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ESTRATTO DOCUMENTO

Customers have to participate in the value generation to let us know what motivates them:

touch points make it possible. The idea is to integrate channels to be consistent in delivering

the experience.

Why multichannel? There are plenty of channels to reach customers:

- Mobile: 1,9 B smartphone users

- Retail

- Internet: 3,2 B internet users; e-commerce penetration in China 10,9% on FMCG

- TV

- Radio: coverage of broadband in China 60% ca.

- Social Networks: 1,4 B on Facebook

- Out-of-home

To sum up, in order to succeed a company must be able to:

1) detect intimate customer needs

2) develop a suited customer experience that is necessary multichannel

3) focus on customer loyalty: to be sure that the effort is paid back by the customer.

The better we treat people, the more we get back from people: it is important to implement

such a culture in the company: technically, financially and culturally. It is not just about

understanding the change but implementing it. 6

THE SCENARIO AND CUSTOMER BEHAVIOR

(See Slides)

The general idea standing behind is the ‘Pareto in whatever social set a small part of it

Law’:

generates the largest part of the phenomenon observed. This idea generates, as an example,

E.g. the 20% of the products generates the 80% of the turnover.

blockbusters.

Example:

Picture yourself in a pizza house. There are 8 types of pizza

available. What’s your choice? The majority of us choose

Margherita and the ketchup and fries pizza was chosen by a

small percentage of people. The general implication is to cut the

pizza with the lowest percentage of customers if the customer

is not a crucial one (e.g. ketchup and fries).

Instead, if we had to say what is our favourite pizza, generally

speaking and not choosing in a list, just a small part of

customers that chose Margherita would choose another pizza,

not in the menu.

Generally speaking, sometimes we choose product because we like them, sometimes because

there is nothing better in the market.

[With the possibility of customize products (e.g. pizza house without a menu). For example, in

the publishing industry, if the topic proposed has a very small market (potential readers: 100

people in Italy) and we are the publisher we would not publish it. Costs (promotion, publishing

– min 5000 copies, distribution; total amount = 30000€) are not worth the effort. B.E.P. =

300€/copy so no copy would be sold for that price. As a result, nobody is going to launch the

book. But in a digital world, with the possibility to send a pdf and put it on a platform

(advertisement: keywords on google [advertiser asks google to advertise in case the users click

that word, the advertiser pay google depending on the number of times the advertisement has

cost-per-click model];

been viewed: in this way costs of advertisement are variable – 0,2€/click,

the probability that the one who clicked will buy is 10% - conversion rate. Acquis cost = cost-

per-click/conversion rate 10 click to get one purchase = 2€. Live expenses = 100€ flat. If the

à

price is 10€ it is worth to launch the book because the structure of the company has changed.]

A part of people who chose Margherita decided to switch to another pizza (in case of no menu

and free choice) because Margherita is a comfortable pizza: maybe it’s not the favourite but

something we can accept. There are some mainstream tastes. If the is no menu and free choice,

long tail effect.

there are plenty of new little products collecting market share: Instead of a big

market share for a small amount of products, there are a lot

of different products gaining market share (e.g. iTunes): the

long tail effect goes against the ‘Pareto Law’ so it is not true

that 20% of the product make the 80% of the turnover.

nowadays we are switching from

Pareto law is a social law:

product to services so maybe the platform is standard but we

can find a lot of variety and so there is the possibility for

In contemporary

everyone to find what he better tastes.

world, with a lot of choices, it is not true anymore the Pareto

Law that stands behind.

