This is a summary of all lectures given for the course Market Assessment including notes. Additionally, the summary also includes several exam practice questions and all notes on the knowledge clips associated.
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
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