Contact rate for word of mouth

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"Michael Bean"
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Posts: 22
Joined: Fri Mar 29, 2002 3:39 am

Contact rate for word of mouth

Post by "Michael Bean" »

Hello Vittorio,

To calibrate a word-of-mouth model, I typically break the word-of-mouth sales
into real world pieces and then calibrate the pieces.

In word of mouth models Ive built, Ive separated sales into two categories:
word-of-mouth sales, and repurchases (by customers who are in the installed
base). Word-of-mouth sales is an outflow from Potential Customers and an inflow
to the Installed Base.

The formula I typically use for word-of-mouth sales is:

Word of mouth sales = Installed Base Customer x Number of Contacts Per Month x
Fraction of Potential Customers x Probability of Adopting if Contacted

The formula assumes that each Installed Base Customer interacts with a number of
other people each month (number of contacts per month). Some of those people
have already purchased the product and some are encountering it for the first
time so, for word of mouth sales, were only interested in the fraction of the
population that might buy the product for the first time (fraction of potential
customers). These potential customers that encounter the product through
interacting with a customer have a chance of being convinced to buy the product
through each interaction with a customer who is in the installed base
(probability of adopting if contacted).

Probability of Adopting if Contacts should be > 0 and <= 1.
Fraction of Potential Customers = Potential Customers / (Potential Customers +
Installed Base)

Anyone who would like a simple but complete complete copy of a word-of-mouth
model that uses this formula, please send me an email and Ill be happy to send
you a copy.

Best regards, Michael
______________________________________
Forio Business Simulations

Michael Bean
mbean@forio.com
John Sterman
Senior Member
Posts: 117
Joined: Fri Mar 29, 2002 3:39 am

Contact rate for word of mouth

Post by John Sterman »

Following Mike Beans nice reply on word of mouth models, these
models are treated in depth in Chapter 9 of Business Dynamics. For
an excellent application, see Urban, G., J. Hauser, and J. Roberts
(1990) Prelaunch forecasting of new automobiles, Management Science
36, 401-421. Also chapter 17 in Richardson, G. (ed.) (1996) Modeling
for Management, Vol. 1. Aldershot, UK: Dartmouth Publishing Co.

John Sterman
From: John Sterman <jsterman@MIT.EDU>
=?iso-8859-1?Q?Jean-Jacques_Laub
Junior Member
Posts: 16
Joined: Fri Mar 29, 2002 3:39 am

Contact rate for word of mouth

Post by =?iso-8859-1?Q?Jean-Jacques_Laub »

Hi Vittorio



I feel not being and by far the more qualified to give you an answer, having
never used a model with a word of mouth hypothesis.



I have the same kind of problem then you.



I am working currently on a price setting problem, and one of the hypotheses
included in the layered diagram representing how the hypotheses are working
together is the famous word of mouth.



The word of mouth is important in our service activity (short term rent a
truck, van and car).

In the layered diagram it is driving the behaviour of many other hypotheses.



The problem is that the difficulty to calculate it is as high as its effect.



I have seen many models, mainly in Stermans Business dynamic book and
others and the way the word of mouth is calculated does not satisfy me. In
fact it is in my model the part that is the more ambiguous.



I have started converting the diagram in a model, and worked on the first
hypotheses and left aside the word of mouth that I will integrate later on.



This is the method I will try to follow to resolve the word of mouth
problematic, providing that I may change it depending on my further
experiences.



First let us criticize the usually found in text books formula that Michael
Bean has sent in his mail.



Word of mouth sales = Installed Base Customer x Number of Contacts Per Month
x
Fraction of Potential Customers x Probability of Adopting if Contacted



The number of contacts per month does not specify if the contacts have the
same effect.

For instance you can have revolving contacts, and occasional contacts.

A revolving contact is by example the contact with your wife or children or
colleagues at work etc.

The first contact with a revolving contact will have more effects then the
second or the third.

There are a lot of revolving contacts.

You can always say that it is an average and you have the probability of
adopting if contacted that will make the difference.

