing the Resource Trade-Offs Framework
 Process for Managing Resource Trade-Offs
 Example
 Takeaways
 Case
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All Resources Are Limited
 The final and perennial issue facing managers is that all resources are limited
and often interdependent
 Managing resources optimally is critical, because marketing resources provide the
primary action levers that firms can use to implement what they have learned from
the previous three Marketing Principles
 The previous 3 Mkt. Principles all involve tradeoffs inherent in making strategic
decisions (STP, AER, BOR) while also providing input for the 4th Mkt. Principle,
which determines the annual budget to specific marketing actions (plan, budgets,
and metrics)
 Specifically, we need to balance marketing resources across:
1. Customer segments: targeting & positioning (STP)
2. Lifecycle stages: acquisition, expansion, and retention (AER)
3. Customer equity and marketing mix elements: brand, offering, and
relationships (BOR, 7Ps)
4. Other: SCAs now and for future, product categories, R&D projects,
geographies, sales territories, etc.
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Exercise on Resource Tradeoffs
 Everyone take a few minutes to describe how your firm allocates the sales
and marketing/R&D budget $ across the following areas:
 Customers (individuals, segments, geographic)
_______________________________________
 Stages (acquisition, expansion, and retention)
_______________________________________
 Marketing mix (brand, offering, relationships, or 7Ps)
_______________________________________
 Does this results in any misallocations, describe?
_________________________________
 Why do these misallocations occur?
__________________________________
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Firms Often Make Poor Allocation Decisions
 How do these portfolios differ?
 Which is stronger?
 Why would this happen?
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Source of Needing to Change Resource
Tradeoffs
 Resource slack refers to the “potentially utilizable resources
a firm possesses that it could divert or redeploy to achieve
organizational goals”
 Changes in customers’ needs
 Changes in the lifecycle stage of a firm’s products
 Changes in the product market landscape, due to entries and
exits by competitors
 Changes in the effectiveness of marketing activities
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Example: Smith’s Snackfood Company (UK /
Australia)
 Smith’s Snackfood Company, is a British-Australian company producing
snack foods
 The company records all the inputs and outputs throughout a product’s
lifecycle from pre-far preparations, on-farm processes to post-farm
transportations
 The data showed that one of the significant trade-offs during the
packaging and processing stage for corn chips is between resource usage
and emission of greenhouse gases
 This assessment enables Smith’s Snackfood to make more informed
decisions on its resource allocations across the product lifecycle stage.
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Sources of Resource Trade-Offs
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Source Idea Examples
Limited resources
and resource slack
Firms have some given level of resource slack, or potentially
usable resources that can be diverted or redeployed to achieve
organizational goals. However, this slack must be shared among
many different marketing needs. Resource allocation therefore
needs to find ways to optimize the return on marketing
investments
Organic downturns like recessions
significantly contract demand for
goods and services, lowering a
firm’s sales and profits, and the firm’s
subsequent resource slack. Resource
allocations must adapt to these
changing conditions and the varying
amounts of resource slack.
Changes in
customers’ needs
Market segmentation provides a description of the industry
segments. A firm then moves from the overall market
landscape to the specific segment(s) of interest to the firm.
Yet, over time, the size and attractiveness of each of the
industry segments changes, which means that the number
of targeted segments may change, and a firm’s commitment
to segments will change.
In 2005, the hotel industry mostly
concentrated on luring business
travelers; today, it spends much more
on marketing to young couples. Young
couples are the fastest growing
demographic, and they seek innovative
and inexpensive hospitality solutions.
Changes in the
lifecycle stage of a
firm’s products
Firms try to balance their product portfolios to have
products in all lifecycle stages, to help offset resource
needs. Introductory stage products require larger resource
allocations to their launch, testing, and advertising to create
awareness. They require different allocations as they
enter the growth, maturity, and decline stages. Changes in
technology and the success or failure of new products also
alter any firm’s product portfolio constantly.
Xero software is in the process of
disrupting traditional bookkeeping and
accounting online offerings owned by
large Australian firms. The large banks
have had to reshuffle and introduce
products that will enable them to
maintain a healthy product portfolio
mix.

Sources of Resource Trade-Offs, Con’t.
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Source Idea Examples
Changes in the
product market
landscape, due to
the entry and exit
of competitors
When the firm moves into a reasonably advantageous
market position, competitors quickly make a countermove.
Such counterattacks have the potential to negate the impact
of the incumbent’s advantage, and often create jostling for
secondary demand – firms stealing market share from one
another rather than creating primary demand. Firms have
to constantly change their resource trade-off decisions
during competitive counterattacks. In some cases, resource
trade-offs have to be made in anticipation of new entrants.
Tylenol’s prices were slashed, its
advertising and sales force budgets
increased, thus attacking its competitor
drug Datril, damaging Datril’s entry
strategy and helping Tylenol’s longterm
performance.
Changes in the
effectiveness
of marketing
activities
Even if a firm is operating during a stable economic window,
with fixed consumer segments, homogeneous preferences
for products across different lifecycle stages, and no major
competitive entry, the effectiveness of marketing activities
change over time, such that the aggregated market
becomes less or more responsive to marketing efforts.
For example, sales cycles have lengthened due to more
relationship selling, product complexity, and informed and
demanding customers.
Mass media advertising effectiveness
has declined since the 1990s in the US,
Europe, and Asia.

