And how do we do that?

Well we know we're going to take 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 of me, right?

In particular, we're charging $8.99 per ball 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

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 prices going to be up in a 899-1099 range, we can tell

that because the .24 is smaller than the overall range between 8.99 and 10.99.

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

And in an order to do that,

we essentially convert it into a 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 that's why we're moving up 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 distance side.

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

price points, 10.99- 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 that for different balls that you might be considering.

Not just increase in distance.

You can even do it for decreases in attribute.

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 conjoined analysis.