If there are plenty of fixed costs to cover, the Pareto Law is still valid: since there is a huge

investment behind the product, the product needs to have a big market in order to pay them

Services follow a different model: standardization

back. Very often special products are in loss. 7

of underline process and high customization in the front end. As the economy moves from

product to services the long tail effect arrives. competition:

Another reason why the long tail effect arrives is very high competition means

infinite choice for customers. Every time there is an unsatisfied need, there will be someone

producing it. Quality (technical reason) is a very weak competitive advantage that will last for

a very short time (e.g. better smartphones every 3 months). The window to pay back the

investment is short so it is necessary to be aggressive on price and in marketing: customer

service – complementary, since the product is not enough (e.g. maintenance, free assistance) to

make the product less imitable. Technical features are easily imitable, services less. You create

competitive advantages on intangibles (e.g. it makes you laugh, it makes you cry, it’s

fashionable, …). PRODUCT SERVICE INTANGIBLES

à à

Intangibles, to be effective, must be one to one. It’s about

understanding what are the things that make you laugh (that are

An intimacy with

specific of every single person, not generally valid).

the customer has to be established.

Competition and long tail are conceptually close to each other.

à

It is necessary to be able to engage customers to work conceptually

as the pizza house with the freedom of choice.

Implications of this situations:

Demand elasticity:

- how many customers am I going to

gain if I decrease the price.

P1Q1 area = revenues

Q2 is going to buy the product since his willingness to pay is

P2: setting a price, very few people are willing to pay no more

than that and a plenty of people are willing to pay more.

Working on service and intangibles it is possible to convince

Q1 to pay more than P1 by creating customer experience:

price discrimination.

In reality, nowadays, we accept to pay two different amount of

money (price discrimination). If we are able to set the price

equal to the willingness to pay of each customer (different prices) the

revenues are equal to the whole area below the curve. In this way it is

possible to use the higher revenues to extend the market to customers

with a lower willingness to pay – on the right of Q1.

E.g. low cost airlines use this principle.

If you are on the long tail, probably you are willing to pay more.

Innovative Business Model

- Freemium: propose two different version of the same item; the simplest is for free, for

the other one you have to pay. You pay only for extra features (e.g. diminished

“disturbs”)

- Long tail

- Pay-what-you-want: buyer pay the desire amount for a given commodity.

Fee-in Free-out: if you feel the urgency you pay for it, otherwise you will have it for free.

- It works by charging the first client a fee for a service, while offering that service free of

charge to subsequent clients

. 8

- Tiered service: allow users to select from a small set of tiers at progressively increasing

price points to receive the product or products best suited to their needs.

The key is to develop intimacy, and to do that we have to keep in mind that it is unlikely to

conversation.

create intimacy with someone without establishing a

Conversation occurs if it goes in both directions: from the company to the customer and vice

to establish an intimacy we must have a dialogue with the customer.

versa. The main idea is:

THE MULTICHANNEL FRAMEWORK

To establish a conversation, it is necessary first of all to find a target. Social networks seem to

be the best way to establish a conversation.

Revolution of mobile: mobile users has increased exponentially in the last years. Since mobile

is increasing, also social medias are:

the long tail effect creates a competitive advantage.

Wikipedia is an example of how You know

you can find anything on Wikipedia. Same for amazon and Alibaba. So you look there for

everything knowing you can find everything.

Social Networks are very successful because they both give you information and collect

information. Nowadays people is used to generate content and companies must be careful to

this content because establishing a dialogue is about changing contents not just giving them.

The quantity of information generated nowadays is bigger than the quantity that can be

processed worldwide. The higher amount of information has been generated in the last years;

that is the kind of information we have to take into consideration. That means the competitive

set for the attention is huge: your own customer are your competitors. When there was just

television it was easy: with a lot of money you buy some space and everybody look at your

9

message; nowadays there are countless channels of communication (it is possible not to reach

the population), customers may use more than one device at a time so their attention is equal

to 0. It is difficult to communicate with people: it’s about convincing people that what you are

saying is interesting. How? Through intimacy.

Creating value for customers

Metaphor of the ice-berg:

- Emerged part: it is possible to see from far away and anyone can see. Expressed

PRODUCT:

preferences of the customers, tangible and objective elements in the offer.

something than can be put on a shelf, either you buy it or not. Technical features.