All Resources Are Limited: A Fundamental
Assumption of Marketing Strategy
 The recognition that all resources are limited and that an effective
marketing strategy must manage ever-present resource trade-offs is the
fourth and final Marketing Principles (MP#4)
 The approaches for dealing with the three previous Marketing Principles
in many ways help create the MP#4
 All resources are constrained; even if a firm’s existing resource allocation
policies appear effective, rapid and often unexpected changes in the legal,
economic, technological, or innovation landscape demand constant
vigilance
 Firms thus need ways to identify misallocations and adjust spending
levels quickly, in response to each new situation
 A firm’s marketing strategy must account for resource trade-offs, or else
its ability to execute the initial three First Principles of marketing
strategy, and thus its overall marketing strategy, will suffer
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Need For Resource Tradeoffs Across First
Principles
1. Selecting the who and what to “sell” across all potential
customers in the market
 Approach: segment and target like customers (STP)
 Decision criteria & allocation process: Attractiveness and
competitive strength using GE matrix
 Improvements: Smaller segments and CLV
2. Selecting who and what to “do” across portfolio of your
existing customers
 Approach: segment across stages (AER)
 Decision criteria & allocation process: CLV of customer personas
 Improvements: Individual customer-level analysis, HMM for
dynamic segmentation
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Need For Resource Tradeoffs Across First
Principles (con’t)
3. Deciding how to use brand, offering, and relationships to
achieve positioning objectives from STP and AER
 Approach: customer equity stack (BOR)
 Decision criteria & allocation process (within domain): elasticities,
partworth utilities, and CLV from choice models, conjoint analysis, experiments,
and regression
 Improvements: Multivariate (simultaneous) models
4. Determining annual budgets, plans, and metrics to execute
BOR marketing strategies and support positionings
 Approach: act, measure metric, evaluate, adjust (iterative)
 Decision criteria & allocation process: MROI, CLV, elasticities and partworth
utilities using choice models, conjoint analysis, response models, and Solver
 Improvements: More refined metrics and more inclusive
response/optimization models (variables and time)
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Agenda
 Introduction
 Response Models
 Metrics
 Example
 Takeaways
 Case
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1
Trends that Have Changed How Marketers Allocate Resources
Information Available for Evaluating Resource Trade-Offs
Heuristic Era Data Era
Information Technology
Infrastructures
Poorly developed Well developed
(a) Heuristic Era: Anchoring and Adjusting Approach
Very little hard data Detailed data on individual
consumers over time
Anchoring
Marketing
Resources
Advertising, sales
force, etc.
Marketing
Outcomes
Market share,
sales, customer
loyalty, etc.
(Not evaluated
by managers)
(Feedback from past outcomes)
Adjusting
(b) Data Era: Attribution Approach
Marketing
Resources
Advertising, sales
force, etc.
Marketing
Outcomes
Market share,
sales, customer
loyalty, etc.
(Feedback from past outcomes)
Attribution
Model
Experiments,
response models,
etc.
Volume of Data
Mostly qualitative and ad hoc data Longitudinal, customer-level data over
time
Customer Sophistication
Uninformed customers Highly informed customers
Proof of Marketing Effectiveness
Trust in marketing effectiveness High demands of mathematical proof of
effectiveness
Globalization
Local markets Highly competitive, global markets
Adjusting
Evolution of Approaches for Managing Resource
Trade-Offs
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Evolution of Approaches for Managing
Resource Trade-Offs
 The evolution of approaches for managing resource allocation suggests
two main and overlapping eras
 Heuristics Era – firms constantly decide how to allocate resources
across different customer segments, different customer stages, different
offerings, different regions, and different marketing communication
formats
 No hard data about resource allocation options
 Managers used simple rules of thumb for allocating resources
 Data Era – firms started using historical data that revealed the link
between their past resource trade-off decisions and outcomes, such that
they could determine the actual effects of certain resources on specific
outcomes
 Scientific approaches, based on data and empirical models, reveal whether firm
should continue its level of resource commitments or adjust them
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Example: Optimal Strategy for
Advertisements (China)
 To discern whether and when to target consumers with mobile
advertising, a large Chinese mobile phone provider conducted a large-
scale study in which it sent 4,400 mobile users a promotional text
between 8 am and 8 pm
 The consumers responded directly to the offer, paying using their phones
 With the resulting information about when and how consumers
responded to the advertisements, the firm was able to determine its
optimal strategy, which was to target customers between 10 am and 12
pm, and then again between 2 pm and 4 pm
 By doing so, it could prompt average purchase rates that were twice what
the firm had been achieving
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No “Perfect System” for Allocating Resources
 Problem: Needs to be simple enough so it is transparent to managers
(believed and understood) while being sophisticated enough to account for
the interdependencies across multiple time-varying inputs each with
different elasticities
 “Best” method
 Iterative approach which attempts to make optimal allocations across
nested levels of decisions
 Each level can be understood (bounded rationality of managers) while
allocation decision criteria and approach can be selected based on
