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The Marketing Mix ² Advertising Budget Decisions ² Pricing Decisions ² Sales Resource Allocation The Marketing Mix ² Advertising Budget Decisions ² Pricing Decisions ² Sales Resource Allocation Decisions: Call. Plan, Re. Allocator ² Promotion Decisions

Advertising Spending Decisions ² Advertising Response Functions ² Advertising in Practice ² Adbudg and Advertising Spending Decisions ² Advertising Response Functions ² Advertising in Practice ² Adbudg and Blue Mountain Coffee ² Media/Schedule to Select? © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 2

Advertising interacts with other mix elements: ² Personal selling (especially for industrial products) ² Advertising interacts with other mix elements: ² Personal selling (especially for industrial products) ² Branding (advertise the brand/company? ) ² Price (does it increase or decrease price elasticity? ) ² Distribution (how to match distribution coverage with advertising coverage? ) © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 3

Sales Response to Advertising Shape: S shape? Linear? Decreasing returns? Saturation point? Threshold? Dynamics: Sales Response to Advertising Shape: S shape? Linear? Decreasing returns? Saturation point? Threshold? Dynamics: Growth and decline equal? Delay/carryover effects? Hysteresis? Interaction: Advertise in strong (or weak markets)? © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 4

What Do We Know About Advertising Response? 1. Sales respond dynamically upward and downward, What Do We Know About Advertising Response? 1. Sales respond dynamically upward and downward, respectively, to increases and decreases of advertising and frequently do so at different rates. 2. Steady state response can be concave or S shaped and will often have positive sales at zero advertising. 3. Competitive advertising affects sales. 4. The dollar effectiveness of advertising can change over time as the result of changes in media, copy, and other factors. 5. Products sometimes respond to increased advertising with a sales increase that falls off even as advertising is held constant © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 5

Hysteresis Example 1. 4 Average during Heavy Advertising Pretest Average 1. 2 1 0. Hysteresis Example 1. 4 Average during Heavy Advertising Pretest Average 1. 2 1 0. 8 0. 6 Heavy Advertising 0. 4 0. 2 12 14 16 18 20 22 24 26 28 30 32 34 0 2 4 6 8 10 Sales Rate Time (4 -week periods) © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 6

Response Shape Example Radio Equipment in Newspapers Service Recruiting in Newspapers 300 1, 200 Response Shape Example Radio Equipment in Newspapers Service Recruiting in Newspapers 300 1, 200 250 1, 000 200 Response Units 150 Response Units 800 600 © Decision. Pro 2007 4, 000 3, 500 3, 000 2, 500 2, 000 1, 500 3, 000 Advertising Units (a) 1, 000 0 500 0 2, 500 2, 000 50 1, 500 400 0 500 1, 000 100 Advertising Units (b) Principles Chapter 7: The Marketing Mix 7

The Timing of Advertising Response 6 4 Sales Increase (%) 2 0 Advertising Pulse The Timing of Advertising Response 6 4 Sales Increase (%) 2 0 Advertising Pulse 1 2 3 4 5 Months © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 8

Advertising Budgeting in Practice ² Affordable method ² Percent of sales ² Competitive parity Advertising Budgeting in Practice ² Affordable method ² Percent of sales ² Competitive parity method ² Objective/task method ² Model based /Response Model approach © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 9

Response Model: Theoretical Idea discounted sum over markets & time of sales Max Profit Response Model: Theoretical Idea discounted sum over markets & time of sales Max Profit = (advertising levels & ´ margin – advertising competition, other mix spending levels) Need to know: ² Sales response for each market area, over time. ² Competitive responses. ² Interactive effects. Examples: ² Rao & Miller study ² ADBUDG © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 10

Rao and Miller Study Idea: ² Use natural variations in changes in advertising versus Rao and Miller Study Idea: ² Use natural variations in changes in advertising versus changes in sales across markets to develop a response function. ² Use response function to optimize advertising spending. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 11

Advertising Response Function (for a specific brand) 37. 5 District 11 30 22. 5 Advertising Response Function (for a specific brand) 37. 5 District 11 30 22. 5 District 7 District 10 District 1 15 District 6 District 8 District 4 District 9 27 22. 5 9 4. 5 0 18 District 3 District 2 13. 5 7. 5 0 Sales Dollars per 1, 000 Persons per Year Advertising Dollars per 1, 000 Persons (in the target population) per Year © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 12