- Just below the water: cannot be seen from far away but it is possible to see it by

approaching the ice-berg. Tangible and intangible elements relatively objectively

related to the way the offer is “taken” to the customer. Specific preferences of the

customer that emerges only if you talk to the customer. Through interactions, these

SERVICE: something activated, it derives from interaction.

characteristics are found.

Relationship with customer.

- Deepest part and biggest one: cannot be seen even getting closer. Cannot be express by

market research and interactions. It qualifies the potential impact of the offer for the

EXPERIENCE:

customer. Intimate and personal impact of the offer on the customer.

having an impact on the customer. Impact on the existence of the customer.

Example: a guitar

- Product – technical characteristics: wood, pick-up, weight, precision, …

- Service: sales process, after sales, picks, …

- Experience: iconic association e.g. Jimi Hendrix

Example: a football team

- Product: the objective is to win, results

- Service: quality of the show

- Experience: e.g. father is a fan, sense of belonging

Value: a checklist of references

How can we create value for customer following this framework? functional value:

In order to create value for the customer, first of all think about the the value

of the features of the product, what does the product do? How does it work? 90% of the

companies stop here: the want to create a good product. The functional value represents the

emerged part of the ice-berg. conditional value:

The next step is to create value also with the does the offer arrive at the right

time? (e.g. an umbrella when it is rainy has more value); the ability to be at right place at the

right time with the right product. To understand the conditional value, it is necessary to get

close to the customer and know him. cognitive value,

The third important leverage is the the value of information and content

provided to the customer. Telling a story to understand the product may create value.

Information exchange? Does the customer understand something better? E.g. Lamborghini is

more expensive than Ferrari because there is a known difference in value. To generate cognitive

value, you have to know your customer and generate dialogue.

The conditional value and the cognitive value represent the part of the ice-berg just below the

water.

The last two values are about being very intimate with the customer. 10

Emotional value: how the product makes you feel with yourself. It is a very powerful way to

understand the intent of your offer. Which kind of impact you want to have on customers. How

does my customer feel along the purchase process? What is the impact of the offer?

Social value: how you want to make customer feels with others. Extremely powerful value

driver. What is the impact of the purchase on the customers’ way to interact with others?

The emotional and the social value are the deepest part of the ice-berg.

Example:

Two similar restaurants, one with the park full, the other one with the empty park: if there are

more cars it means there are more people and so that it is better. But probably it is crowded

because the first one arrived and the other as a consequence, not because the restaurant is

better. But if you are on a hurry you choose the empty one: if the food is good, the other may be

better (benefit = 0), if the food is bad it is your fault because you went against the mass.

Very often, especially in B2B there is more inertia compare do B2C.

Social value = Switching costs= Inertia.

The combination of the five values create the total value generated by the company for the

customer.

Emotional and social value are not just about fashion, …, but are instead present in every

purchase decision even if sometimes the supplier is not aware of this. If you don’t picture the

impact on the customer it is difficult to fully satisfy him. Even if performances of the product

are low, but it creates social and emotional value the relationship does not change. It is a strong

relationship. We are lazy so we won’t change it if nothing extraordinary happens. It is important

to establish this kind of relationship with customers.

Keep in mind that impact is something understandable only thorough intimacy with the

customer. It is difficult to convince the customer only with the product. A conversation to built

intimacy it is necessary. Thorough a set of channels, it is possible to establish intimacy with the

The ability to send content and the ability of listening should be

customer (TV, press, …).

combined to gain intimacy.

By collecting big data, it is possible the listening. Data has then to be interpret to understand

the customer. LISTENING BIG DATA INTERPRET

à à 11

We deliver value along different channels to stimulate all the different value drivers to establish

It is important to manage the different channels in

the intimacy to make our product credible.

an integrated way to create value in all its shapes. Channels are used in different circumstances

by different customers and they have to be integrated.

And it depends on the kind of target: the idea is to identify the target and develop a multichannel

architecture.

