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The Marketing Mix. Advertising Budget Decisions Pricing Decisions Sales Resource Allocation Decisions: CallPlan, ReAllocator Promotion Decisions. Advertising Spending Decisions. Advertising Response Functions Advertising in Practice Adbudg and Blue Mountain Coffee
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The Marketing Mix • Advertising Budget Decisions • Pricing Decisions • Sales Resource Allocation Decisions: CallPlan, ReAllocator • Promotion Decisions
Advertising Spending Decisions • Advertising Response Functions • Advertising in Practice • Adbudg and Blue Mountain Coffee • Media/Schedule to Select?
Advertising Advertising interacts with other mix elements: • Personal selling (especially for industrial products) • Branding (advertise the brand/company?) • Price (does it increase or decrease price elasticity?) • Distribution (how to match distribution coverage with advertising coverage?)
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)?
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
Hysteresis Example 1.4 Average duringHeavy Advertising 1.2 Pretest Average 1 0.8 Sales Rate 0.6 HeavyAdvertising 0.4 0.2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 Time (4-week periods)
Response Shape Example Radio Equipment in Newspapers Service Recruiting in Newspapers 300 1,200 250 1,000 200 800 ResponseUnits Response Units 150 600 100 400 50 200 0 0 0 500 500 1,000 1,500 2,000 2,500 3,000 1,000 1,500 2,000 2,500 3,000 3,500 4,000 Advertising Units(a) Advertising Units(b)
The Timing ofAdvertising Response 6 4 Sales Increase (%) 2 0 -2 0 1 2 3 4 5 Advertising Pulse Months
Advertising Budgeting in Practice • Affordable method • Percent of sales • Competitive parity method • Objective/task method • Model-based /Response Model approach
Response Model: Theoretical Idea discounted sum over markets & time of salesMax Profit = (advertising levels &´ margin – advertising competition, other mix spendinglevels) • Need to know: • Sales response for each market area, over time. • Competitive responses. • Interactive effects. • Examples: • Rao & Miller study • ADBUDG
Rao and Miller Study Idea: • Use natural variations in changes in advertising versus changes in sales across markets to develop a response function. • Use response function to optimize advertising spending.
Advertising Response Function(for a specific brand) 37.5 District 11 30 22.5 District 7 Sales Dollarsper 1,000 Persons per Year District 10 District 5 District 1 15 District 6 District 8 District 4 District 9 7.5 District 3 District 2 0 0 9 18 27 4.5 13.5 22.5 Advertising Dollarsper 1,000 Persons (in the target population) per Year
Relationship between Marginal Sales Created by Advertising and Average Advertising 37.5 District 10 30 District 9 Y District 11 District 8 22.5 District 7 District 4 District 6 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 5 15 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
ADBUDGResponse Model Assumptions • 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. • 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. • There is some advertising rate that will maintain initial share. • 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.
Input—Calibrating Sales Response to Advertising Function Max share at endwith saturation AD Saturation advertising End sharewith +20% AD +20% advertising Share Maintenance advertising Initial Share Zero advertising Min share at end One period Time
Share Response vs Advertisingin 1 Period Max Share Min Maintenance +20% Advertising • Share Response = min + (max – min)(adv)c / [d + (adv)c]
Effective Advertising adv = [media efficiency (t)] ´ [copy effectiveness (t)] ´ [adv dollars (t)]
Adding Time Delays/Carryover • In the absence of advertising, share would eventually decay to some long-run minimum value (possibly zero) • 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 run Persistence = fraction of the difference between “long run min” and amount of share retained with zero advertising
The Full Model Sharet = Long Run Minimum (LRM) + Persistence ´ (Sharet–1 – LRM) + Share Response
Pricing Decisions • Demand/Price Functions • Pricing in Practice • Cost based • Value based • Competition based • Revenue Management
Demand/Price Functions(Linear) Q |b2| > |b1| Elasticity of Q2 is larger than elasticity of Q1. Q1 = a – b1p Quantity (Q) Q2 = a – b2p p Price
Demand/Price FunctionsNonlinear (Constant Elasticity) ConstantElasticity Q Q = aP–b Quantity P Price
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: • focus on short run profit; • focus on immediate customers; • price is independent of advertising, promotion, etc.; • demand and cost functions are known; • unit cost is constant; • firm has true control over price; • competitors are ignored, etc.
Pricing Under DifferentElasticities of Demand Q: Quantity P: Price
Pricing Under DifferentElasticities 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).
Profits at different Elasticities(Lo versus Hi) Example effects of price increases BeforeAfter (Lo)After (Hi) Price 10.00 10.10 +1% 10.10 +1% Quantity 1009890 Revenue 1,000 989.8 909.0 Total Cost 970950.6873.0 Profit 30 39.2 +31% 36.0 +20%
Pricing in Practice Cost-Oriented Pricing (e.g., learning curve analysis)Costs influence prices because they influence supply. Demand-Oriented Pricing (e.g., elasticity analysis Customers influence prices through value-in-use analysis—Ch 2) their influence on demand. Competitor-Oriented Pricing (e.g., competitive bidding)Competitors influence prices through their actions in the marketplace.
Competition-Oriented Pricing: Competitive Bidding • Firm is in competition with an unknown number of suppliers with no (deterministic) knowledge of their prices. • 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 Analysis Approach Q1: Should I bid at all? Q2: If Yes to Q1, what should the bid be? Expected Profit (P) = Win Prob (P) [P – C] where: P = Price, C = Cost of production. è Every (bid) price has a “Win Prob”. How can that Win Prob be estimated?
