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Sample Quantitative Questions Chapter 4 Ted Mitchell
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A Marketing Machine Producing Revenues From the 4P’s The Marketing Machine Inputs to The Marketing Machine Price Tags Product Quality Promotion Place Revenue Output from The Marketing Machine Revenues Revenue
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Typology of Demand Producing, Quantity Sold, Q, Marketing Machines Two-Factor Model Calibrated from a Single Observation Two-Factor Meta-Model Calibrated from a minimum of two observations Input from Positive Elements of Marketing Mix, π Promotion, Place, Product Type #1 Quantity Sold, Q = r x π Conversion rate, r = Q/π Quantity Sold, Q = (Q/π) x π Type #3 ∆Quantity Sold, ∆Q = m x ∆π Conversion rate, m = ∆Q/∆π Slope-Intercept version Q = a + m(π) Input from Negative elements of the Marketing mix Price Tag, P Type #2 Quantity Sold, Q = r x P Conversion rate, r = Q/P Quantity Sold, Q = (Q/P) x P Type #4 ∆Quantity Sold, ∆Q = m x ∆P Conversion rate, m = ∆Q/∆P Slope-Intercept version Q = a - m(P) See Chapter 3 for details
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Typology of Basic Revenue Machines Two-Factor Machine Single Point of Calibration Two-Factor Meta-Model Two or More Points of Calibration Positive Input From Marketing Mix, π Promotion, Place, Product Quality Type #1 Revenue, R = (R/π) x π Type #3a: demand extension Revenue, R = P x Q Revenue, R = P(a + b( π )) Revenue, R = aP + bP( π ) Type #3b: direct observation Revenue, R = a + m π Negative Input From Marketing Mix, Price Tag, P Type #2 Revenue, R = (R/P) x P Revenue, R = Q x P Type #4a: demand extension Revenue, R = P x Q Revenue, R = P (a-b P ) Revenue, R = a P – b P 2 Type #4b: direct observation Revenue, R = a + m P
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1) Analysis of a Revenue Machine from Total Expenditure on Servers You own two coffee shops. You are trying to understand the role that servers play in the creation of revenues The shops sell 3 different sizes of coffees and pastries and you have aggregated information on the weekly revenues and the total amount spent on servers each week. Coffee shop #1 spends $1,333 on server wages and generates $10,000 in revenues Coffee shop #2 spends $2,000 on server wages and generates $14,000 in revenues What is the revenue returned per dollar of server wages in each coffee shop?
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Calculating Sales Return on Server Expense Café #1Café #2 Weekly Server Expense, S $1,333$2,000 Return per dollar of expense, r = R/S Weekly Sales Revenue, R = r x S $10,000$14,000
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Calculating Sales Return on Server Expense Café #1Café #2 Weekly Server Expense, S $1,333$2,000 Return per dollar of expense, r = R/S $10,000/$1,333 =$7.5 per dollar or 750% return $14,000/$2,000 =$7.0 per dollar or 700% return Weekly Sales Revenue, R = r x S $10,000$14,000
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2) Analysis of an Average Revenue Returned You own two coffee shops. You are trying to understand the role that servers play in the creation of revenues The shops sell 3 different size coffees and pastries and you have aggregated information on the weekly revenues and the total amount spent on servers each week. Coffee shop #1 spends $1,333 on server wages and generates $10,000 in revenues Coffee shop #2 spends $2,000 on server wages and generates $14,000 in revenues What is the average rate of revenue being returned by the two stores?
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Calculating Sales Return on Server Expense Café #1Café #2Average cafe Weekly Server Expense, S $1,333$2,000$3,333/2 = 1,666.5 Return per dollar of expense, r = R/S $10,000/$1,333 =$7.5 per dollar or 750% return $14,000/$2,000 =$7.0 per dollar or 700% return NOT 725% Weekly Sales Revenue, R = r x S $10,000$14,000$24,000/2 = $12,000
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Calculating Average Revenue Returned on Server Expense Café #1Café #2Average cafe Weekly Server Expense, S $1,333$2,000$3,333/2 = 1,666.5 Return per dollar of expense, r = R/S $10,000/$1,333 =$7.5 per dollar or 750% return $14,000/$2,000 =$7.0 per dollar or 700% return $24,000/$3,33 3 = 7.2 dollars per dollar or 720% return Weekly Sales Revenue, R = r x S $10,000$14,000$24,000/2 = $12,000
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3) Calculate the Meta-Return Rate of Meta-Revenue Machine You observed two coffee shop performances. You are trying to understand the role that servers play in the creation of revenues The shops sell 3 different size coffees and pastries and you have aggregated information on the weekly revenues and the total amount spent on servers each week. Observation #1 café spends $1,333 on server wages and generates $10,000 in revenues Observation #2 café spends $2,000 on server wages and generates $14,000 in revenues What is the Meta-Revenue Return rate, m?