Relationship between Marginal Sales Created by Advertising and Average Advertising 37. 5 District 10 Relationship between Marginal Sales Created by Advertising and Average Advertising 37. 5 District 10 30 Y Y = Change in sales dollars per 1, 000 persons per year for a $6 change in advertising dollars per 1, 000 persons per year District 9 District 8 District 4 22. 5 15 District 11 District 7 District 6 District 5 District 3 District 1 7. 5 District 2 0 0 4. 5 9 13. 5 18 22. 5 27 X X = Advertising dollars per 1, 000 persons per year © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 13

ADBUDG Response Model Assumptions ² If advertising is cut to zero, brand share will ADBUDG Response Model Assumptions ² If advertising is cut to zero, brand share will decrease, but there is a floor (min), on how much share will fall from its initial value by the end of the period. ² If advertising is increased a great deal, say to something that could be called saturation, brand share will increase but there is a ceiling (max), on how much can be achieved by the end of one period. ² There is some advertising rate that will maintain initial share. ² An estimate can be made by data analysis or managerial judgement of the effect on share by the end of one period of a 20% increase in advertising over the maintenance rate. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 14

Input—Calibrating Sales Response to Advertising Function Max share at end with saturation AD Saturation Input—Calibrating Sales Response to Advertising Function Max share at end with saturation AD Saturation advertising +20% advertising Share Initial Share End share with +20% AD Maintenance advertising Zero advertising Min share at end One period Time © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 15

Share Response vs Advertising in 1 Period Max Share Min Maintenance +20% Advertising Share Share Response vs Advertising in 1 Period Max Share Min Maintenance +20% Advertising Share Response = min + (max – min)(adv)c / [d + (adv)c] © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 16

Effective Advertising adv (t)] = [media efficiency (t)] ´ [copy effectiveness ´ [adv dollars Effective Advertising adv (t)] = [media efficiency (t)] ´ [copy effectiveness ´ [adv dollars (t)] © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 17

Adding Time Delays/Carryover ² In the absence of advertising, share would eventually decay to Adding Time Delays/Carryover ² In the absence of advertising, share would eventually decay to some long run minimum value (possibly zero) ² The decay in one time period will be a constant fraction of the gap between current share and the long run minimum, that is, decay is exponential Long run min = lowest share possible in the long = fraction of the difference run Persistence between “long run min” and amount of share retained with zero advertising © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 18

The Full Model Sharet = Long Run Minimum (LRM) + Persistence ´ (Sharet– 1 The Full Model Sharet = Long Run Minimum (LRM) + Persistence ´ (Sharet– 1 – LRM) + Share Response © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 19

Pricing Decisions ² Demand/Price Functions ² Pricing in Practice § Cost based § Value Pricing Decisions ² Demand/Price Functions ² Pricing in Practice § Cost based § Value based § Competition based ² Revenue Management © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 20

Demand/Price Functions (Linear) Q |b 2| > |b 1| Elasticity of Q 2 is Demand/Price Functions (Linear) Q |b 2| > |b 1| Elasticity of Q 2 is larger than elasticity of Q 1 = a – b 1 p Quantity (Q) Q 2 = a – b 2 p p Price © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 21

Demand/Price Functions Nonlinear (Constant Elasticity) Constant Elasticity Quantity Q Q = a. P–b P Demand/Price Functions Nonlinear (Constant Elasticity) Constant Elasticity Quantity Q Q = a. P–b P Price © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 22

Classical (Theoretical) Price Analysis for a Monopolist 1. Quantity demanded = f (Price) 2. Classical (Theoretical) Price Analysis for a Monopolist 1. Quantity demanded = f (Price) 2. Profit = Quantity (Price) ´ [Price – Unit Cost] 3. Find price to maximize profit (Find price where Marginal Cost = Marginal Revenue). Core Assumptions: ² focus on short run profit; ² focus on immediate customers; ² price is independent of advertising, promotion, etc. ; ² demand cost functions are known; ² unit cost is constant; ² firm has true control over price; ² competitors are ignored, etc. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 23

Pricing Under Different Elasticities of Demand Q: Quantity P: Price © Decision. Pro 2007 Pricing Under Different Elasticities of Demand Q: Quantity P: Price © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 24

Pricing Under Different Elasticities of Demand To maximize profit for the monopolist, set MR=MC. Pricing Under Different Elasticities of Demand To maximize profit for the monopolist, set MR=MC. That is: Therefore, the incremental price that you can get over marginal cost depends on the elasticity of demand. When E is very large (infinity), then P/MC = 1, i. e. , P = MC. When E is very small, P will be much larger than MC. Marketing attempts to lower elasticity to the extent feasible (e. g. , retail/airline loyalty programs). © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 25