Assume One Competitor 100% Perhaps “Best Guess” k ´ “Our Cost”, ie, a model of competitive bids.Perhaps for 2 or more competitors, k varies as ki, i = 1, 2, . . . # competitors, (ki is high Ô skimmerki is low Ô penetrator), Chance of Competitor Bidding X or Lower 50% 0% ñBest Guess Competitive Bid (X)
How Much to Bid? 100% 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 = prob. of bidding lower than Competitor 1and Competitor 2 and . . . Competitor n. Competitive Bid Probability Our Win Probability is this area 0% ñOur Bid Competitive Bid (X)
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?
800 Target Price 700 Most Profitable Bid Price calculated 600 Expected Contribution 500 Expected Contribution 400 300 200 100 0 Bid Price Calculating Optimal Bid Price 100 Market Response 80 Likelihood of Winning (%) 60 Market Response Curve 40 X 20 0 Bid Price 1200 1000 Revenue - Costs 800 ContributionMargin 600 Contribution Margin 400 200 0 = -200 Bid Price -400
Differential Pricing First Degree — Charge consumers exactly what they are willing to pay for product (e.g., college tuition) Price Discrimination 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) Third Degree — Divide consumers into distinct segments, charging different prices to different segments (e.g., movie-theater pricing)
Value from….Value to Value from….Value to Service Service Service Service Appropriate Higher Cost Service Level Appropriate Low-cost Service Level Low-Value Customers High Value Customers Balance the value provided to a customer with the price received from the customer. Differential Pricing with Differential Service
Bases for Differential Pricing • Geographic • Temporal (time of making reservation) • Non-linear (Quantity discounts) • Costs of servicing an account • Reference accounts • …….
Revenue Management ThroughTemporal 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. • High fixed cost industries • Service industry (here, we focus on hotels and airlines) • Alternative approaches (temporal price discrimination in the airline/hotel industry) • Time-of-day pricing • Time when purchased • Day of the week pricing • Seasonal pricing
Actual Revenue Data for a Sample Flight Total available seats: 138
Revenue Stream if LowPrice Seats Fill up First Total available seats: 138
Revenue Stream if AirlineKnows Exact Demand Pattern What is the maximum opportunity cost of not having a revenue management system? Total available seats: 138
Implementing Revenue Management • Estimate demand for each class of service. • Demand arrives over time—so update demand function/remaining supply. • Allocate remaining space to: • maximize expected profitability • meet other criteria subject to situation specific constraints.
Revenue Management Process 3-Step Process I: Design II: Seasonal Planning/Allocation III: Daily Management
Revenue Management Process cont’d Step I: Design Specify: • Number of classes of services • Design of each service class • (Average) price/demand curve/class • Total capacity
Revenue Management Process cont’d Step II: Seasonal Planning/Allocation • Specify time path of demand arrival/class • Minimum price difference/class • Seasonal demand adjustments • (Incremental) cost of service Find: • Optimal number of spaces/class • Optimal price/class
Revenue Management Process cont’d Step III: Daily Management • X days before target date • Current booked-to-date by class ðUpdate expected demandUpdate allocation of product to class (upgrade/release higher class of service product)
Example of Revenue Managementin Action Occupancy Rate % 60 days before room-night, a hotel might accept bookings with some discounts. At the same time, some marketing strategies could be pursued. At this point, the hotel might sell rooms only at full rates, assuming that the demand curve will continue. The hotel can use aggressive marketing strategies and discount rooms to reach target occupancy. The demand curve really picks up. The 70% target occupancy is passed 8 days before due date. The hotel goes back to full rates. Decision Points 4 70 Reservation Profile 3 2 1 Actual Reservations Leadtime (days) 45 30 15 0
Revenue Management in PracticeAirlines • Major US domestic carriers: • Operate 5000 flights per day • Serve over 10,000 markets • Offer over 4,000,000 fares • Schedules change twice each week • On a typical day, a major carrier will change 100,000 fares • Airlines offer their products for sale more than one year in advance • The total number of products requiring definition and control is approximately 500,000,000 (various possible routes) • This number is increasing due to the proliferation of distribution channels and customer-specific controls Source: Sabre
1 PHG 01 E 08800005 010710 010710 225300 XXXXXXXX 000000 I 01 1V XXXXXXXX SNA US XXX 05664901 00000000 XXXXXXXXX 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 XXXXXXXX 000000 I 01 1V XXXXXXXX SNA US XXX 05664901 00000000 XXXXXXXXX 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 PHG 01 E 08800005 010710 010712 142000 XXXXXXXX 000000 I 01 1V XXXXXXXX SNA US XXX 05664901 00000000 XXXXXXXXX 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 PHG 01 E 08800005 010710 010716 104500 XXXXXXXX 000000 I 01 1V XXXXXXXX SNA US XXX 05664901 00000000 XXXXXXXXX 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 PHG 01 E 08800005 010710 010717 111500 XXXXXXXX 000000 I 01 1V XXXXXXXX SNA US XXX 05664901 00000000 XXXXXXXXX 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 2 3 4 5 Real-Time Transactions Data for Revenue Management in Airlines Source: Andrew Boyd
Decision Support Systemsfor Revenue Management Source: Andrew Boyd
Profiting from Revenue Management • Use price management, rather than cost cutting to balance supply and demand. • Price according to what the market will bear. • Use differential pricing to reach different segments of customers. • Save the “best product” for the most valuable customers. • Make decisions based on real-time market information. • More fully exploit available resources. • Revenue management is a way to bring discipline into the organization’s decision making process.