Memo 1 To: Pricing Manager, Tri-State Region From: Regional Vice President, Tri-
ID: 1136547 • Letter: M
Question
Memo 1
To: Pricing Manager, Tri-State Region
From: Regional Vice President, Tri-State Region
Re: Revenue from EPIX
We recently added the EPIX Movie Channels as part of a new tier of programming for our digital video subscribers. The EPIX channels are sold as an add-on package for $9.75 per month, but we would like to potentially increase our revenue from our subscriber base. Currently we have about 15,059 subscribers, generating monthly revenue of $146,823.
Some have suggested we should cut price, as customers tend to be fairly price sensitive for add-on packages. However, in this case, if we lower price for our new subscribers, we really need to cut it to all of our existing subscribers as well. I have some concerns that lowering price will be counter-productive.
The marketing department calculated some subscription levels at various price points in this region, and I need you to perform the analysis. Specifically, I want you to estimate the price sensitivity of customers at the current price. Please address the following questions:
(1) If we lower the price, do you think this is likely to lead to higher revenue, and
(2) how much potential revenue can we generate and how low should go with our price.
The demand equation from the regression is as follows:
Qd = 39.057-2.462P (from the information in the Excel data)
3.) Calculate elasticity at current price of $9.75
4.) Inverse demand: P = 15.869-0.406
What is Marginal revenue?
Set MR = 0 and solve for P and Q.
Use this information from the regression plus the information in Memo 1 to answer questions 1 and 2. You do not need to discuss the output of a regression.
Time Warner Cable Solution to MEMO 1:
Revenue from EPIX
Using the Epix.xlsdata file, estimation of a linear regression will give the following output:
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.9463
R Square
0.8955
Adjusted R Square
0.8900
Standard Error
2.6757
Observations
21
ANOVA
df
SS
MS
F
Significance F
Regression
1
1166.15
1166.15
162.88
0.000
Residual
19
136.03
7.16
Total
20
1302.17
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
39.057
2.015
19.383
0.000
34.840
43.274
Price
-2.461
0.193
-12.763
0.000
-2.865
-2.058
Table:
Estimates of market penetrationin the Tri-State Region based on different price levels.
License fees representthe fees that we must pay to Epix for the rights to re-transmit their channels. Fees are based on the number of subscribers.
Thanks for your help.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.9463
R Square
0.8955
Adjusted R Square
0.8900
Standard Error
2.6757
Observations
21
ANOVA
df
SS
MS
F
Significance F
Regression
1
1166.15
1166.15
162.88
0.000
Residual
19
136.03
7.16
Total
20
1302.17
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
39.057
2.015
19.383
0.000
34.840
43.274
Price
-2.461
0.193
-12.763
0.000
-2.865
-2.058
Explanation / Answer
Answer:
To get profit maximizing price lets calculate profit at each level.
Profit = TR - TC
and TR = Price * number of subscriber
TC = Cost of license fee + general administrative and divisional cost
As you can see profit is maximized at Price of $11.5
Recommended price is $11.5. By adjusting price to this level, the profit will be $78221. And total revenue will be $152329.
Yes the revenue will increase as well.
Price No of subscribers Cost of license fees Divisoanl, general and adm costs TR TC Profit 5 29.974 134.883 14.5 149.87 149.383 0.487 5.5 29.256 131.651 14.5 160.908 146.151 14.757 6 17.822 80.199 14.5 106.932 94.699 12.233 6.5 22.657 101.956 14.5 147.2705 116.456 30.8145 7 19.897 89.537 14.5 139.279 104.037 35.242 7.5 16.671 75.017 14.5 125.0325 89.517 35.5155 8 20.492 92.213 14.5 163.936 106.713 57.223 8.5 20 89.998 14.5 170 104.498 65.502 9 19.76 88.92 14.5 177.84 103.42 74.42 9.5 17.123 77.053 14.5 162.6685 91.553 71.1155 10 12.643 56.896 14.5 126.43 71.396 55.034 10.5 12.785 57.532 14.5 134.2425 72.032 62.2105 11 12.216 54.974 14.5 134.376 69.474 64.902 11.5 13.246 59.608 14.5 152.329 74.108 78.221 12 8.637 38.867 14.5 103.644 53.367 50.277 12.5 10.595 47.78 14.5 132.4375 62.28 70.1575 13 5.857 26.357 14.5 76.141 40.857 35.284 13.5 2.615 11.768 14.5 35.3025 26.268 9.0345 14 2.739 12.326 14.5 38.346 26.826 11.52 14.5 5.291 23.809 14.5 76.7195 38.309 38.4105 15 3.051 13.73 14.5 45.765 28.23 17.535