Segment basically are developed around the idea of functional value (e.g. people between 24

and 30 have similar tastes). We should make segmentation with emotional and social value but

this way the segment is made by one customer and the single customer belong to different

segment in different moments of his life. (e.g. totally different behaviours according to the

situation: supermarket to eat alone, with friends, in a hurry, with time, …). 12

METHODOLOGIES OF SEGMENTATION

Segmentation consists in grouping customers according to different characteristics. The people

in one segment should be similar.

In reality we have to deal with complicated situations: customers’ needs and interests could

largely differ, which can also depend on a lot of other factors. Even the same person in different

situation can have different needs and interests.

Variables we have to consider in segmentation are a lot:

- People are different in the (e.g. if the person is a boy or a girl).

purchase process

- People are different according to factors: region, size, population density,

geographic

climate, …

- People are different according to factors: gender, age, race, family status,

demographic

education, occupation, income, …

- People are different according to factors: interests, activities, personality,

psychographic

values, attitudes, lifestyles, …

- People are different according to factors: benefit sought, purchase occasion,

behavioural

usage rate, purchase pattern, loyalty level, …

Which are the variables to choose? Which one should we combine?

Why to segment the market?

Segmentation was before targeting and

positioning. We segment to create a product that

best suits customer’s needs. Positioning consists

in creating products with different

characteristics compared to competitors.

Starting from a deep understanding of the

customer (segmentation) it can be used not only

for product creation but for branding and

communication as well. We have to

communicate effectively with the customers in

order to be successful. But communication is not

everything: there is also the distribution (deliver

customer value) that can be another purpose of

segmentation. There are many different ways to

communicate with the customers and deliver

the products (multichannel).

SEGMENTATION PROCESS

First of all, define segmentation objectives: develop new product, identify communication or

distribution plans, …

According to objectives, different data are needed (e.g. distribution: look at preferences for

distribution channels). Then we get the data and module them to get some results: variables

should be consistent with the objectives. (Database: a lot of data are already available

nowadays). Now we have an initial source for segmentation. If the database does not provide

the information we need, it is necessary to collect them through market research.

With all the data needed, now it is possible to identify what could be the segment of the

customer that data is suggesting, with the help of a software. Eventually it is necessary to

identify segment and get to know them. 13

To start segmentation, we need quantitative data. In some cases, we do not know where to start

and looking at the data we already have we think they are not providing the information

needed. In some cases, it is not immediately clear what we have to collect. Numbers carry

meaning.

In order to develop questionnaire, usually first of all it is necessary to get to know the

qualitative research first.

customers: It is not necessary to address all the customers in order to

start understanding: take first of all a sample to start understanding the customers. These kind

primary data.

od data are Can be collected also indirectly, for example from report already done

in the past, but these not always fit our needs; it is possible to combine the two of them.

Once we have a good view, it is possible to make a list of the variables we want to collect; and

quantitative

then we can develop the questionnaire according to the list and start collecting

data. It is not necessary to cover every single customer but a big number in order to understand.

Once the sample has been chose, we have to try to avoid biases (e.g. only boys or girls can be

biases, easily avoidable).

Segmentation objectives

Segmentation could have many different operational objectives, for example:

- To develop new product service

- To raise brand or new product awareness

- To facilitate new product acceptance

- To improve current process 14

- To identify customer relationship management programs

- …

Such objectives have to be properly defined:

- they must be consistent with the business needs at hand

- they guide the process to be followed

To recap, variables to be considered are: Sources:

- geographic factor - survey

- demographic factor - experiments (large scale)

- physiographic factor - Data warehouse

- behavioural factor - Big data

- …

K-Means Cluster Analysis

Clustering object into homogeneous groups based on variables with measurement.

interval

(E.g. sometimes people do not want to say the age, the ideal would be to ask in which range you

are). Numbers do not always have a meaning; we have ordinal (e.g. range-age) or categorical

(e.g. gender) or interval (e.g. exact age) variables.