Profits at different Elasticities (Lo versus Hi) Example effects of price increases Before After Profits at different Elasticities (Lo versus Hi) Example effects of price increases Before After (Lo) After (Hi) 10. 10 +1% Price 10. 00 10. 10 +1% Quantity 100 98 90 Revenue 1, 000 989. 8 Total Cost 970 950. 6 873. 0 Profit 30 39. 2 +31% 36. 0 +20% © Decision. Pro 2007 909. 0 Principles Chapter 7: The Marketing Mix 26

Pricing in Practice Cost Oriented Pricing Costs influence prices because they influence supply. (e. Pricing in Practice Cost Oriented Pricing Costs influence prices because they influence supply. (e. g. , learning curve analysis) Demand Oriented Pricing Customers influence prices through their influence on demand. (e. g. , elasticity analysis value in use analysis—Ch 2) Competitor Oriented Pricing (e. g. , competitive bidding) Competitors influence prices through their actions in the marketplace. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 27

Competition-Oriented Pricing: Competitive Bidding ² Firm is in competition with an unknown number of Competition-Oriented Pricing: Competitive Bidding ² Firm is in competition with an unknown number of suppliers with no (deterministic) knowledge of their prices. ² Two approaches: symmetric: (competitors are like me—game theory/equilibrium analyses) asymmetric: (my analysis is different than competitors, who can be represented probabilistically—decision analysis) © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 28

Decision Analysis Approach Q 1: Should I bid at all? Q 2: If Yes Decision Analysis Approach Q 1: Should I bid at all? Q 2: If Yes to Q 1, what should the bid be? Expected Profit (P) = Win Prob (P) [P – C] where: P = Price, C = Cost of production. è Prob”. Every (bid) price has a “Win How can that Win Prob be estimated? © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 29

Assume One Competitor 100% Chance of Competitor Bidding X or Lower 50% 0% ñ Assume One Competitor 100% Chance of Competitor Bidding X or Lower 50% 0% ñ Best Guess Competitive Bid (X) Perhaps “Best Guess” ´ “Our Cost”, ie, a model of competitive bids. k Perhaps for 2 or more competitors, k varies as ki, i = 1, 2, . . . # competitors, (ki is high ki is low Ô Ô skimmer penetrator), © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 30

How Much to Bid? 100% Competitive Bid Probability Our Win Probability is this area How Much to Bid? 100% Competitive Bid Probability Our Win Probability is this area 0% ñ Our Bid Competitive Bid (X) So, to win, we must bid lower than our (one) competitor. If there are n competitors, we must be lower than all of them. So, Win Probability lower than Competitor 1 Competitor n. = prob. of bidding and Competitor 2 and . . . © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 31

Question How can this structure help select a bid price when: a. the number Question How can this structure help select a bid price when: a. the number of competitors is known? b. the number of competitors is not known for sure? c. our costs are not known for sure? © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 32

Market Response Curve Likelihood of Winning (%) Calculating Optimal Bid Price 100 Market Response Market Response Curve Likelihood of Winning (%) Calculating Optimal Bid Price 100 Market Response 80 60 40 X 20 0 Bid Price Contribution Margin 1200 1000 Revenue - Costs 800 600 400 200 0 -200 -400 Bid Price = Target Price Most Profitable Bid Price calculated Expected Contribution 800 700 600 500 400 300 200 100 0 Bid Price © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 33

Differential Pricing First Degree — Charge consumers exactly what they are willing to pay Differential Pricing First Degree — Charge consumers exactly what they are willing to pay for product (e. g. , college tuition) Second Degree — Offer consumers a menu of options at different prices that correspond to consumers’ willingness to pay for the different options (e. g. , volume pricing) Price Discrimination Third Degree — Divide consumers into distinct segments, charging different prices to different segments (e. g. , movie-theater pricing) © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 34

Differential Pricing with Differential Service Value from…. Value to e vic er S ice Differential Pricing with Differential Service Value from…. Value to e vic er S ice Serv Low-Value Customers Appropriate Low-cost Service Level ice v er S High Value Customers vice Ser Appropriate Higher Cost Service Level Balance the value provided to a customer with the price received from the customer. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 35

Bases for Differential Pricing ² Geographic ² Temporal (time of making reservation) ² Non Bases for Differential Pricing ² Geographic ² Temporal (time of making reservation) ² Non linear (Quantity discounts) ² Costs of servicing an account ² Reference accounts ² ……. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 36