characteristics of that level
 Can learn and improve at each level overtime (short feedback loop with
targeted metrics at each level; build specific expertise)
 Attempt to account for cross-level effects on a case-by-case basis
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GE Portfolio Analysis is Classic Approach for
Making Resource Tradeoff Decisions
 What are the pros and cons of this approach?
 How does it account for AER, BOR, and SCA tradeoffs?
Market
Segment
Attractiveness
(adaptation
of
Porter
Five
Forces
Model)
Competitive Strength (Available Levers)
Challenge for Top
Position
• Invest for growth
• Build on major strengths
• Protect areas of vulnerability
Build Preemptive
Position
• Diversify globally
• Consolidate position
• Focus on long-term cash flow
Expand Selectively
• Seek most desirable areas of
segment
• Trade share for earnings as
appropriate
• Monitor closely for further
decline
Challenge for Top
Position
• Build on major strengths
• Protect areas of vulnerability
Build Preemptive
Position
• Diversify globally
• Consolidate position
• Focus on long-term cash flow
Expand Selectively
• Seek most desirable areas of
segment
• Trade share for earnings as
appropriate
• Monitor closely for further
decline
Harvest
• Reduce fixed costs
• Minimize capital expenditures
• Reduce product line
• Seek opportunistic sale
Exit
• Exit market or prune product
line
• Determine timing so as to
present maximum value
• No further commitment of
resources
Strict Cash Flow
Management
• Minimum commitment of
resources
• Protect position in attractive
areas
Harvest
• Reduce fixed costs
• Minimize capital expenditures
• Reduce product line
• Seek opportunistic sale
Exit
• Exit market or prune product
line
• Determine timing so as to
present maximum value
• No further commitment of
resources
Strict Cash Flow
Management
• Minimum commitment of
resources
• Protect position in attractive
areas
Capitalize on
Attractiveness
• Selectively position to
improve base business
• Create well-defined and
rigidly enforced cut-off criteria
• Monitor closely
Preserve Position
• Make selective investments
to maintain position
• Seek opportunistic growth
• Apply strengths in more
attractive areas
Protect/Refocus
• Selectively invest for earnings
• Defend strengths
• Refocus to attractive segments
• Monitor for harvest or
divestment timing
Capitalize on
Attractiveness
• Selectively position to
improve base business
• Create well-defined and
rigidly enforced cut-off criteria
• Monitor closely
Preserve Position
• Make selective investments
to maintain position
• Seek opportunistic growth
• Apply strengths in more
attractive areas
Protect/Refocus
• Selectively invest for earnings
• Defend strengths
• Refocus to attractive segments
• Monitor for harvest or
divestment timing
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Anchoring – Adjusting Heuristics Approach
 Anchoring and adjustment heuristics are widely used,
though the exact anchoring rules vary in practice:
 In the percentage of sales method, marketing resources reflect the sales
revenue earned from the focal product
 With the percentage of profits method, the resources dedicated to
marketing instead vary with the profits earned by the product in
previous periods
 Managers who adopt the historical method simply set their present
resource allocations to a level very close to the previous year’s
spending
 Finally, the competitive parity method implies that managers set
resource allocation levels to match those of their competitors
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Attribution Approach
 Specifying an attribution model, such that the firm learns the exact dollar
impact that a small resource increase will exert, also can provide answers
to two more questions:
1. What is the relative dollar value impact of a marketing investment?
2. What is the profit-maximizing level of investment?
 By using an attribution model, managers thus can allocate resources to
optimize their desired outcome, as well as avoid waste or reliance on
arbitrary heuristics
 In turn, rather than reactive resource allocation strategies, managers can
implement proactive ones
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Experimental-Based Attribution
 Firms operate in environments in which various factors operate
simultaneously
 Managers still must make constant, rapid decisions about whether
to commit resources and how much to commit
 The experimental attribution approach involves an intervention,
outcome, design of the experimental condition, and a control
condition
 With this approach, all other factors (at least those under the
firm’s control) that can influence sales are purposefully kept
constant
 This method offers many advantages over an anchoring–
adjustment approach
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Experimental-Based Attribution (con’t)
 Deciding which factors to test is critical, and experiments can quickly
grow very complex
 Another element that defines the success of an experimental approach is
its reliability, that is, its internal and external validity
 Internal validity means that the experiment is well designed, and it
reflects three key criteria:
1. The cause should precede the effect in time, known as temporal precedence
check
2. The cause and the effect must be related, according to a covariation check
3. No plausible alternative explanations exist for the observed outcome, which
can be determined with a non-spuriousness check
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Components of Experimental Attribution
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Component Definition
Intervention A key marketing action whose
effectiveness the firm seeks to
document
Outcome The key marketing gain for the firm
implementing the experiment
Design When, where, and to whom the firm
administers the intervention
Control Group A region, customer, or situation
similar to the experimental
intervention that remains unchanged
during the experimental process

