Pagina |1
Slides & Lecture Notes Market
Assessment
, Pagina |2
Week 1
A marketing strategy stands and falls with
segmentation – targeting – positioning. The
4Ps are used to either:
- Create value: product and price; the
first is more difficult to change
- Deliver value: promotion and place
(channels)
o Promotion: the change of
the fraction of consumers
that know you awareness
o Place: the market coverage
Another important question to ask oneself
is to what extent a company should invest
in either the attraction or the retention of costumers.
A response function can easily be represented in a graph.
For example:
Units sold is used here since revenues = price * units sold.
When one wants to know the response to a change in price, one
often sees a downward slope the higher the price, the less
units sold.
Task 1: What is the response? (response function)
Task 2: Decision-making – what is the optimal point?
e.g. find the optimal value of x (=price)
low price: low margins, high demand
high price: high margins, low demand
An outbound campaign means reaching out to consumers at a
certain cost.
The market response can be assessed by using surveys / empirical data, experiments and
opinions. Based on this market response, decisions can be made. This can either be the
practical implementation of how to make profit maximising decisions and what if scenarios
(simulation). The marginal benefit should be equal to the marginal cost.
Preferences
Preferences are the guiding principles for decision-making. There are different measures of
preferences possible. For example:
- Taste testing (e.g. foods and drinks)
- Sales per facing (in e.g. supermarket – shelf spacing)
- Sales
These examples are all examples of “revealed preferences” (=taking action). Measurements of
preferences can vary across a continuum, from stated preferences to revealed preferences:
- Intention to buy – many different companies often use this method
, Pagina |3
o Too hard a question for consumers / respondents
o Over-confident about the buying probability
- Self-reported importance weights
o Lack of discrimination, everything is important
You do not ask for trade-offs is this way; they want the best products for free
- Trade-offs – choice
o Benefits and costs
o What is desired most
The best known and often used example of this form of measuring is conjoint analysis
- Actual purchase data
o Counts
o Sales force reports
Stated intention-to-buy measures
Durables: e.g. cars
Non-durables: e.g. groceries
X-axis: probability of buying
Y-axis: conversion rate
So the data in the graph shows what
is actually bought.
The stated intention-to-buy is not a good preference measure since reality and predicted
behaviour are far apart from one another. For example, “definitely yes” should have a
conversion rate of 100%, while the graph clearly shows that this is not the case. Also, you
predict there to be no sales for the group “definitely not”, while there are some sales there.
Consumers are not on purpose untrue, the question is just too difficult to answer. A lot can
change over time – the graph shows overconfidence bias.
The conversion rate maps what people say and do; their actual behaviour.
Conjoint analysis
The measurement method conjoint analysis is more intuitive for consumers to answer. There
is more value in asking consumers to give trade-offs / choice tasks than allowing them to have
everything. Consumers are more experienced in balancing costs and benefits than in stating
ideal points. Ideal points are generally not feasible; consumers are not able to give their ideal
choice
Conjoint analysis is a survey-based research technique designed to force customers to make
trade-offs, thereby revealing their true preferences. In conjoint, products and services are
treated as combinations of features – benefits and costs. The procedure produces a
mathematical model of each customer’s “value system”; the utility function of each
consumer. The latter is very important, since this is the basis of segmentation (and so STP).
Keep in mind that there is no typical or general consumer!
Conjoint analysis aims to do two things really well, namely measuring
, Pagina |4
- willingness to pay: measure what individual consumers are willing to give up to obtain
certain product benefits – what they spend extra on certain attributes
- distribution of willingness to pay: measure how consumers differ in their willingness
to pay – how different is your population?
Knowing the distribution of the willingness to pay is more important than the average WTP.
This is because:
- consumers want what caters their needs; design the product so that it differs per
segment higher demand, higher price. The latter is made possible by the fact that
consumers have a higher evaluation of a product that fits their needs and it can be an
example of uniqueness no competition = positively valued
- cater the market no yet discovered by either you or your competitors; then there is
WTP that can be captured by you – you then have monopoly power
e.g. Tesla in the car market
Categories that are often used to perform conjoint analysis in are the markets of television,
smartphones and cars. Some examples of successful conjoint analysis applications are the
Courtyard Marriott (hotel), Caterpillar and over the counter (OTC) medication.
Conjoint analysis is typically applied with:
- opportunity identification – marketing definition and idea generation
- design – customer needs, positioning, segmentation, forecasting, engineering,
marketing mix product development
- testing – advertising and product testing, pre-test and pre-launch forecasting, test
marketing you know the product you are planning to make, now you need to know
the correct pricing, how to position, personal selling, etc.
- introduction – launch planning, tracking the launch
- life cycle management – market response analysis, competitive monitoring and
defence, innovation at maturity
There are different wants and needs in the different stages of the product life cycle;
preferences shift!
Conjoint analysis helps answering design stage questions like:
- What do our customers want?
- How do we position this product?
- Which segments should we cater to?
- Given product design, what will be our market share?
- How should we allocate the marketing mix?
