[SOLVED] the Price Optimization model in Enginius
Question 1
Run the Price Optimization model in Enginius. Hint1: Assume that the average attendance is
now about 250 people per event, with an average of 12 events per month; use this information to
specify the monthly total market size (# of people) before running the price optimization model
in Enginius. Hint2: The “case study in pdf format” mentions that Zach’s costs are $3,000 per
month; use this information to specify the monthly fixed costs ($) before running the price
optimization model in Enginius. Hint 3: Ignore the data block named “demographic information”
for your analysis throughout this report.
(a) Looking at the Enginius output, what is the maximum market share that Zach can attain in
this market?
(b) Looking at the Enginius output, and assuming that the data contains a representative sample
of Zach’s Garage customer base, what price level would maximize the predicted purchase
likelihood among his customers?
(c) Looking at the Enginius output, and assuming that the data contains a representative sample
of Zach’s Garage customer base, what price level would maximize the expected gross margin
and the expected net margin per month?
(d) Looking at the Enginius output, would that optimal price, which you identified in Question
1c, be sufficient to cover Zach’s monthly fixed costs? Justify your answer giving one argument.
(e) Looking at the Enginius output, what are the expected monthly total revenue at the optimal
price, which you identified in Question 1c? Tip: to compute the expected monthly total revenue,
use the formula: MONTHLY TOTAL MARKET SIZE × PREDICTED PURCHASE
LIKELIHOOD × PRICE.
Question 2:
(a) Looking at the Price Point Examples table in the Enginius output, what are the minimum and
maximum price levels below and above which, respectively, Zach does not cover his monthly
costs – that is, he is losing money? Justify your answer giving one argument.
(b) Assuming that attendance is currently around 250 people per event, at what price level would
that attendance decrease to an average of 125? That is, approximately at what price would
around half the attendees stop coming because of the entrance fee? Use results from the Enginius
output to justify your answer. Hint4: use the Predicted Purchase Likelihood chart and the Price
Point Examples Table to answer this question, given that likelihood of purchase denotes the
percentage of 9 attendance.
(c) Taking into account your answers to all preceding questions, as well as information from the
“case study in pdf format”, what price level would you recommend to Zach, and why? Give one
reason.
Question 3:
Looking at the “survey options” data block in Enginius, one can see that the associated
probability for scale option 5 (i.e., “will definitely buy”) is 100%. In your discussions with Zach,
you, as his consultant, voiced your concern that assuming that an answer of 5 would translate
into a 100% purchase probability seems dubious. What if this probability is actually lower? That
is, what would happened if the probability would be lower than 100%? To explore this issue, run
“what-if” scenarios, by changing the values of the associated probability (%) for scale option 5 in
the “survey options” data block, and rerunning the price optimization analysis in Enginius
(without however changing anything else in your specification and analysis). Although you are
free to run your own “what-if” scenarios, a good suggestion is to run the following scenarios: a
pessimistic (i.e., the associated probability (%) for option 5 is way lower than 100%, say, 50%),
and a realistic (i.e., the associated probability (%) for option 5 is slightly lower than 100%, say,
90%).
(a) What conclusions do you now draw about the optimal price levels that maximize the
expected net margin per month under each of the 2 scenarios? Give one argument for each
scenario.
(b) (b) Would you now change your recommendation to Zach (i.e., your answer to Question 2c)
or not, and why? Give one reason. the Price Optimization model in Enginius the Price Optimization model in Enginius
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