Imagine by example that the base of customers is relatively stable and the
only interesting contacts are the non revolving, because the revolving have
already been contacted.

In that case, logically there is very little word of mouth, depending only
on the revolving customers. Then the word of mouth is depending too on the
customer base being instable.



Another problem comes from the needs of the person being contacted. It the
person being contacted has the need only one year afterward, he may have
forgotten the contact.



All this to say that the number of contacts per period has an influence, but
it needs some other information.



I think that it is easier to consider the product number of contacts x
probability of adopting if contacted that makes sense.



The difficulty is to calculate the parameters: number of contacts and
efficiency.



But the worse problem comes from the fact that the probability of adopting
is influenced by the world of mouth of the competitors.

Your word of mouth is influenced by your own word of mouth plus the word of
mouth of competitors.

The result is that the efficiency can vary considerably with the time.

It can be negative too.

One can argue that a model can only consider endogenous factors. But the
objective is generally to find policies and is it worth considering an
endogenous factor that can vary suddenly and change the results of the
policy?



Other problems can be considered: for instance the fact that some people
contacted can be occasional or regular buyers. It will make a difference for
the efficiency. Other factors can be considered depending on the kind of
product.



Whatever the problem, word of mouth is worth considering it.



I will follow several steps.



1. Calculate the impact of word of mouth on the goal of the model.

What is its influence? Is it worth investing money and time and how much, to

add word of mouth to the model?



For instance, in my model, I am interested in price setting. Maybe whatever
the word of mouth effect, it may have no influence on the price setting or
the influence may be small.

If I was interested in a more general model whose goal is to maximize the
result on a long range period, then word of mouth should be considered.



2. Once I have an idea of the influence of the word of mouth, I will have a
close look at reality.

Going down to earth, talking to revolving or not revolving customers or
anybody linked to the subject, is a paramount way to understand how things
are working, get a feel of reality and is often better than tons of data.



3. After this close inspection of live data, I will decide if it is worth
estimating by some ways the effect of word of mouth, independently from any
other factors.

I want simply to know if there is an influence and how much.

To do this, I can make qualitative in depth questioning or quantitative
questioning.

I can for instance, ask every new customer in my agencies, why he decided to
choose our Society or choose some customers and talk with them a longer
time.



4. If the third step is positive, I will have proved that there is word of
mouth influence.

But I still do not know how. I personally think that for my case, it is
depending on the basis of

customers and potential customers multiplied by a factor. I can estimate the
factor if I know the customers the potential customers and the effect. One
of the factors that influence the word of mouth is the quality of the
product, relatively to the competitors.

I will have then to establish a close survey of the quality of our product
compared to the competition.



I have then the formula:

Word of mouth per period =

Installed Base Customer x
Fraction of Potential Customers x Quality of our product compared to the
competition x

a constant factor.



The constant factor can be evaluated by dividing the word of mouth per
period estimated by survey by the other calculated variables.



This is of course a lot of work and it is necessary to prove its usefulness.



After all I may simply leave the word of mouth effect for the next model.
Commercial policy.



Regards.



J.J. Laublé, Allocar, rent a car company.
From: =?iso-8859-1?Q?Jean-Jacques_Laubl=E9?= <JEAN-JACQUES.LAUBLE@WANADOO.FR>

Strasbourg France
"Michael Bean"
Member
Posts: 22
Joined: Fri Mar 29, 2002 3:39 am

Contact rate for word of mouth

Post by "Michael Bean" »

Jean-Jacques Laublé makes a good point about the traditional word-of-mouth
product diffusion model not working in quite the same way for services such as
telephone service contracts, internet service subscriptions, or rental cars.

There are (at least) two reasons why the *service* word-of-mouth model is
different than the *product* word-of-mouth model:

1) the relationship with the customer is ongoing, so revenue is calculated from
the installed base stock multiplied by the revenue per customer per year,
instead of the word-of-mouth sales flow and the replacement sales flow.

