Market Assessment Summary:
Market Assessment Lecture 1:
Quiz questions:
1. A bat and a ball cost 1.10€. The bat costs 1.00€ more than the ball. How much does
the ball cost?
€0.05 → bat + ball = 1.10
2. If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100
machines to make 100 widgets?
5 minutes
3. Yoghurt A has 10% fat <> yoghurt B is 90% fat free. Which yoghurt (A or B) is more
healthy?
They are exactly the same, but 10% fat sounds more negative and 90% fat free sounds more
positive.
4. You plan a shopping trip in Amsterdam with your best friend to buy clothes and
houseware.
To be able to transport everything, you decide to go by car. You expect the shopping
+ lunch to take at least 6h and at most 8h. Parking space near the city center all have
the same tariffs (you risk a €35 parking fine in case you do not pay) and you can only
choose among 2 payment schemes:
OPTION A: 4h ticket for €24 (€6/h price per hour), and in case you extend it, you
need to pay €8/h per extra hour started
OPTION B: a full day ticket at a fixed of €40
What do you do? Please motivate your choice
The fine is actually lower than the parking costs, so the alternative is ignored
1.1 Definition & Role:
Market Assessment= the systematic use (= analysis) of hard data and judgments about
customer, companies, competition, and industry context to support strategic marketing
decisions.
- Acquire relevant input data in market
- Needed to analyse the structure/dynamics of a market in which the firm is
competing or wishes to compete
- The basis to develop marketing strategies for the firm
Market Assessment supports marketing decisions
- Helps to ask good question and to use systematic, fact-based methods to answer
them
,1.2 Why do we need formal assessment tools?
- Enhance decision making capabilities
o Improve decision efficiency (save time) and effectiveness (better decisions
- Problem (opportunity) recognition
o More easily/quickly detected by collecting/integrating/organising/presenting
knowledge
- Avoid limitation of cognitive constraint
o Managers allocate their time over a large number of different problems
o Humans suffer from biases & overconfidence
- Forces you to selecting a problem-solving approach
o What objective to achieve? (e.g., maximising sales <> profit <> minimising
losses?
- Forces you to list alternative options and choices
o What are the alternative options? (including opportunity losses from NOT
acting!)
1.3 Market Assessment Skills:
• Making decisions based on critical thinking and a structured decision process instead
of “management by intuition”
• Extracting, analyzing, and interpreting information from text, graphs, and data (as
well as acknowledging missing information)
• Collecting relevant data to infer relevant market information
• Evaluating, choosing, and calibrating market models that enable better managerial
decisions
• Making reasonable assumptions and judgments calls in the light of limited
information (sometimes also “out-of-the-box” thinking)
• Critically evaluation the model outcomes
• Communicating results professionally and providing clear recommendations / making
decisions
1.4 Typical Marketing Decisions this course will address:
• How large is the market for product XX? Is it growing or shrinking? -> What new
market to invest in? How much?
• How should the product be priced? What will be the effect of price
changes/promos?
• How to allocate advertising across traditional & other media? Total budget?
• What marketing actions are effective?
, • Who are my competitors in the market? How do they position compared to us?
• Where to open the next store?
• How many brand variants should we offer?
2.1 Models & managers:
YET, skepticism & resistance
- Complex to use
- Emphasis on data collection/storage instead of analytics
- Unable to create an analytical culture/ mindset in the firm
- Results not always trusted/used
Decision calculus= model-based set of procedures for processing data and judgment to
assist a manager in decision making
- Based on data
- Uncover underlying processes
- Uncertainty
- Guide managers’ decisions
- Methods not always used
- If used, results not always implemented
2.2 Obstacles for managers to rely on models / analytics:
- Good models/methods are hard to find
o Develop your own models/method!
- Good parameterisation is hard
o Relevant data not always available
- Managers don’t understand the models/methods
o Use intuitive models
- Models/methods are incomplete
o A simplification of reality
Models assist managers but do NOT replace them
2.3 Model/method requirements:
1. Simple = easy to understand
2. Robust = result in acceptable outcomes, e.g., 0 < share < 100%
3. Easy to control = input-output logic clear and controllable by managers
4. Adaptive = easy to adjust to new market/firm situation
5. Complete on important issues = realistic & leaves room for subjective judgment &
input
6. Easy to communicate with = produces meaningful variables and parameters with
clear interpretation, e.g., price elasticity
Leeflang & Wittink (2000, IJRM): “Managers now routinely use model-based results for
marketing decisions”
Marketing decisions that benefit most from model-based input:
- Repetitive promotion and pricing programs
, - Media allocation decisions
- Distribution programs
- Product assortment & shelf space allocation decisions for individual stores
- Direct mail solicitations
→ Potential for automated decisions!
2.4 Model example: Scan*pro model
Basic model structure:
With:
Qt (volume) sales of brand in week t
Plt price index (= actual price relative to regular price or Pt / RPt) in week t
dMt dummy= 1 if store runs merchandising support / in week t, and= 0 otherwise
[with 3 merchandise support types: FO= feature only; DO= display only; and FD=
both feature & display]
e𝛼 = baseline sales at the store |
β = price elasticity | → = estimates
Y = multiplier |
Linear function in Ln(PI) and merchandise dummies dFO, dDO, & dFD:
→ estimate w/ OLS regression:
(i)
(ii)
(iii)
Exercise: Does this Scan*Pro model satisfy the criteria in Little (2004, MgmtSc)?
Why not hire a statistician to build your model?
2.5 Future of business analytics?
“Biggest bottleneck in the managerial use of models is not their development but getting to
use them!”