Response Model Attribution
 A response model is a statistical model that captures the relationship
between past marketing resources and past outcomes
 The underlying philosophy is that historical data contain insightful
information about whether and how much marketing resources truly
increase outcomes, which is useful to know when deciding on future
marketing actions
 With the basic—and often reasonable—assumption that past outcomes
relate to future outcomes, this approach leverages the past data to isolate
the relationship between marketing resources and performance
 Response models also offer many advantages, in terms of their flexibility
and usefulness
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Example: Samsung Electronics (South Korea)
 In 1999, Samsung Electronics needed to allocate its corporate budget of
$1 billion across 14 products, sold in more than 200 countries, with the
goal of improving the returns on its marketing spending
 Before the reallocation, Samsung used an anchoring and adjustment
method, allocating resources to products and countries in proportion to
the sizes of their markets
 When it adopted a response model approach, Samsung learned that it
had overinvested in North America and Russia. It reduced spending in
those regions and invested more in Europe and China
 By 2002, Samsung already had achieved significant market share gains in
these countries, increased its brand value by 30 percent (to $8.3 billion),
and grew its net income to $5.9 billion
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Response Models
A response model is a statistical and mathematical model
that captures the relationship between investments in
marketing resources and outcomes.
DAT 8.1
Description
• To discover the shape of the relationships between marketing efforts and
performance.
• To compare the effects of various marketing mix efforts on marketing outcomes.
• To capture the effects of competitive marketing efforts on a focal firm’s outcomes.
When to Use It
How it Works
Historical data contain insightful information about whether and how much marketing resources truly increase economic outcomes, which is
useful to know when deciding on marketing actions in the future. A basic assumption is that past outcomes relate to future outcomes, which
is reasonable most of the time, barring exceptions like recessionary periods. Using past data to uncover the relationship between marketing
resources and performance, response models provide four main insights. First, they capture the shape of the relationship between marketing
resources and outcomes, which is usually concave: Financial outcomes increase with increases in marketing resources but at a diminishing
rate. Second, response models reveal exactly how much financial outcomes would change if marketing efforts increased by 1 percent, also
known as marketing elasticity. Third, with a response model, marketing managers can figure out the relative impact of several resources and
thereby allocate them optimally and in proportion to the effectiveness of the different activities. Fourth, response models help managers
capture the effect of focal marketing efforts on outcomes while also controlling for competitive marketing efforts, which may increase the
clutter in the market.
If the marketing outcome is given by Y, and we have two marketing efforts (X1 and X2) by the focal firm, as well as competitor spending (Z1),
the formula for a response model is given by
ln(Y) = 𝛽1ln(𝑥1) + 𝛽2ln(𝑥2) + 𝛽3ln(𝑍1) + 𝜀
Where the ln() term is the natural logarithm of all variables in the model, which captures the diminishing returns relationship between the
outcome and the covariates, 𝛽1 and 𝛽2are called the elasticities of marketing efforts, 𝛽1 captures the % change expected in Y for a 1% change
in X1, 𝛽1 captures the % change expected in Y for a 1% change in X1, and 𝛽3 captures the % change expected in Y for a 1% change in
competitive efforts Z1, and 𝜀 is a random error term. With data about past outcomes and past marketing inventions, as well as confounds,
software available from SAS or SPSS can determine the sign, strength, and statistical significance of the coefficients.
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Facing tough economic times, newspaper executives at XYZ company evaluated how much to spend on marketing investments in the
newsroom (enhancing news quality by hiring more reporters, section editors, copy editors, and photographers) versus investing in the
sales force to generate more advertising revenues. They decided to build an econometric model to study the revenue effects of these
different marketing investments.
They collected monthly data for the previous 10 years, related to their investments in the newsroom and advertising sales force, their
total revenues (outcomes), and the newsroom and sales force investments of other newspapers operating in the same city (competitive
investments). The resulting response model captured the relationships among outcomes, marketing efforts, and competitive efforts, as
estimated in the following table.
With this model, XYZ determined that the elasticities of newsroom investments (.36) and sales force investments were both positive
and significant (.24). Thus, $1 invested in the newsroom led to a 36 percent increase in sales, and $1 invested in the sales force led to a
24 percent increase. The magnitude of the elasticities thus revealed that newsroom investments were 1.5 times more effective than
sales force investments. In XYZ’s current plan, the company split its investments equally between the newsroom and sales force, so the
response model estimates led the executives to make changes and invest more in the newsroom than in the sales force.
Adding in the effects of competitive efforts revealed that competitive newsroom investments hurt (-.12) their revenues more than did
competitive sales force investments (-.08). Thus the overwhelming evidence pointed to XYZ’s urgent need to commit strongly to
investing in the newsroom: The high quality of the newsroom would not only help it attract subscribers but also enable it to combat
attacks on its revenue by competitors.
Response Models
DAT 8.1
Example
Variable Coefficient Capturing Elasticity p-Value for Statistical
Significance
Ln(Newsroom investments) 0.36 0.03
Ln(Sales force investments) 0.24 0.02
Ln(Competitive newsroom investments) -0.12 0.01
Ln(Competitive sales force investments) -0.08 0.02
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Resource Allocation Using Market Reponses
Models: Pros and Cons
 Classic Approaches to Sales Forecasts and Marketing
Budgets
 Percent of Sales Method
 Industry Benchmarks
 Last Period +/- Reward and Punishment
 “Squeaky Wheel” Model
 “Spread the Butter” Model
 Response Model
 Builds a “black box” model based on past response to changes in
inputs
 Once model is built then optimizes for objective (Solver)
 In essence it is just curve fitting, which assumes past is good
predictor of future
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A Response Model System Has Eight Key
“Parts”
1) Marketing Inputs 2) Competitive Actions 5) Business Outputs
(metrics)
3) Environmental
Factors
6) Optimize and
Evaluate
8) Adjust
Marketing Inputs
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Product Design
Price
Advertising
Selling Effort
Etc.
4. Market
Response
Model
Awareness level
Preference level
Sales level
7. Objectives

