Why Conjoint?

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來自 University of Virginia 的課程

Customer Value in Pricing Strategy

92 個評分

University of Virginia

Customer Value in Pricing Strategy

92 個評分

課程 2（共 4 門，Specialization Pricing Strategy Optimization）

The traditional approach to pricing based on costs works to pay the bills, but it leaves revenue on the table. You can, in fact, price your products in a way that increases sales--if you know what your customers are willing to pay and can leverage psychology to create better deal and discount plans. In this course, we'll show you how to price a product based on how your customers value it and the psychology behind their purchase decisions. Led by Darden faculty and Boston Consulting Group global pricing experts, this course provides an in-depth understanding of value-based pricing and how to use it to capture more revenue. By the end of this course, you'll be able to... -- Apply knowledge of customer value to price products -- Leverage core value-based pricing techniques to inform pricing decisions -- Measure customer willingness to pay using models (surveys, conjoint analysis, other data) -- Use knowledge of consumer psychology to set prices beneficial to both consumers and sellers

從本節課中

Measuring Customer Preferences

As you learned in Week 1, understanding customer willingness to pay (WTP) is critical for effective pricing. This week, we'll show you two ways to measure willingness to pay: surveys and conjoint analysis. You'll see how one company, Adios Junk Mail, used surveys to better understand WTP. Conjoint is a terrific tool, and we'll walk you through how it's used to determine product preferences and prices. You'll finish the week with a solid understanding of how to measure customer preferences and use this information in your pricing strategy.

Conjoint Analysis Applications4:28

Why Conjoint?4:21

Conjoint Analysis: Steps 1-38:01

Conjoint Analysis: Step 4 and Product Preferences7:24

Attribute Trade-offs2:45

Attribute Importances4:03

Conjoint Analysis: Willingness to Pay5:38

Conjoint Analysis: Other Ways to Interpret Data3:56

Conjoint Analysis: Propensity Modeling7:58

與講師見面

Jean Manuel Izaret
Senior Partner and Managing Director, Leader of BCG’s Global Pricing Practice
Thomas Kohler
Associate Director, Pricing
Marketing, Sales & Pricing Practice
Ronald T. Wilcox
NewMarket Corporation Professor of Business Administration & Senior Associate Dean for Degree Programs
Marketing

Let's remind ourselves, why we're doing a conjoint analysis?

We're doing a conjoint analysis because asking people questions about preferences

often leads to unenlightening answers.

For example, what load would you like to pay on your mutual fund?

What annual fee would you like?

I bet you know, don't you?

Would you like online access for your fund?

Of course, you would.

People want everything and they want it for free!

They want to pay zero load.

They want to pay zero management fee and of course they want all the features.

But here's the basic problem, you can't give that to them

if you actually want to make money in these markets.

You can't give them all the best attributes and charge them little or

nothing for them.

So that's where conjoint analysis really comes in.

Because as a business person you are charged with increase in profits.

And to do that you have to provide cost effective products to the market.

Cost effective in the sense that people like them.

But, of course, you can spend tons of money and

create products that people just really love and lose a lot of money doing it.

You have to provide cost effect to products that people really like and

the first step in that process is to really understand what are the trade

offs people are willing to make.

And in so doing, you find out this is really important to them, or

this is not really important to them.

So it's not really important to them,

I don't want to spend a lot of money on that particular attribute.

And conversely, if it is really important, that's where I've got to put my resources.

That's where I've got to put my money.

Now, does conjoint work for everything?

It doesn't.

It works for certain types of products and

certain types of services and in particular the products or

services are one's that can be reasonably decomposed into attributes.

So what does that mean?

We'll take our mutual fund example.

If you're evaluating a mutual fund, what are you looking at?

For those of you who are not familiar with mutual funds, don't worry about it.

it's a financial product, I imagine some of you are familiar with it and

some of you aren't.

I will certainly have a non-financial example in just a minute.

But a mutual fund has a lot of different attributes.

You can look at past returns, investment returns and people do look at that.

They look at fees like that load or that annual management fee, the brand name,

whether they've heard of the fund before that might be important.

It might make them feel safe about investing in the fund and whether or

not they have online, very convenient online access to their fund.

So a mutual fund is a product that's recently described by a set of attributes.

Better important in the decision process.

Commercial aircraft so

this is not just the business consumer space, commercial aircraft is a B2B, or

Business to Business, purchase and a large one of that right.

So when Singapore Airlines or

American Airlines decides to buy an aircraft from let say, Airbus or

Boeing which are two with a major manufactures, what are they looking at?

Well, they're looking at the attribute of the product.

What's the capacity of the plane?

What's the maximum range to the plane?

How fuel efficient is it?

If it's more fuel efficient, it costs them less for jet fuel.

What's the price going to be?

What's the cost of the service contract?

Because a lot of the manufacturers make a lot of money on.

Service and many other attributes probably a long list

of attributes that the individual airline might be considering.

So this is another product in a very different kind of environment

that's reasonably described by a set of attributes.

Conversely, think about something like clothing, yes, it has some attributes

my coat has a lapel on it, my shirt has some buttons on it, those are in fact

attributes to the product but really think about in a realistic way.

When you go to buy clothes, you are really not balancing attributes against

each other, you are looking at a shirt and say I really like that shirt.

I think that shirt would look good on me.

It's more of an emotional gut reaction.

Yes, you look at the price but it's not a stack up of the attributes in the same

way that a mutual fund or a commercial aircraft would be.

So for a category like clothing or maybe a restaurant that you like to attend which

is a more of an emotional play, conjoint analysis

really isn't appropriate because it doesn't give us a lot of information.

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