Conjoint Analysis: Willingness to Pay

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En provenance du cours de University of Virginia

Customer Value in Pricing Strategy

137 notes

University of Virginia

Customer Value in Pricing Strategy

137 notes

Cours 2 sur 4 dans 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

À partir de la leçon

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 Data3:57

Conjoint Analysis: Propensity Modeling7:58

Rencontrer les enseignants

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

So, now we've come to the point in our analysis

that we're going to look at willingness to pay, right?

We've had a lot of build up to this point, we've looked at willingness to pay with

surveys and I’ve shown you a lot of other things that a conjoint analysis can do.

And I promised you it can give you willingness to pay and it can.

So we're going to do an example of that right now.

So, lets look at a particular golf ball that we're considering.

We've got the magnum force, 10 yards further than the average, $8.99.

By now I think you know where these utilities are coming from and

that this is just the sum of all those utilities.

And we're going to ask ourselves a question,

how much more would the average golfer be willing to pay for

an increase in distance of 5 yards, okay?

So, there it is.

It's a little more complicated than what we've done before but,

it's not a lot more complicated than what we've done before.

Here are the basic steps.

The first thing we need to do is calculate the utility gain for

the increase in distance.

So, we're going to give the ball five more yards or engineer said they can do that.

We need to figure out how much happier people will be with that new ball,

we calculate it.

Then, we're going to find the new price, and

it's going to be a bigger price, right?

We're going to give them a better ball, we're going to charge a bigger price,

we need to find that new price such that we take back from the consumer

the exact amount of utility that we gave them when we gave them that improve ball.

And so in that sense, it's like a break-even.

We give them some utility and whatever that utility is we come over to here to

price and we take it back from them.

And the difference between that new price that we calculate and

the old price is really that increase in willingness to pay.

So let's apply this to the data.

So first of all we're going to calculate the utility gain for

an increase in distance.

And that's 0.36- 0.12.

Where does that come from?

Well if you look at distance, 0.36 is that 15 yards further.

That's the new ball, right?

because our current ball is 10 yards further.

The new ball would be 15 yards further.

That would give them a utility of 0.36, and then we subtract the original utility,

which is that 10 yards further ball, which is 0.12.

So we have a difference of 0.24.

So now what are we going to do?

We're going to take that 0.24 back in the utility from the price.

And how do we do that?

Well we know we're going to pay back 0.24, but 0.24,

that difference is not exactly the same as the difference between

any of the price points that I've got in front me, right?

In particular, we're charging $8.99 per ball right now, and

we're asking how much more would people be willing to pay?

It would be very nice if the $10.99, the utility for

that was just 0.24 less than the $8.99, right?

And then we could just say, it's $2 and it's very easy because we give them 0.24

in distance, we take 0.24 in utility on price.

And all of those numbers are just in front of us, but

usually it doesn't work out that way.

And in fact, I bet you can tell by looking at the data,

the new price is going to have to be somewhere between $8.99 and

$10.99 because the spread of the utilities, which is the difference

between negative 0.83 and negative 0.08 is greater than 0.24.

So here's how we handle that.

We know the new price is going to be up in the $8.99 to $10.99 range.

We can tell that because the 0.24 is smaller than the overall

range between $8.99 and $10.99.

What we need to determine is exactly how far into that range we need to go?

And then in order to do that we essentially convert it into percent

along that range.

We do that by taking 0.24 and dividing that

by the spread in the two price points that we're interested in.

In this particular example that's $8.99 and $10.99 because we know that

price is going up and that's why we're moving to the $10.99 price point.

That's given right down here.

So the resulting calculation gives you 32%,

that means we're moving 32% up in that price range.

That's what we need to do in order to break even and

take back from consumers the exact dollar amount that's

equivalent to the utility gain that they get on the distant side.

I then take that 32% and multiply it by the difference between

the two price points, $10.99 minus $8.99, so $2.

And when I make that calculation I get $0.64.

And how do I interpret $0.64?

That is the increased willingness to pay for the increase in distance.

And you can do that for different segments, you can do it for different

balls that you might be considering, not just increases in distance.

You can even do it for decreases in attributes,

suppose you take something away from consumers.

The exact same math will tell you how much less they would be willing to pay.

This is a very common and

very useful set of metrics that comes out of a conjoint analysis.

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