Revenue Management Through Temporal Price Discrimination Revenue management is the art and science of Revenue Management Through Temporal Price Discrimination Revenue management is the art and science of selling the right product to the right customer for the right price at the right time. ² High fixed cost industries ² Service industry (here, we focus on hotels and airlines) ² Alternative approaches (temporal price discrimination in the airline/hotel industry) § Time of day pricing § Time when purchased § Day of the week pricing § Seasonal pricing © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 37

Actual Revenue Data for a Sample Flight Total available seats: 138 © Decision. Pro Actual Revenue Data for a Sample Flight Total available seats: 138 © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 38

Revenue Stream if Low Price Seats Fill up First Total available seats: 138 © Revenue Stream if Low Price Seats Fill up First Total available seats: 138 © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 39

Revenue Stream if Airline Knows Exact Demand Pattern What is the maximum opportunity cost Revenue Stream if Airline Knows Exact Demand Pattern What is the maximum opportunity cost of not having a revenue management system? Total available seats: 138 © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 40

Implementing Revenue Management ² Estimate demand for each class of service. ² Demand arrives Implementing Revenue Management ² Estimate demand for each class of service. ² Demand arrives over time—so update demand function/remaining supply. ² Allocate remaining space to: § maximize expected profitability § meet other criteria subject to situation specific constraints. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 41

Revenue Management Process 3 Step Process I: Design II: Seasonal Planning/Allocation III: Daily Management Revenue Management Process 3 Step Process I: Design II: Seasonal Planning/Allocation III: Daily Management © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 42

Revenue Management Process cont’d Step I: Design Specify: ² Number of classes of services Revenue Management Process cont’d Step I: Design Specify: ² Number of classes of services ² Design of each service class ² (Average) price/demand curve/class ² Total capacity © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 43

Revenue Management Process cont’d Step II: Seasonal Planning/Allocation ² Specify time path of demand Revenue Management Process cont’d Step II: Seasonal Planning/Allocation ² Specify time path of demand arrival/class ² Minimum price difference/class ² Seasonal demand adjustments ² (Incremental) cost of service Find: ² Optimal number of spaces/class ² Optimal price/class © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 44

Revenue Management Process cont’d Step III: Daily Management ² X days before target date Revenue Management Process cont’d Step III: Daily Management ² X days before target date ² Current booked to date by class ð Update expected demand Update allocation of product to class (upgrade/release higher class of service product) © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 45

Example of Revenue Management in Action Occupancy Rate % 1. 60 days before room-night, Example of Revenue Management in Action Occupancy Rate % 1. 60 days before room-night, a hotel might accept bookings with some discounts. At the same time, some marketing strategies could be pursued. Decision Points 2. At this point, the hotel might sell 4 70 rooms only at full rates, assuming that the demand curve will continue. 3. The hotel can use aggressive marketing strategies and discount rooms to reach target occupancy. Reservation Profile 3 2 4. The demand curve really picks up. The 70% target occupancy is passed 8 days before due date. The hotel goes back to full rates. 1 Actual Reservations Leadtime (days) 45 30 15 © Decision. Pro 2007 0 Principles Chapter 7: The Marketing Mix 46

Revenue Management in Practice Airlines ² Major US domestic carriers: § Operate 5000 flights Revenue Management in Practice Airlines ² Major US domestic carriers: § Operate 5000 flights per day § Serve over 10, 000 markets § Offer over 4, 000 fares ² Schedules change twice each week ² On a typical day, a major carrier will change 100, 000 fares ² Airlines offer their products for sale more than one year in advance ² The total number of products requiring definition and control is approximately 500, 000 (various possible routes) ² This number is increasing due to the proliferation of distribution channels and customer specific controls Source: Sabre © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 47