Steps to Building a Response Model
1. Determine relevant inputs, outputs, and objectives
 Marketing actions (price, promotion, sales coverage)
 Competitive actions (price, new products, discounts)
 Environmental factors (government, trade barriers)
 Business outcomes/metrics (sales level, awareness)
 Objective (optimize sales or profits, advertising or sales coverage)
2. Determine the “form” and “calibrate” the response model
 Form (i.e., type of equation): linear, saturation, hysteresis, etc.
 Calibrate: estimate parameters using experiments, manager judgments, past data (need variance
across inputs)
3. Estimate response model and evaluate (vs. objectives)
4. Optimize (Solver) to adjust marketing inputs
5. Design field experiment and test
6. Rollout or adjust model and redo process
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Select Response Model’s Functional Form
That Captures Reality
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 Base level: “sales” with no input
 Linear: constant relationship between input and output
(infrequent)
 Delayed response: lag between input and output
(common)
 Saturation: curve flattens at some higher level (diminishing
returns, common)
 S shape: slow to start and reach saturation (good starting
point)
 Hysteresis: slow to decay after input removed
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Examples: Response Model’s Functional Form
Y
X
Y
X
Saturation
Linear
Y
X
S-Shaped
Current
Sales
Response
Function
Current
Effort
Sales
Response
Effort Level
Y = a (1 – e–bx) + c
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Calibration is the Process for Estimating
Parameters in Response Model
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 Estimate from historical data
 Data from CRM system
 Must be sufficient variability in the data to allow for reliable estimation
(across regions, overtime)
 Conduct experiments
 Fairly easy in online settings
 P&G does this for advertising for most new product launches (3 cities)
 Elicit managerial judgment
 Quick and helps build consensus (combine with others)
 Encourages systematic thinking
 A series of questions on what would happen when inputs change
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Preprogrammed Response Models (many
included in ME)
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 ADBUDG: market share response model for advertising spend, which builds in
many known advertising phenomena
 Floor to share w/o advertising
 Ceiling where advertising spend has no effect
 Need some advertising rate to maintain share
 Built in typical delays and carryover
 Sales force allocation models
 GEOLINE: allocation of salespeople over territory
 CALLPLAN: allocation of sales calls over customers, products
 MDZ: allocation of compensation over salespeople
 Many other response models account for multiple types of marketing inputs
simultaneously
 Interaction among advertising, salespeople, and promotion $
 Consultants specialize in each model and across industries
 Build your own model for key ongoing allocation decisions
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Solver: An Optimization Program in Excel
 Add-in for Excel that “solves” linear and non linear
functions for optimal point
 Plug in equation for response function to optimize (set min
and max limits)
 Set any constraints (e.g., advertising spending > 0)
 Solver gives optimum level of input(s) “assuming” response
function captures relationship between inputs and outputs
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“If you can’t measure it, you can’t manage it!”
The Balanced Scorecard
 Managers need intermediate metrics to capture the effects of their
decisions in order to adjust actions
 Short feedback loop, forward-looking, fast response
 Scope of metric should align to domain of decision
 Common marketing metrics:
 Customer satisfaction (product focused, forward-looking)
 Service quality (experience and relationship focused)
 Brand awareness (promotion focused, fast response)
 Brand strength and quality (promotion, price, and product focused, slow
response/high inertia)
 Customer retention (aggregate, backward-looking)
 Loyalty (probably best forward-looking aggregate measure of marketing’s
effect)
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However, Some Measures of Loyalty are
Misleading
High Low
High
True
loyalty
Latent
loyalty
Low
Spurious
loyalty
No loyalty
Loyalty: attitudes
and behaviors that
signal a motivation
to maintain a
relationship
Attitudes: captures
beliefs and feelings
relative to
competitive options
Behaviors: captures
actual actions
Repurchase/WOM Behaviors
Relative
Attitude
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Net-Promoter Score (NPS): Popular Loyalty
Measure
 Net-promoters: % of customers who are promoters - % who are
detractors (i.e., removes people in zone of tolerance)
 Promoters answer 9 or 10 and distractor 0 to 6 to question,
“How likely is it that you would recommend [firm] to a friend or
colleague?”
 Scores are linked to profitable growth
 Scores of 75% and above are world class
 Mixed support in academic research
 Pros: simple and good “single item” measure
 Cons: not very diagnostic, may not be true loyalty since no actual
behaviors
38
38
© Palmatier