- Managers refuse to use the models because they do not understand them
Market Assessment Lecture 1:
Quiz questions:
1. A bat and a ball cost 1.10€. The bat costs 1.00€ more than the ball. How much does
the ball cost?
€0.05 → bat + ball = 1.10
2. If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100
machines to make 100 widgets?
5 minutes
3. Yoghurt A has 10% fat <> yoghurt B is 90% fat free. Which yoghurt (A or B) is more
healthy?
They are exactly the same, but 10% fat sounds more negative and 90% fat free sounds more
positive.
4. You plan a shopping trip in Amsterdam with your best friend to buy clothes and
houseware.
To be able to transport everything, you decide to go by car. You expect the shopping
+ lunch to take at least 6h and at most 8h. Parking space near the city center all have
the same tariffs (you risk a €35 parking fine in case you do not pay) and you can only
choose among 2 payment schemes:
OPTION A: 4h ticket for €24 (€6/h price per hour), and in case you extend it, you
need to pay €8/h per extra hour started
OPTION B: a full day ticket at a fixed of €40
What do you do? Please motivate your choice
The fine is actually lower than the parking costs, so the alternative is ignored
1.1 Definition & Role:
Market Assessment= the systematic use (= analysis) of hard data and judgments about
customer, companies, competition, and industry context to support strategic marketing
decisions.
- Acquire relevant input data in market
- Needed to analyse the structure/dynamics of a market in which the firm is
competing or wishes to compete
- The basis to develop marketing strategies for the firm
Market Assessment supports marketing decisions
- Helps to ask good question and to use systematic, fact-based methods to answer
them
,1.2 Why do we need formal assessment tools?
- Enhance decision making capabilities
o Improve decision efficiency (save time) and effectiveness (better decisions
- Problem (opportunity) recognition
o More easily/quickly detected by collecting/integrating/organising/presenting
knowledge
- Avoid limitation of cognitive constraint
o Managers allocate their time over a large number of different problems
o Humans suffer from biases & overconfidence
- Forces you to selecting a problem-solving approach
o What objective to achieve? (e.g., maximising sales <> profit <> minimising
losses?
- Forces you to list alternative options and choices
o What are the alternative options? (including opportunity losses from NOT
acting!)
1.3 Market Assessment Skills:
• Making decisions based on critical thinking and a structured decision process instead
of “management by intuition”
• Extracting, analyzing, and interpreting information from text, graphs, and data (as
well as acknowledging missing information)
• Collecting relevant data to infer relevant market information
• Evaluating, choosing, and calibrating market models that enable better managerial
decisions
• Making reasonable assumptions and judgments calls in the light of limited
information (sometimes also “out-of-the-box” thinking)
• Critically evaluation the model outcomes
• Communicating results professionally and providing clear recommendations / making
decisions
1.4 Typical Marketing Decisions this course will address:
• How large is the market for product XX? Is it growing or shrinking? -> What new
market to invest in? How much?
• How should the product be priced? What will be the effect of price
changes/promos?
• How to allocate advertising across traditional & other media? Total budget?
• What marketing actions are effective?
, • Who are my competitors in the market? How do they position compared to us?
• Where to open the next store?
• How many brand variants should we offer?
2.1 Models & managers:
YET, skepticism & resistance
- Complex to use
- Emphasis on data collection/storage instead of analytics
- Unable to create an analytical culture/ mindset in the firm
- Results not always trusted/used
Decision calculus= model-based set of procedures for processing data and judgment to
assist a manager in decision making
- Based on data
- Uncover underlying processes
- Uncertainty
- Guide managers’ decisions
- Methods not always used
- If used, results not always implemented
2.2 Obstacles for managers to rely on models / analytics:
- Good models/methods are hard to find
o Develop your own models/method!
- Good parameterisation is hard
o Relevant data not always available
- Managers don’t understand the models/methods
o Use intuitive models
- Models/methods are incomplete
o A simplification of reality
Models assist managers but do NOT replace them
2.3 Model/method requirements:
1. Simple = easy to understand
2. Robust = result in acceptable outcomes, e.g., 0 < share < 100%
3. Easy to control = input-output logic clear and controllable by managers
4. Adaptive = easy to adjust to new market/firm situation
5. Complete on important issues = realistic & leaves room for subjective judgment &
input
6. Easy to communicate with = produces meaningful variables and parameters with
clear interpretation, e.g., price elasticity
Leeflang & Wittink (2000, IJRM): “Managers now routinely use model-based results for
marketing decisions”
Marketing decisions that benefit most from model-based input:
- Repetitive promotion and pricing programs
, - Media allocation decisions
- Distribution programs
- Product assortment & shelf space allocation decisions for individual stores
- Direct mail solicitations
→ Potential for automated decisions!
2.4 Model example: Scan*pro model
Basic model structure:
With:
Qt (volume) sales of brand in week t
Plt price index (= actual price relative to regular price or Pt / RPt) in week t
dMt dummy= 1 if store runs merchandising support / in week t, and= 0 otherwise
[with 3 merchandise support types: FO= feature only; DO= display only; and FD=
both feature & display]
e𝛼 = baseline sales at the store |
β = price elasticity | → = estimates
Y = multiplier |
Linear function in Ln(PI) and merchandise dummies dFO, dDO, & dFD:
→ estimate w/ OLS regression:
(i)
(ii)
(iii)
Exercise: Does this Scan*Pro model satisfy the criteria in Little (2004, MgmtSc)?
Why not hire a statistician to build your model?
2.5 Future of business analytics?
“Biggest bottleneck in the managerial use of models is not their development but getting to
use them!”
- Managers refuse to use the models because they do not understand them