Real-Time Transactions Data for Revenue Management in Airlines 1 2 PHG 01 E 08800005 Real-Time Transactions Data for Revenue Management in Airlines 1 2 PHG 01 E 08800005 010710 225300 XXXX 000000 I 01 1 V XXXX SNA US XXX 05664901 0000 XXXXX XXX I R 0 0 PSG 01 OA 3210 LAX IAH K 010824 1500 010824 2227 010824 2200 010825 0227 HK OA 0 0 PSG 01 OA 9312 IAH MYR K 010824 2330 010825 0037 010825 0330 010825 0437 HK OA 0 0 PHG 01 E 08800005 010710 010711 125400 XXXX 000000 I 01 1 V XXXX SNA US XXX 05664901 0000 XXXXX XXX I R 0 0 PSO 01 EV 0409 K PSG 01 OA 1221 LAX IAH K 010825 0600 010825 1325 010825 1300 010825 1725 HK OA 0 0 PSG 01 OA 0409 IAH MYR K 010825 1455 010825 1636 010825 1855 010825 2036 HK OA 0 0 PSO 01 EV 4281 Y PSG 01 OA 4281 MYR IAH Y 010902 0600 010902 0714 010902 1000 010902 1114 HK OA 0 0 PSG 01 OA 5932 IAH LAX K 010902 0800 010902 0940 010902 1200 010902 1640 HK OA 0 0 3 PHG 01 E 08800005 010710 010712 142000 XXXX 000000 I 01 1 V XXXX SNA US XXX 05664901 0000 XXXXX XXX I R 0 0 PSO 01 EV 0409 K PSG 01 OA 1221 LAX IAH K 010825 0600 010825 1325 010825 1300 010825 1725 HK OA 0 0 PSG 01 OA 0409 IAH MYR K 010825 1455 010825 1636 010825 1855 010825 2036 HK OA 0 0 PSO 01 EV 4281 Y PSG 01 OA 4281 MYR IAH L 010903 0600 010903 0714 010903 1000 010903 1114 HK OA 0 0 PSG 01 OA 5932 IAH LAX K 010902 0800 010902 0940 010902 1200 010902 1640 HK OA 0 0 4 PHG 01 E 08800005 010710 010716 104500 XXXX 000000 I 01 1 V XXXX SNA US XXX 05664901 0000 XXXXX XXX I R 0 0 PSO 01 EV 0409 K PSG 01 OA 1221 LAX IAH K 010825 0600 010825 1325 010825 1305 010825 1725 HK OA 0 0 PSG 01 OA 0409 IAH MYR K 010825 1455 010825 1636 010825 1855 010825 2036 HK OA 0 0 PSO 01 EV 2297 L PSG 01 OA 5932 IAH LAX K 010903 0800 010903 0940 010903 1200 010903 1640 HK OA 0 0 PSG 01 OA 2297 MYR IAH Q 010903 1140 010903 1255 010903 1540 010903 1655 HK OA 0 0 5 PHG 01 E 08800005 010710 010717 111500 XXXX 000000 I 01 1 V XXXX SNA US XXX 05664901 0000 XXXXX XXX I R 0 0 PSO 01 EV 0409 K PSG 01 OA 1221 LAX IAH K 010825 0600 010825 1325 010825 1300 010825 1725 HK OA 0 0 PSG 01 OA 0409 IAH MYR K 010825 1455 010825 1636 010825 1855 010825 2036 HK OA 0 0 PSO 01 EV 2297 Q PSG 01 OA 0981 IAH LAX Q 010903 1420 010903 1608 010903 1820 010903 2308 HK OA 0 0 PSG 01 OA 2297 MYR IAH Q 010903 1140 010903 1255 010903 1540 010903 1655 HK OA 0 0 Source: Andrew Boyd © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 48

Decision Support Systems for Revenue Management Source: Andrew Boyd © Decision. Pro 2007 Principles Decision Support Systems for Revenue Management Source: Andrew Boyd © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 49

Profiting from Revenue Management 1. Use price management, rather than cost cutting to balance Profiting from Revenue Management 1. Use price management, rather than cost cutting to balance supply and demand. 2. Price according to what the market will bear. 3. Use differential pricing to reach different segments of customers. 4. Save the “best product” for the most valuable customers. 5. Make decisions based on real time market information. 6. More fully exploit available resources. 7. Revenue management is a way to bring discipline into the organization’s decision making process. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 50

From Revenue Management to Dynamic Pricing? ² Typically, revenue management and differential pricing go From Revenue Management to Dynamic Pricing? ² Typically, revenue management and differential pricing go together, but this is not necessary § Do fare classes represent different products, or different prices for the same product? ² Although revenue management appears to focus on inventory management and control, it is really about dynamic pricing based on evolving demand forecasting. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 51

Lessons ² Pricing offers high leverage in improving profitability. ² Understanding elasticity of demand Lessons ² Pricing offers high leverage in improving profitability. ² Understanding elasticity of demand for different customer segments is key to making informed price decisions. ² Revenue management (typically accomplished through differential and dynamic pricing) is an important determinant of profitability, especially in high fixed cost industries. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 52

Sales Resource Allocation ² Background ² Call. Plan ² Re. Allocator © Decision. Pro Sales Resource Allocation ² Background ² Call. Plan ² Re. Allocator © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 53

Marketing/Sales Budgeting and Resource Allocation (Current Practice) Budgeting ² % of sales method ² Marketing/Sales Budgeting and Resource Allocation (Current Practice) Budgeting ² % of sales method ² Benchmark with industry Resource Allocation ² The “squeaky wheel” model ² Inertia (+ or – a percentage of last period) ² The “Eloquent Ignorance” model ² “Spread the butter” model ² Other – your business? © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 54