Then the right kind of method would be choosing: K-Means can only use interval variables. If

we want to put together different variables, they should be standardized in order to be

comparable with each other. Interval variables with different scales should be standardized as

well.

For example: actual age/height/weight/income. Likert scale survey data – considered ordinal

by nature but we treat them as interval (e.g. in a range from 1 to 5 how much did you like – it is

used to ask opinions), ticket scale, annual spending, minutes spent online, …

K-Means classifies objects by computing the Euclidean distance among the objects.

The number of clusters has to be imposed before computation: it is a restriction but we can

perform an analysis with 1,2,3, … clusters and then compare the different solution and ask the

software which one is statistically the best; several K-Means cluster analysis could be

performed to choose the best solution.

K-means is faster and easy to perform on a large data-set, it cannot classify subjects with

missing values: it is important the quality of the data set and avoid missing values.

Many times we can rely on statistic but sometimes it does not work because of subjectivity and

instinct.

It is helpful to give a name to the segment and describe them, to better identify it.

Example: 15

Questionnaire: it gave an idea of the physiographic characteristic of customers

Cluster interpretation – the result:

Segment profiling:

Then it is important to understand how and who the customers are. Who are the customers in

each cluster? Describe the characteristics of the clusters:

More importantly, are the clusters different in terms of he marketing outcome that you are

interested in? 16

Hierarchical Cluster Analysis

Hierarchical Cluster analysis could use diverse types of variables: interval, normal and ordinal.

However, it is not advisable to mix different types of variables in the same analysis. For

example, beside interval variables: gender, education level, model of product purchased, touch-

point used, …

It simultaneously computes results from 1 to N clusters for sample size N. the number of

clusters is decided later. It is more difficult to calculate for large dataset. This method takes

longer and it is more difficult.

Neither of K-Means and Hierarchical cluster analysis ensures the “meaningfulness” of the

resulted clusters.

Statistically it suggests the best solution but it does not guarantee so it is necessary to go ahead

with the segment profiling.

Latent Class Segmentation

Latent class segmentation computes with probability, therefore the most significant superiority

is that it can deal with different types of variables (internal, nominal, ordinal) simultaneously;

it can also deal with missing values.

It has dependent variables, therefore ensures the meaningfulness of the clustering.

It can include (active or negative) covariates. Active covariates would influence the clustering;

inactive covariates are mainly for profiling.

Fitness indicators are available to suggest the number of clusters which explains the data the

best. 17

Segment strategy

After collecting and analysing the data, we have to develop

segment strategy. After identifying and describing the segment,

now, what are the marketing actions towards these segments?

One of the objectives of segmentation is product development.

(E.g. online bookstore: three different segments according

usage and purchase frequency – different involvement in the

business that have to be treated differently otherwise it would

not be successful).

It is not possible to use the same strategy for all the groups. It is

necessary to define an objective for each group, cluster by

cluster.

DEMO WITH MUSIC PREFERENCE

An institution has conducted a large-scale survey among young people on many aspects of their

lives, such as:

- Self perception - Preferences in music, movie, etc.

- Likes and fears - Some demographic information

- And so on

- Lifestyle

Now, suppose, you work for a company in the music industry and you obtained the data of this

survey from the institution. How could this data be somehow useful to you?

Music preference of young people:

- I enjoy listening to music (Likert scale, 1 Not at all – 5 Very much)

- I prefer: slow or fast songs (1 Slow – 5 Fast)

- I like the following music genres (1 Not at all – 5 Very much)

Dance, Rock n Roll

Rock

o o

o Alternative

disco, funk o

Metal, hard

o Latin

o

Folk rock

o Techno,

o

Punk

Country o

o Trance

Hip hop, rap

o

Classical

o Opera

o

Reggae, Ska

o

Musicals

o Swing, Jazz

o

Pop

o

A total personalization would be knowing exactly the likes and dislikes of each person,

Ø and make recommendation accordingly – an approach quite infeasible even for a

company such as Spotify.