Growth by Word of Mouth
10%
5
0
-5
-10
-10 0 10 20 30 40 50 20 25 30 35
20%
10
0
-10
Net Promoters Net Promoters
3
Year
Growth
3
Year
Growth
Airlines Car Rentals
Southwest
United
American
Enterprise
Avis
Hertz
See The Rules of
Measurement
and NPS for
overview
39
© Palmatier

Benefits of Customer Loyalty
 Loyal customers tend to spend more with the organization over time
(expansion, cross-selling)
 Less churn, higher retention
 Price premium
 On average costs of account maintenance are lower than for new customer
costs
 Employee retention is more likely with a stable customer base (impact on
firm culture)
 Positive WOM increases customer base and reduces acquisition costs
 Positive attributions and competitive sheltering
 Shares information and helps innovation
 Very strong positive affect on CLV
See Building
Loyalty in
Business
Markets
40
© Palmatier

41
Loyalty is Better than Accounting Metrics, but…
Relationship
Equity
Service
Quality
People
Physical
Place
Promotion
Process
Price
Product
Brand
Equity
Value
Equity
Satisfaction
Loyalty
(NPS)
7Ps Marketing
Mix (expense)
Customer Equity
Stack (assets)
Intermediate
Mkt. Metrics
Accounting
Metrics
Profits
Costs
Sales
Growth
1) Can be
long delay
2) Operates
thru many
mechanisms
(AER)
3) Not very
diagnostics
41
© Palmatier

Many Marketing Metrics, But Two Main
Approaches: Pros and Cons?
1. Use specific metric for what you want to control (narrow, fast, and
domain specific)
 Brand (awareness, quality, strength)
 Offering (innovativeness, adoption rates, price premium, value)
 Relationship (loyalty to salesperson, trust, relationship quality, velocity)
 Acquisition (# new customers, CLV, duration)
 Retention (churn, lost customer, share)
2. Use aggregate financial metrics and analyze using chain ratios
(uses accounting measures, can be decomposed)
 Net marketing contribution (NMC) tells us profit after sales and marketing
costs
 Marketing ROS tells us what portion of our sales is profit (MROS =NMC/sales
* 100%)
 Marketing ROI tells us our earnings for every 1$ invested in sales and
marketing (MROI=NMC/Sales and marketing costs *100%)
42
42
© Palmatier

Types of Metrics
© Palmatier 43
Marketing Mix Functions Marketing Terms Close Financial Analogs
Customer Delight Metrics Awareness
Interest
Desire
Sales
Loyalty
Market share
Share of wallet
Social influence
Return on marketing spending
Sales return to marketing spending
Projected sales
Sales/total SIC sales
Customer sales/customer total SIC sales
Advertising Metrics Impressions/visits/page views
Click-through rate
Media impressions
Recall
Cost per lead
Cost per click
Cost per impression
Cost per recall
Pricing Metrics Price premium
Price elasticity
Brand equity
Unit margin/ margin percentage
Marginal price effort x (price/sales)
Revenue premium
Sales Force Leads
Conversions
Winbacks
Cost per lead
Cost per conversion
Cost per winback
Distribution Stock-keeping unit growth
Same store sales
Passthrough
Total inventory
Sales per store/previous year sales
Net margin
Note: SIC = Standard Industry Classification

Net Marketing Contribution (NMC) as a Chain
Ratio
44
Sales
(COGS)
Gross Profit
(SGA)
Net Income
Sales
(COGS)
Gross Profit
(Sales and Marketing Costs)
Net Marketing Contribution
(GA)
Net Income
See Note on
Marketing
Performance
Assessment for
excellent overview
of metrics
44
© Palmatier
Strategies to
Grow Market
Demand
Strategies to
Lower Channel
Costs
Strategies to
Grow Market
Share
Strategies to
Increase
Average
Selling Price
Net Marketing
Contribution
Market
Share
Market
Demand
= x x
Average
Selling
Price
Channel
Discount
Profit
Margin
Marketing
Budget
Strategies to
Increase Profit
Margin
Strategies to
Improve
Marketing
Efficiency
x x -