Resource Allocation Using a Response Model System Marketing Actions Inputs Competitive Actions Product design Resource Allocation Using a Response Model System Marketing Actions Inputs Competitive Actions Product design Price Advertising Selling effort etc. Market Response Model Observed Market Outputs (2) (1) (4) Awareness level Preference level Sales Level (3) Environmental Conditions Control Adaption (6) Objectives © Decision. Pro 2007 Evaluation (5) Principles Chapter 7: The Marketing Mix 55

Allocation Example: Call. Plan Model at United Airlines ² Step 1 Determine expected contribution Allocation Example: Call. Plan Model at United Airlines ² Step 1 Determine expected contribution of all possible call policies for each product account. ² Step 2 Allocate time to accounts. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 56

How to Estimate the Response Function? ² Estimate from Historical data § § Data How to Estimate the Response Function? ² Estimate from Historical data § § Data available? Is there sufficient variability in the data to allow for reliable estimation? ² Conduct Experiments § § Difficult to execute in offline settings. A bit easier in online settings ² Elicit Managerial Judgment § § § Quick. Builds consensus. Encourages systematic thinking. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 57

The Call. Plan Judgmental Approach Asks Each Salesperson. . . What would sales of The Call. Plan Judgmental Approach Asks Each Salesperson. . . What would sales of this account be if. . . you don’t visit the account? X 0. . . you visit the account the same as last period? X 1. . . you visit the account 50% more than last period? X 2. . . you visit the account as frequently as possible? X 3 © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 58

This Yields a Response Function… X X Expected Sales X X 3 2 1 This Yields a Response Function… X X Expected Sales X X 3 2 1 0 0 Base 1. 5 ´ Base Number Of Calls © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 59

Optimization Problem How much time to spend at each account to: ² Maximize § Optimization Problem How much time to spend at each account to: ² Maximize § sum of account revenues ´ account margin ² Subject to § salesperson time constraint § min. /max. calling restriction ² Output § Recommended calling frequencies for each account © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 60

Optimization Procedure in Call. Plan (Incremental Analysis) Number of calls 8 9 1 2 Optimization Procedure in Call. Plan (Incremental Analysis) Number of calls 8 9 1 2 10 3 4 5 6 7 1 11 100 70 300 50 600 400 300 225 160 Account 2 165 1400 85 1100 15 850 650 490 360 250 Number 3 40 3600 30 1800 25 800 200 100 75 50 180 120 170 115 160 150 140 135 130 4 125 The numbers in each row of the matrix correspond to the response function for that account, showing incremental contribution per call at that call level. Total calls available: 15. Indicates marginal contributions at current level of deployment © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 61

Current Allocation vs Model Recommended Allocation 7 6 5 4 3 2 1 0 Current Allocation vs Model Recommended Allocation 7 6 5 4 3 2 1 0 Number of Calls 8 1 2 3 4 Account Number Current Allocation 8 7 6 5 4 3 2 1 0 1 2 3 4 Account Number Model Recommended Allocation Profit with current allocation: $11, 985 Profit with optimal allocation: $13, 000 © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 62

Experimental Application The United Airlines Experiment ² 20 sales people participated § § ² Experimental Application The United Airlines Experiment ² 20 sales people participated § § ² 10 pairs selected § ² 5 East and 5 West matched by managerial judgment, personal characteristics, compatibility of territory size, and revenue account mix. 10 CALLPLAN participants selected § § ² 10 West Coast 10 East Coast 1 from each pair. Other 10 were control group. Control group § § § Told they were in an experiment. Participated in judgmental call frequency/account response development. Received computer feedback of their input but no CALLPLAN recommendations. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 63

Results After 6 Months Sales Change vs Previous Year Experimental Group – Difference Control Results After 6 Months Sales Change vs Previous Year Experimental Group – Difference Control = +11. 9% +3. 8% +8. 1% 0. 025. ) (Probability that this result is due to chance < © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 64

Profit Impact ² Time Needed § ~ 1/2 day per salesperson ² Change in Profit Impact ² Time Needed § ~ 1/2 day per salesperson ² Change in Sales § (~ 95% profit in airline business) > $1, 000 (for the 10 sales people) in 6 months. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 65

Where Does The Gain Come From? ² Pooled judgment on how the market operates/ Where Does The Gain Come From? ² Pooled judgment on how the market operates/ responds to marketer actions taps corporate experience and knowledge. ² Separate focus on inputs and ends/goals facilitates exploration of more input options to reach the goals. ² Computer simplifies cognitive load by performing calculations and sensitivity analyses. ² The analysis process aligns management actions with their beliefs. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 66

