Customer Surveys Camera Example

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En provenance du cours de IE Business School

Pricing Strategy

449 notes

IE Business School

Pricing Strategy

449 notes

Cours 2 sur 5 dans Specialization Marketing Mix Implementation

Pricing is one of the most important but least understood marketing decisions. Learn and practice concepts, techniques, and get to grips with the latest thinking on assessing and formulating pricing strategies. Analyze how firms attempt to capture value, as well as profits, in the revenues they earn. After this course, you will be able to contribute to the process of formulating pricing strategies for your own products and services, or those of your firm. This course has an additional focus on pricing dynamics and the reaction to and by competitors, taking a highly pragmatic approach and one that is directly applicable to your day-to-day professional life. Martin Boehm - IE Professor and Dean of the Business School with over 10 years experience - will guide you through four modules. We begin with the importance of pricing and how it ultimately can affect the bottom line. Then, we move on to methods to help you decide what is the optimal price for your product; and then price discrimination - should all your products follow the same pricing strategy or should you differentiate depending on the customer segment? Finally, we look at pricing psychology and how you can manipulate customers in order to drive the highest possible price for your product.

À partir de la leçon

Determining Willingness to Pay

After finishing this module you will be able to take advantage of four different methods to determine the willingness to pay from customers. Whether using Market Data or Experiments (Observation based) or Expert or Customer Surveys (Survey based), you'll be able to use this information in order to identify the optimal price.

Expert Surveys3:34

Customer Surveys7:35

Customer Surveys Camera Example5:21

Rencontrer les enseignants

Martin Boehm
Professor of Marketing
Dean of IE Business School

I briefly wanted to expand on our camera example

that we used in the consumer survey video.

As you might recall,

we had sales information available for camera sales at

three different price points: $120, $180, and $250.

You might remember as well that we also had information about so-called market share,

so these three different price points.

We saw that 47% of the respondents mentioned

that they would purchase the camera at a price of $120.

Equally, we knew that 18% would purchase at a price of $180,

and 11% would purchase at a price point of $250.

We can now transform this as well into actual sales data or

actual demand data assuming a total market size of 100 cameras.

That's why I depicted this here at 47 cameras being sold at a price of $120,

18 at a price of $180 and 11 cameras at a price of $250.

So the first thing that we would like to do is,

what other resulting revenues and try to find as well

that price that maximizes our revenues.

In order to do that, what we simply going to do is we multiply.

For each price point, the price,

in this particular case $120,

times the number of units that we actually would sell.

So, in the very first example,

we would actually see, or for the first price point of $120,

we would actually see that the resulting revenue would be $5,640.

I'm going to quickly do the very same thing

with the very same exercise as well for the other price points.

Again, now we would multiply $180

times the 18 cameras that we're expecting to sell at that particular price point,

which would be $3,240.

And finally, just complete this,

$2,750 for the highest price point of $250.

So we can already see that obviously,

the price that maximizes our revenues would be the price of $120.

And we see that the resulting revenues would be a little bit more than $5,600.

We now can calculate as well our cost,

and the cost information was given in the video as well.

So now, we would have a resulting cost of $4,700 in the very first case.

In the second case, $1,800,

and at the highest price point of $250,

it will be at $1,100.

How did we get to these numbers?

Actually quite straightforward.

As you might recall,

we mentioned in the previous case that the cost per

unit of producing these cameras is $100.

And as a consequence,

we have the 47 units multiplied by a $100 is going to be the $4,700 in total cost.

The same is obviously true if we go to the next price point,

18 units being produced at a cost of $100,

which would result in $1,800 in total cost.

Now as we calculated revenues and calculated cost,

we obviously can determine as well what would be the resulting profits.

This is actually fairly straightforward.

We're just going to subtract the cost of $4,700 of the

$5,640 for the very first price point of $120.

So the resulting profit is going to be $940.

The same is obviously true as well for the second price point.

We have $3,240 with respect to revenues and the total cost of $1,800,

which will result in $1,440.

And I just going to complete that as well for the third price point,

the highest price point of $250.

And here, the total profit is going to be $1,650.

So what we see in this particular case is that now,

we would actually maximize our profits at the highest price point of $250.

So in this simple example,

why we would maximize our revenues at the lowest price point tested of $120,

we would maximize our profitability at the highest price point of $250.

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