MBM6
Chapter 2
(Best 2012)
Marketing Profitability & Marketing
Profitability Metrics
MROS & MROI Can be Used to Benchmark
Entities (competitors, products, regions)
45
Percent Margin
38.8%
Other
Operating
Expenses
$20 million
Sales Revenues
$125 million
Marketing &
Sales Expenses
$18.5 million
Gross Profit
$48.5
million
Net Marketing
Contribution
$30 million
Operating
Income
$10 million
Marketing ROS
24%
Marketing ROI
162%

MBM6
Chapter 2
Internal View of Performance External View of Performance
(Best 2012)
Effective Marketing Dashboards Capture
Multiple Views of the Firm Over Time
46
Financial Metrics Performance
Profit Metrics
• Gross Profits
• Return on Sales
• Return on Assets
55.0%
17.0%
17.8%
Expense Metrics
• Marketing & Sales Expenses
• General & Administrative Expenses
• Other Expenses
21.0%
8.0%
12.0%
Asset Management Metrics
• Sales-to-Assets Ratio
• Accounts Receivable
• Capacity Utilization
1.05
15.0%
67.0%
Shareholder Metrics
• Return on Equity
• Return on Capital
• Earnings per Share
15.0%
13.0%
$2.00
Financial Metrics Performance
Market Metrics
• Market Growth Rate
• Market Share
• Market Development Index
22.5%
8.5%
40
Customer Metrics
• Customer Satisfaction
• Customer Retention
• Customer Lifetime Value
64
65%
$45
Competitiveness Metrics
• Product Performance
• Service Quality
• Customer Value
11.0
-9.0
8.0
Marketing Profitability Metrics
• Net Marketing Contribution
• Marketing ROI
• Marketing ROS
$156
162%
34.0%

Framework for Managing Resource Trade-
Offs
Inputs to the Managing Resource Trade-Offs
Framework
Positioning Statements
AER Strategies
BOR Strategies
Outputs of the Managing Resource Trade-Offs
Framework
Plans and Budgets
Marketing Metrics
© Palmatier 48

Managing Resource Trade-Offs
Approaches & Processes
Heuristic approach
Attribution approach
Analyses
Response model attributions
Experimental-based attributions
Inputs (MP#1, 2, and 3)
Positioning Statements
• Who, what, and why support,
both overall and for each
persona
• AER stages
AER Strategies
• What strategies work best for
each persona
• AER stage
BOR Strategies
• Brand, offering, and relationship
strategies
Plans and Budgets
• Budget per marketing activity
• Allocation across categories
• Time horizon
Marketing Metrics
• Marketing metrics
• Financial metrics
Marketing Principle #4: All Resources Are
Limited  Managing Resource Trade-Offs
49
© Palmatier

Inputs to the Managing Resource Trade-Offs
Framework
 The outputs of the three previous Marketing Principles serve as the key
inputs to the resource trade-off framework, such that each MP requires
some initial trade-off decisions
 The positioning statement attained through MP#1 answers key questions
about who customers are, what needs the product or service can fulfill,
and why this product or service is the best option to satisfy those
customers’ needs
 The AER positioning statements, the output from MP#2, also are key
inputs for the resource trade-off framework
 Finally, the input derived from MP#3, which builds on MP#1 and MP#2,
describes how to use BOR strategies to build SCA and erect strong
barriers against competitive attacks
© Palmatier 50

Outputs of the Managing Resource Trade-
Offs Framework
 A fundamental problem for effective resource allocation is
identifying and measuring the best or most appropriate
metrics
 As a popular saying holds, a firm is only likely to achieve
what it measures
 For most marketing resource investments, both financial and
marketing metrics are necessary to capture the different
aspects of the benefits earned from the investment
© Palmatier 51

Outputs of the Managing Resource Trade-
Offs Framework
 Another set of outputs pertains to the three components of
each resource allocation decision:
 Budget per marketing activity, or the size of the commitment the
firm makes to the marketing activity
 Allocation across categories, which reflects the percentage split of
the marketing budget for a specific activity across categories
 Time horizon of the budget, involving the timespan for which the firm
commits to this marketing budget
 Thus when choosing its advertising budget for example, a
firm would determine how many total dollars to spend
(budget) on different forms of advertising (e.g., print and
online), as well as how long to run the advertising campaigns
(e.g., two months)
© Palmatier 52

Process for Managing Resource Trade-Offs
Five-step process for managing resource
trade-offs:
1. Identify strategically relevant metrics
2. Assess the relationship between metrics and
marketing resources
3. Assess the optimality of the resource allocation
decisions
4. Finalize the resource allocation decisions
5. Integrate across different marketing activities
© Palmatier 53