Determining Salesforce Size ² % of sales method (back into number of people) ² Determining Salesforce Size ² % of sales method (back into number of people) ² Breakdown method (add up sales potential) ² Based on response functions § Syntex model © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 67

Response Function Sales a Response Max Response Function Current Sales b Min Current Effort Response Function Sales a Response Max Response Function Current Sales b Min Current Effort © Decision. Pro 2007 Effort Level Principles Chapter 7: The Marketing Mix 68

Aggregate Response Model Used in Syntex (Adbudg Function) Xc Y = b + (a–b) Aggregate Response Model Used in Syntex (Adbudg Function) Xc Y = b + (a–b) d + Xc b: Minimum sales with zero effort a: Maximum (saturation level sales) c, d: Response parameters S shaped (c > 1) and concave (c < 1) Incorporates saturation effect Widely used Amenable to judgmental calibration © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 69

Delphi method for Calibrating Sales Response Function Compile group data (e. g. , median Delphi method for Calibrating Sales Response Function Compile group data (e. g. , median sales = 50) Provide aggregate (anonymous) feedback to respondents until consensus reached Get new data from respondents (e. g. , forecasted sales are 50, 65, 45, 50) © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 70

Delphi method for Calibrating Sales Response Function ² Is a method for eliciting “tribal Delphi method for Calibrating Sales Response Function ² Is a method for eliciting “tribal wisdom. ” ² Developed at the Rand Corporation in the 1950’s (used first in military applications). ² Elicits opinions through iterative question process that attempts to reach stability of views (i. e. , consensus). ² This method is more widely used (goes under different names). ² Assumes that collective judgment (particularly expert judgment) provides valid and/or valuable forecasts in the absence of reliable secondary data required for traditional forecasting techniques. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 71

Some Recommendations for Applying Delphi Method in Marketing ² Use neutral facilitator ² Establish Some Recommendations for Applying Delphi Method in Marketing ² Use neutral facilitator ² Establish baseline qualifications for participants ² Ideal size: 7 12 ² Give everyone a common “Briefing Book” about historical performance of products/markets ² Review conflicts of interest (Difficult to avoid) § No advocacy or promotional position § Shared common goal with respect to problem of interest ² Minimize domineering personalities © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 72

Example of Judgmental Calibration © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix Example of Judgmental Calibration © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 73

Example: C-Tek Calibration Form © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix Example: C-Tek Calibration Form © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 74

Base Case Sensitivity © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 75 Base Case Sensitivity © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 75

“Optimal” Selection (Base Case) © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix “Optimal” Selection (Base Case) © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 76

Reallocation © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 77 Reallocation © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 77

Opportunity Costs Identified by Syntex Model Change in Profit after Change in Salesforce Size Opportunity Costs Identified by Syntex Model Change in Profit after Change in Salesforce Size and Reallocation of Effort +$15 M Opportunity cost of maintaining current sales force size +$10 M +$5 M 0 –$5 M 0 Current level 30 Optimal increase in sales force size Change in Salesforce Size from Current Level © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 78

Sizing Example: Salesforce Sizing at Syntex ² Current salesforce size (1982) was 433 reps, Sizing Example: Salesforce Sizing at Syntex ² Current salesforce size (1982) was 433 reps, expanding by 30– 40 per year. ² Salesforce allocated to: 7 Drugs Naprosyn, Anaprox, Norinyl, etc. & 9 Physician Specialties medicine OB/GYN, etc. by judgmental/historical norms. Family practice, internal ² Questions: How large should the salesforce be? How should it be allocated to drugs and to physician specialties? ² Approach: Judgmental estimation of response functions. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 79

Syntex Approach Each management team member separately estimates a response function for each sales Syntex Approach Each management team member separately estimates a response function for each sales entry As a group, the management team members discuss and develop consensus estimates of response functions Run the model Test profit consequences of alternate scenarios Do results make sense? Can they be implemented? No Yes Implement resource allocation decisions Monitor and evaluate sales performance © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 80

Goals of Judgmental Resource Allocation Model ² Helps set broad direction ² Identify priorities Goals of Judgmental Resource Allocation Model ² Helps set broad direction ² Identify priorities ² Gain anticipatory intelligence ² Generate buy in for action ² Improve communication within the organization © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 81

