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Summary lectures, readings, tutorials - Market Assessment (328043)

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Provides an in-depth summary of the lectures, weblectures, readings and tutorials of the course Market Assessment given by Deleernsyder. This provides all material to study for your exam. Good luck!

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  • 31 mei 2023
  • 108
  • 2022/2023
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Market Assessment 328043
Lecture 1: Introduction
1. Introduction
1. A bat and a ball cost 1.10$. The bat costs $1.00 more than the ball. How much does
the ball cost? Majority will probably think the ball costs $0.10 (following the brain
reaction). But it’s actually $0.05. Make an equation, then you will get to the right
answer. Regular brain -> $0.10, mathematical brain -> $0.05. if you use a structure,
formal tool -> find out solution easily. One of the reasons why market assessment
tools can help to come to right solution.
2. If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100
machines to make 100 widgets? You would initially say 100 minutes. 5 minutes is the
right answer. Way our brain works. Using analytical way of thinking -> then you will
get to the right answer.
3. Yoghurt A has 10% fat <> yoghurt B is 90% fat free. Which yoghurt (A or B) is more
healthy? It’s the same. If you show this to random people: both variants in
supermarket: majority will say that yoghurt B is the more healthy one. Be immune ->
know the biases. We all have cognitive biases. If you know them, you are more likely
immune. Follow instant reactions -> very often we are not correct. Follow other
approaches and be aware that you can be fooled by your own brain.
4. Parking fine is cheaper than all the pay options there are. If you have multiple
options, you also always have to take the default option into account. (Not doing
anything). In stead of 2 options, you also have a 3rd option.
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 in market
➔ Needed to analyse the structure/dynamics of a market in which the
firm in 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?
(Important!)
• Enhance decision making capabilities
- Improve decision efficiency (save time) and effectiveness (better decisions)
- Adding serious analytics under decisions. More correct decisions & save time.
• Problem (opportunity) recognition
- More easily/quickly detected by collecting/integrating/organizing/presenting
knowledge



1 – Julia van Dommelen

, - Plotting sales of different brands over time, different types of customers, gives
you a lot of information. For instance: younger people increase spending, older
people decrease, adjust marketing campaigns!
• Avoid limitation of cognitive constraint
- Managers allocate their time over a large number of different problems
- Humans suffer from biases & overconfidence
• Forces you to selecting a problem-solving approach
- What objective to achieve? (e.g. maximizing sales <> profit <> minimizing
losses?)
- What do you want to actually achieve? Not always maximize profit.
• Forces you to list alternative options and choices
- What are the alternative options? (including opportunity losses from NOT acting!)
1.3 Typical marketing questions to address:
• How large is the market for product XX? Is it growing or shrinking? -> Invest? 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?
• Can the market be usefully segmented? Along which dimensions?
• Who are the competitors in the market? How do they position compared to us?
• Where to open the next store?
• How many brand variants should we offer?
• Etc…
1.4 Market Assessment skills
• Making decision based on critical thinking and a structured decision process instead
of “management by intuition”
• Extracting, analysing, 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 judgment calls in the light of limited information
(sometimes also “out-of-the-box” thinking)
• Critically evaluate the model outcomes
• Communicating results professionally and providing clear recommendations/making
decisions.

• From info and estimates -> Make good decisions! (Especially good decisions!)
• Not only about techniques: About decision making process with using data, doing
analysis, then use output in decision making.
• Translate the solution into managerial/management skills/decisions!




2 – Julia van Dommelen

,McKinsey & Company: Insights & Analytics
What they do: “Our goal is to help our clients develop a set of practical and interlocking
capabilities that reveal – and maximize the profitable use of – the data appropriate to their
situation.”
• Discovering insights by analysing multiple data sources.
• Designing programs based on the insights generated
• Delivering insights-driven growth for the short- and long-term.

2. A decision calculus
Not enough models to actually use them back in those days. Now we have plenty of
techniques! Belongs to mandatory reading. Keep in simple: if you build a model: build
simplification of reality. Type of relationships you want to grab. Train basic translations from
statistical models to making better decisions. Essence of paper. Models are too little used, not
enough using them. When paper was written not enough models. Most important reasons
why not using them: to difficult, estimate and need data for it. A lot of things are uncertain.
Models are designed to account for uncertainty. You will never predict the exact number,
need a good guess what next demand level will be for certain problems.
2.1 Definition
Decision calculus = model-based set of procedures for processing data and judgments to
assist a manager in his decision making.
• Based on data
• Uncover underlying processes
• Uncertainty
• Guide managers’ decisions
<>
• Models are not always used
• If used, results not always implemented
2.2 Obstacles for managers to use models
• Good models are hard to find
- Develop your own models!
• Good parameterization is hard
- Relevant data not always available
• Managers don’t understand the models
- Use intuitive models
• Models are incomplete
- A simplification of reality
Models assist managers but do NOT replace them!
Sales of ice creams on daily basis + prices of ice creams on daily basis. Find out: positive
price elasticity: if you raise your price, your demand will increase. You should raise price as
manager. That is the outcome of the mode. Doesn’t make sense, but its true. This happens
with luxury products. For ice cream it doesn’t seem logical. It’s a seasonal product. Ice cream

3 – Julia van Dommelen

, vendor will raise prices in summer. Ice cream vendor: bad weather: not many people at the
beach. Not ask same price as in the summer, everyone wants ice cream then. In low season:
set price low, in high season: raise price. This is how you see: running standard analysis on
price elasticity, you might end up with a big mistake and wrong decision. You still need a
manager to evaluate what is going on. Include valuable called temperature or season.
Models and tools are there to help you. But you always have to stay critical. Especially when
outcome seems illogical.
2.3 Model Requirements




“Managers now routinely use model-based results for marketing decisions”
Marketing decision that benefit most from model-based input:
• Repetitive promotion and pricing programs;
• Media allocation decisions;
• Distribution programs;
• Product assortment & shelf space allocation decision 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 the brand in week t
PIt price index (= actual price relative to regular price or Pt/RPt) in week t
dMlt dummy = 1 if store runs merchandising support I in week t, and = 0 otherwise
[with 3 merchandise support types: FO = feature only; DO = display only; and FD
= both feature and display]




4 – Julia van Dommelen

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