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.