Summary Lessons from Sales Resource Allocation ² Most of the gains typically come from Summary Lessons from Sales Resource Allocation ² Most of the gains typically come from “reallocation” rather than from incremental effort. ² The Syntex model allows us to assess the opportunity costs of following existing organizational policies, or of adopting political solutions (implemented via constraints in the model). ² Response function normalization around the current business context makes it easier for managers to understand the model and its implications. ² Need to be careful about optimization results that may represent local optima. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 82

Promotional Analysis ² Promotion Types and their Effects ² Aggregate Models ² Individual Models Promotional Analysis ² Promotion Types and their Effects ² Aggregate Models ² Individual Models © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 83

Promotional Types and Targets Trade Promotions Manufacturer q Case allowances q Advertising Trade (Retailer) Promotional Types and Targets Trade Promotions Manufacturer q Case allowances q Advertising Trade (Retailer) allowances q Display allowances q Contests q etc. Consumer Promotions q Coupons q Samples q Price packs q Value packs q Refunds q Contests q Tie-ins q etc. Consumer © Decision. Pro 2007 Retailer Promotions q Price cuts q Displays q Feature ads q Retailer coupons q Free goods q etc. Principles Chapter 7: The Marketing Mix 84

Promotional Objectives and Types Objective Promotional Type Increase repeat buying In pack coupons, continuity Promotional Objectives and Types Objective Promotional Type Increase repeat buying In pack coupons, continuity programs (eg, frequent flyer, “N for” retail promotions Increase market share among FSI coupons, coupons targeted to users of other brand switchers brands, retail promotions. Increase retailer’s promotion Trade deals, combination of consumer promotions frequency and trade deals (big bang theory) Enhance the product’s image Co op image advertising with image oriented retailers Increase category switching Retail promotions, FSI coupons, large rebates Target deal sensitive consumers Coupons, “N for” retail promotions Increase category consumption Retailer promotions, promotions tied to events (e. g. , back to school) Increase trial among non users Cross couponing, free samples, trial packs, direct mail coupons Liquidate short term inventories Trade deals, rebates, inventory financing Increase distribution FSI coupon, (increase demand), trade deals (increase DPP) “N for” FSI DPP = = = multiple unit promotion (6 for 99¢) free standing insert in newspapers and magazines dealer price promotion. © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 85

Promotional Effects 10 9 8 7 Brand Share 6 5 4 3 2 1 Promotional Effects 10 9 8 7 Brand Share 6 5 4 3 2 1 0 Prepromotion Period Promotion Period © Decision. Pro 2007 Immediate Long-run Postpromotion Period Principles Chapter 7: The Marketing Mix 86

Effects of Trade Promotions Manufacturer’s Shipments Other Factors Pipeline Inventories Retailer Promotions Consumer Sales Effects of Trade Promotions Manufacturer’s Shipments Other Factors Pipeline Inventories Retailer Promotions Consumer Sales © Decision. Pro 2007 Other Factors Principles Chapter 7: The Marketing Mix 87

Promotional Effects Model ² Manufacturer’s Shipment Model: Shipmentst = ² Retail Promotions model: Retail Promotional Effects Model ² Manufacturer’s Shipment Model: Shipmentst = ² Retail Promotions model: Retail Promotionst – 1, inventoriest– 1) ² f 1 (trade promotionst, trade promotionst f 3 (retailer promotionst, other factorst) Inventory model: Inventoryt = ² = Consumer Sales model: Consumer Salest = ² f 1 (inventoryt– 1, trade promotionst, other factorst) f 4 (inventoriest– 1, shipmentst, consumer salest) Note that the Inventory model is simply an accounting equation, as: Inventoryt = Inventoryt– 1 + Shipmentst – Consumer Salest © Decision. Pro 2007 Principles Chapter 7: The Marketing Mix 88

Consumer Sales vs Factory Shipments Promotion Period Adjusted Unit Sales 100, 000 80, 000 Consumer Sales vs Factory Shipments Promotion Period Adjusted Unit Sales 100, 000 80, 000 60, 000 40, 000 20, 000 1998 1999 © Decision. Pro 2007 2000 2001 2002 Principles Chapter 7: The Marketing Mix 89

Evaluating the Effect of a Promotion 2. 0 Promotion Ends 1. 8 1. 6 Evaluating the Effect of a Promotion 2. 0 Promotion Ends 1. 8 1. 6 1. 4 Carryover Effect Trade Deal Begins Consumer Sales 1. 2 1. 0 0. 8 Inventory Effect 0. 6 0. 4 II IV I 1999 II III 2000 © Decision. Pro 2007 IV I 2001 Principles Chapter 7: The Marketing Mix 90