Real Example: CallPlan Response Model at
United Airlines
55
 Objective: Allocate salesperson time to maximize gross profits
 Build and calibrate model from average salesperson answer to 4 questions:
What would sales of this account be if . . .
 You don’t visit accounts (X0)
 You visit the account the same as last period (X1)
 You visit the account 50% more than last period (X2)
 You visit the account as frequently as possible (X3)
 Optimize response model:
 Maximize sum of account
revenues x account margin
 Constraints are salesperson
time and min./max. calling
restriction
 Provides recommended
calling frequencies for each
account
55
© Palmatier

Current Allocation vs. Response Model’s
Recommended Allocation
 Profit with current allocation: $11,985
 Predicted profit with optimal allocation: $13,000
 Do you believe this will happen?
Account Number Account Number
Number
of
Calls
Number
of
Calls
0
1
2
3
4
5
6
7
8
1 2 3 4
0
1
2
3
4
5
6
7
8
1 2 3 4
Current Allocation Recommended Allocation
56
© Palmatier

Test Recommended Allocations in Field
Experiment
 Sample
 20 randomly selected geographically-stratified salespeople
 20 other salespeople matched on key demo (age, experience, territory)
 Randomly selected 1 from each pair, others were control
 Treatment
 Both groups were asked judgment questions, but only one group given
recommended allocations
 Other group given computer feedback summarizing answer to
questions (helps prevent a demand effect)
 Evaluated salesperson sales growth after six months
 Experimental group 11.9%
 Control group 3.8%
 Difference 8.1%, probability this is due to chance is < .025
57
© Palmatier

Takeaways
 All resources are limited. Managers must manage resource trade-offs to
develop an effective marketing strategy. Most marketing decisions require
trade-offs across multiple objectives, because resources are constrained and
often interdependent.
 Several factors increase the need for ongoing resource trade-offs, including
limited resources (resource slack), changes in the composition of consumer
segments, changes in the lifecycle stages of the product portfolio, changes in
the market landscape due to competitive actions, and changes in the
effectiveness of marketing activities.
 Approaches to managing resource trade-offs have evolved from an
exclusively heuristic-based era, in which managers solved resource allocation
problems using simple rules of thumb, intuition, and judgment, to a data-
based era, in which managers rely on statistical models and detailed
information.
 The heuristics approach relies on anchors, often related to spending in the
previous period, which managers use to make marketing resource allocation
decisions. Then managers may adjust their decisions every period, after
observing the prior outcomes.
© Palmatier 59

Takeaways
 An attribution approach asks, How does a specific (e.g., 1 percent)
increase in a resource option affect a particular outcome, keeping all else
constant? The model integrates past decisions and past outcomes, then
produces a mathematical assessment of how much impact each resource
trade-off truly has for generating outcomes.
 A response model-based attribution approach captures the relationship
between past marketing resources and past outcomes. A basic
assumption is that past outcomes relate to future outcomes, which is
usually reasonable. The use of past data then can uncover the
relationship between marketing resources and performance.
 There are three key inputs and two key outputs of the framework for
managing resource trade-offs. The inputs are the outputs of the previous
three principles. The outputs are a description of the firm’s resource
plans and budgets and the use of key marketing metrics that can
effectively validate these resource outlays.
© Palmatier 60

Readings
 Note on Marketing Performance Assessment (great
overview on marketing metrics and process for using
metrics)
 The Rules of Measurement (process for NPS, response rate
and bias)
 Building Loyalty in Business Markets (building B2B
loyalty)
 Marketing Strategy Book: Chapter 8
61
© Palmatier

Analytics Driven Case: Allocating Dollars
Wisely at BRT Tribune
 Newspaper industry had enjoyed high profits for decades, but between
2000 and 2010, daily circulation and advertising revenue declined
significantly, in favor of less profitable free online news and other sources
 Salespeople are limited resource. BRT’s sales force split in 6 divisions,
historically allocated by percentage of sales
 Company faced an issue of resource allocation - how to best allocate
limited resources (salespeople)
 BRT used a scientific, attribution-based approach to budgeting because
marketing strategy is based on goals (profit maximization), rationale
(sales response models), actions (budgets and reallocation) rather than
just a gut-based decision (i.e. percentage of sales)
© Palmatier 63

Analytics Driven Case: Allocating Dollars
Wisely at BRT Tribune
 Sales Response Model
 Used managerial estimates of revenue levels at different effort levels and a
mathematical function capture the relationship between sales force and
revenue
 Estimate shape of response model curve
 Optimization Procedure
 Add or subtract a certain number of salespeople from each division such that
the marginal benefit of adding and subtracting salespeople across all six
divisions is exactly equal to the marginal cost
 Optimal allocation of current salespeople
© Palmatier 64

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