Slides & Lecture Notes Market
Assessment
, Pagina |2
Week 1
A marketing strategy stands and falls with
segmentation – targeting – positioning. The
4Ps are used to either:
- Create value: product and price; the
first is more difficult to change
- Deliver value: promotion and place
(channels)
o Promotion: the change of
the fraction of consumers
that know you awareness
o Place: the market coverage
Another important question to ask oneself
is to what extent a company should invest
in either the attraction or the retention of costumers.
A response function can easily be represented in a graph.
For example:
Units sold is used here since revenues = price * units sold.
When one wants to know the response to a change in price, one
often sees a downward slope the higher the price, the less
units sold.
Task 1: What is the response? (response function)
Task 2: Decision-making – what is the optimal point?
e.g. find the optimal value of x (=price)
low price: low margins, high demand
high price: high margins, low demand
An outbound campaign means reaching out to consumers at a
certain cost.
The market response can be assessed by using surveys / empirical data, experiments and
opinions. Based on this market response, decisions can be made. This can either be the
practical implementation of how to make profit maximising decisions and what if scenarios
(simulation). The marginal benefit should be equal to the marginal cost.
Preferences
Preferences are the guiding principles for decision-making. There are different measures of
preferences possible. For example:
- Taste testing (e.g. foods and drinks)
- Sales per facing (in e.g. supermarket – shelf spacing)
- Sales
These examples are all examples of “revealed preferences” (=taking action). Measurements of
preferences can vary across a continuum, from stated preferences to revealed preferences:
- Intention to buy – many different companies often use this method
, Pagina |3
o Too hard a question for consumers / respondents
o Over-confident about the buying probability
- Self-reported importance weights
o Lack of discrimination, everything is important
You do not ask for trade-offs is this way; they want the best products for free
- Trade-offs – choice
o Benefits and costs
o What is desired most
The best known and often used example of this form of measuring is conjoint analysis
- Actual purchase data
o Counts
o Sales force reports
Stated intention-to-buy measures
Durables: e.g. cars
Non-durables: e.g. groceries
X-axis: probability of buying
Y-axis: conversion rate
So the data in the graph shows what
is actually bought.
The stated intention-to-buy is not a good preference measure since reality and predicted
behaviour are far apart from one another. For example, “definitely yes” should have a
conversion rate of 100%, while the graph clearly shows that this is not the case. Also, you
predict there to be no sales for the group “definitely not”, while there are some sales there.
Consumers are not on purpose untrue, the question is just too difficult to answer. A lot can
change over time – the graph shows overconfidence bias.
The conversion rate maps what people say and do; their actual behaviour.
Conjoint analysis
The measurement method conjoint analysis is more intuitive for consumers to answer. There
is more value in asking consumers to give trade-offs / choice tasks than allowing them to have
everything. Consumers are more experienced in balancing costs and benefits than in stating
ideal points. Ideal points are generally not feasible; consumers are not able to give their ideal
choice
Conjoint analysis is a survey-based research technique designed to force customers to make
trade-offs, thereby revealing their true preferences. In conjoint, products and services are
treated as combinations of features – benefits and costs. The procedure produces a
mathematical model of each customer’s “value system”; the utility function of each
consumer. The latter is very important, since this is the basis of segmentation (and so STP).
Keep in mind that there is no typical or general consumer!
Conjoint analysis aims to do two things really well, namely measuring
, Pagina |4
- willingness to pay: measure what individual consumers are willing to give up to obtain
certain product benefits – what they spend extra on certain attributes
- distribution of willingness to pay: measure how consumers differ in their willingness
to pay – how different is your population?
Knowing the distribution of the willingness to pay is more important than the average WTP.
This is because:
- consumers want what caters their needs; design the product so that it differs per
segment higher demand, higher price. The latter is made possible by the fact that
consumers have a higher evaluation of a product that fits their needs and it can be an
example of uniqueness no competition = positively valued
- cater the market no yet discovered by either you or your competitors; then there is
WTP that can be captured by you – you then have monopoly power
e.g. Tesla in the car market
Categories that are often used to perform conjoint analysis in are the markets of television,
smartphones and cars. Some examples of successful conjoint analysis applications are the
Courtyard Marriott (hotel), Caterpillar and over the counter (OTC) medication.
Conjoint analysis is typically applied with:
- opportunity identification – marketing definition and idea generation
- design – customer needs, positioning, segmentation, forecasting, engineering,
marketing mix product development
- testing – advertising and product testing, pre-test and pre-launch forecasting, test
marketing you know the product you are planning to make, now you need to know
the correct pricing, how to position, personal selling, etc.
- introduction – launch planning, tracking the launch
- life cycle management – market response analysis, competitive monitoring and
defence, innovation at maturity
There are different wants and needs in the different stages of the product life cycle;
preferences shift!
Conjoint analysis helps answering design stage questions like:
- What do our customers want?
- How do we position this product?
- Which segments should we cater to?
- Given product design, what will be our market share?
- How should we allocate the marketing mix?