2) because services are worthless if not used by a specific date, they must be
replenished. There is no replacing an old service for a new service because once
a service expires, it ceases to exist. Therefore there are no replacement sales
for services.

I believe the basic word-of-mouth adoption for service is essentially the same
and is based on subscribers in the installed base interacting with potential
customers. The difference for services is, once these customers adopt, they
continue to pay based on the average life of a subscription or service contract.
And after customers end their subscription, they usually no longer generate new
word-of-mouth sales from interactions with potential customers.

Heres a comparison of the product diffusion revenue and service diffusion
revenue calculations:

The basic revenue equation for *product* diffusion is:
Total Revenue = (Word-Of-Mouth Sales x Price) + (Replacement Sales x Price)

where Replacement Sales = Installed Base / Average Product Replacement Time

The basic revenue equation for *service* diffusion is:
Total Revenue = Subscription Revenue Per Period x Installed Base of Subscribers

For services, Total Revenue goes down when customers exit the installed base by
terminating their long-term contracts or subscriptions. This is somewhat similar
to Replacement Sales declining because customers are no longer using the
product.

Of course, for both services and products, a model based on a real example is
likely to be considerably more sophisticated than these simple, generic
examples.

Best regards, Michael
______________________________________
Forio Business Simulations

Michael Bean
mbean@forio.com
Paulo Goncalves
Junior Member
Posts: 2
Joined: Fri Mar 29, 2002 3:39 am

Contact rate for word of mouth

Post by Paulo Goncalves »

Just to add to the number of references that have been sent on modeling and
calibrating WOM, a colleague at Yale is doing some interesting work in the
area. The link to her page and her working papers is
http://www.som.yale.edu/faculty/dm324/papers.asp The titles of her working
papers are listed below.

<soc_networks.htm>The Influence of Social Networks on the Effectiveness of
Promotional Strategies" (.pdf) Dina Mayzlin, July 17, 2002

<wom2.htm>Using Online Conversations to Study Word of Mouth Communication
(.pdf), David Godes and Dina Mayzlin, August 2003

<PromoChat2.htm>Promotional Chat on the Internet (.pdf) Dina Mayzlin, June
28, 2003

<draft10_5.htm>The Effect of Word of Mouth Online: Online Book Reviews
(.pdf) Judith Chevalier and Dina Mayzlin, Oct 5, 2003

Paulo Goncalves
paulog@miami.edu
=?iso-8859-1?Q?Jean-Jacques_Laub
Junior Member
Posts: 16
Joined: Fri Mar 29, 2002 3:39 am

Contact rate for word of mouth

Post by =?iso-8859-1?Q?Jean-Jacques_Laub »

Hi everybody.



Mike Bean, is right when he says that a model based on a real example is
much more complicated then those found in text books.



He is for instance considering the telephone service contracts and rent a
car service.

But in the rent a car service, there is great difference in a short term
rental service and

in long term service which is more similar to the telephone service
contracts.



In a short term rental service as in a hotel of a restaurant, the customer
has generally no contract and may change his suppliers very easily, or even
has at the same time different suppliers for the same service, generally for
a reason of disposability.



So the behaviour of customers is very different in these two kinds of
service.



1. The customers can change easily their suppliers.



2. There is often a problem of short term capacity.



3. The impossibility to assume the service for a problem of capacity will
have a very different



cost if it concerns a revolving customer or an occasional one because
the revolving



customer may choose to switch durably to another supplier.



4. This very lack of capacity will not only have an effect on the sales but
on the word of mouth, because the ability to deliver a service is an
important part of the quality of service.



Arif pointed out the capacity problem and its relation with the flow from
potential to customers, but it has to an effect on the word of mouth.



In our business the capacity problem is critical and has always been
considered by customers as the more important attribute of the service
quality.



Regards.



J.J. Laublé, Allocar, rent a car company

Strasbourg France
From: =?iso-8859-1?Q?Jean-Jacques_Laubl=E9?= <JEAN-JACQUES.LAUBLE@WANADOO.FR>
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