A one-size fits all strategy surely will make many mistakes (17 genres asked in the

Ø survey!). 18

The best feasible action is, knowing what are the similar interests that customers may

Ø have, therefore to increase the chance of making a good guess and recommending

something that a customer actually likes.

Choose the variables:

- Type of measurement

K-means/K-median: interval

o Hierarchical: all types of measurement, but not to be mixed

o LCC: all types of measurement, can be mixed

o

- Meaning: what are the consumer characteristics, on which the segmentation is based?

K-means/Hierarchical: meaning of the variables should be “comparable

o meaning”

LCC: any variables can be combined, roles in segmentation are defined

o

If the two groups are different, there is the statistical meaning to do segmentation. The it is

necessary di define the size of the cluster as well.

a new variable is created to record the cluster that each subject is being assigned to. To profile

the segment is the next step (excel is enough): 19

Output:

It is not so easy to describe such a result because there are too many variables and information:

perform a factor analysis is the solution.

Pre-clustering - segments based on a large number of variables are difficult to interpret (among

other potential problems). In this situation, you may want to reduce the dimension of the

segmenting variables before performing the cluster analysis > Factor Analysis.

A bank collected 11 key variables which its customers consider important for choosing and

interacting with a bank:

- Monthly account fee - Availability of parking

- Charge for withdrawal and deposits - Operation hours

- Loan interest rate - Friendliness of staff

- Distance to home - Assistance via telephone

- Distance to other frequently visited - Waiting time

places

To try to make the picture clearer: identify factors through the factor analysis, looking at similar

things (e.g. the first three variables have to do with cost)

Now we will proceed with these three variables: in this way it will be easier. It does not change

results, just make them clearer. 20

Output (the higher the number – in red the stronger the association):

Giving a name, makes it easier to understand it.

Five new variables are added: five “factor scores” are calculated for each subject, to represent

their answers to all the variables on which the factor analysis is based. Note that, factor scores

are standardized, therefore not in the same measurement scale as the original variables.

Clustering again: re-perform the cluster analysis using the five factors scores instead of 17

variables.

Unlike FA, K-means cluster analysis does not indicate an “optimal” solution; in fact, the number

of clusters needs to be pre-defined. Therefore, unless you have strong hypothesis or other

specific purpose, you can perform a series of cluster analysis with different cluster-number

solutions. Then you compare them and choose the most suitable solution.

Criteria for choosing the solution:

- Distinctiveness among the clusters

- Meaningful clusters 21

Cluster profiling: Who are the customers?

For your music business, what strategies you could deploy with the knowledge of your

customers discovered through segmentation?

It is possible to decide weather to focus on every segment or not. 22

PRICING

(See Slides)

is a cost based pricing approach in which after defining the cost of the product we

Mark-up

apply a mark-up.

- Pros of mark-up pricing: apparently easy.

- Cons of mark-up pricing: it does not consider competition and the customer.

The three C model is the main model considered in pricing:

- Customer: position in the mind of the customer matters, if the product is better it should

cost more;

- Cost: the price must be higher than the cost to have profits;

- Competitors: value perceived by the customer is expressed through the price.

Then different models have been developed:

- Going-Rate pricing: based on the assumption that the price index (


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DETTAGLI
Corso di laurea: Corso di laurea in ingegneria gestionale (CREMONA - MILANO)
SSD:
A.A.: 2018-2019

I contenuti di questa pagina costituiscono rielaborazioni personali del Publisher franciig_ di informazioni apprese con la frequenza delle lezioni di Multichannel Customer Strategy e studio autonomo di eventuali libri di riferimento in preparazione dell'esame finale o della tesi. Non devono intendersi come materiale ufficiale dell'università Politecnico di Milano - Polimi o del prof Lamberti Lucio.

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