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Calculating Meta-Sales Return Rate Observation #1Observation #2Meta-machine Weekly Server Expense, S $1,333$2,000∆S = $777 Return per dollar of expense, r= R/S $10,000/$1,333 =$7.5 per dollar or 750% return Not Used $14,000/$2,000 =$7.0 per dollar or 700% return Not Used m = ∆R/∆S m = $4,000/$777 m = $5.15 per dollar or 515% Weekly Sales Revenue, R = r x S $10,000$14,000∆R = $4,000
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4) Forecasting with the single point meta-revenue server machine The boss proposes a $200 change in the total expenditure on servers as a means to increase revenues. The calibrated meta-revenue server machine for a single point (∆R, ∆S) is ∆R = 515%(∆S) What is the forecasted change in Revenue, ∆R, given a proposed increase in server expense, ∆S = $200? Forecasted change in Revenue, ∆R = 5.15 ($200) Forecasted change in Revenue, ∆R = $1,030
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Forecasting Revenue works in concert With an analysis of a breakeven revenue, BER In future classes we will calculate the breakeven revenue needed to cover the proposed change in the cost of the server expenditure, ∆S It is usually more convenient to forecast the revenue using the slope-intercept equation of the meta-revenue server machine
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5) Calculate the y-intercept of the slope-intercept equation of meta-revenue server machine You have observed two coffee shop performances. You are trying to understand the role that servers play in the creation of revenues The shops sell 3 different size coffees and pastries and you have aggregated information on the weekly revenues and the total amount spent on servers each week. Observation #2 café spends $2,000 on server wages and generates $14,000 in revenues What is the y-intercept of the slope-intercept equation of the Meta-Revenue machine?
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5) Calculate the y-intercept of the Meta-Revenue Server Machine Calibrated meta-revenue server machine uses 1) one of the observed performances and 2) the calculated meta-conversion rate, m ∆R = m x ∆S (R – R 2 ) = 515% x (S – S 2 ) R – $14,000 = 5.15 x (S – $2,000) Set the proposed input value to S=0 and solve for R = y-intercept, a
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5) Calculate the y-intercept of the Meta-Revenue Server Machine Set the proposed input value to 0 and solve for R = y-intercept, a a – $14,000 = 5.15 x (0 – $2,000) a = $14,000 – $10,300 = $3,700 The y-intercept is a = $3,700 The slope-intercept equation of the meta- revenue server machine is Revenue, R = $3,700 + 515%(Server expenditure, S)
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6) Forecast the Sale Revenue from a proposed level of server expenditure Market Research has calibrated the meta-revenue server machine as Revenue, R = $3,700 + 515%(Server expenditure, S) The boss is proposing an increase in server availability that will result in a total server expenditure of S = $2,200 What is the forecasted Sales Revenue that will be produced by the meta-revenue with $2,200 in server expense as an input? Forecasted Revenue, R = $3,700 + 5.15( $2,200) Forecasted Revenue, R = $3,700 + $11,330 Forecasted Revenue, R = $15,030
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6) Forecast the Sale Revenue from a proposed level of server expenditure Market Research has calibrated the meta-revenue server machine as Revenue, R = $3,700 + 515%(Server expenditure, S) The boss is proposing an increase in server availability that will result in a total server expenditure of S = $2,200 What is the forecasted Sales Revenue that will be produced by the meta-revenue with $2,200 in server expense as an input? Forecasted Revenue, R = $3,700 + 5.15( $2,200) Forecasted Revenue, R = $3,700 + $11,330 Forecasted Revenue, R = $15,030 Always remember to convert the percent return back into a decimal before doing any calculations
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Revenue = kπ a S = server expenditure R = Revenue x x x x x x x x x x x x Linear Revenue Meta-Machine is a secant that approximates the Revenue function R = a + m(S) R =$3,700 +515%(S) R = kPπ a
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7) Extend the meta-demand price equation or demand curve Into a meta-revenue price equation Market Research has estimated that the demand for a medium size coffee is explained by the size of the price tag as Quantity sold, Q = 6,000 – 900(price tag, P) What is the meta-revenue price machine equation? Multiply both sides by the price tag, P (P x Q) = 6,000P – 900(P)(P) Revenue, R = 6,000P – 900P 2
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Estimated Meta-demand price machine or Demand curve Price per Cup $3.90$4.00 Quantity Sold 2,400 Demand Equation Q = 6,000 – 900(P) Revenue = 2,400 x $4.00 Revenue = $9,600 TJM
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8) Forecast a revenue from the meta-revenue price machine using the expanded demand equation Market research has estimated that the meta- revenue price equation that best explains revenues from sales of medium size cups at different prices is Revenue, R = 6,000P – (900cp$ x P 2 ) Management wants to set the selling price at $4.10 a cup. What is the forecasted revenue at that price? Revenue, R = 6,000($4.10) – 900cp$ x ($4.10) 2 Revenue, R = $24,600 – (900cp$ x 16.81$ 2 ) Revenue, R = $24,600 – $15,129 = $6,471
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Revenue Price per cup 0 TJM R= P(a-bP) R = aP - bP 2 R= a-mP
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An Optimal Price, Pr* In Future Chapters we will learn that the optimal selling price, Pr* for maximum revenue for this demand curve is dR/dP = 6,000 – 2(900 cp$)P set = 0 Pr* = a/2(b) = (6,000 cups) /2(900 cp$) Pr* = $3.33 per cup
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