Assume data coming from a price skimming experiment, where the price of a particular product was reduced in an online platform over 17 consecutive days, in steps of $50 from an initial value of $1,000 to a final value of $200. The price was maintained constant during each day, and was changed at the beginning of the following day. The last column represents the total number of purchases observed during the corresponding day.
Using the linear demand function, and assuming that product quantities are continuous, compute the optimal price and the optimal revenues under no supply constraint.
Day | Price | #Purchases |
1 | 1000 | 1 |
2 | 950 | 2 |
3 | 900 | 1 |
4 | 850 | 5 |
5 | 800 | 6 |
6 | 750 | 6 |
7 | 700 | 13 |
8 | 650 | 11 |
9 | 600 | 12 |
10 | 550 | 19 |
11 | 500 | 17 |
12 | 450 | 20 |
13 | 400 | 22 |
14 | 350 | 25 |
15 | 300 | 29 |
16 | 250 | 28 |
17 | 200 | 30 |
Total | 247 |
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