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MRKT 354
Marketing Management II

Session 7
Market Simulator
Overview
•
•
•
•

Building Blocks
Choice Rules
Market share forecasting
Profit forecasting

Menu
Market simulator
Excel Solver

Price

Manual Input

Product Characteristics

Product Specification

Competing products

In...
Market share forecasts
• Market simulators
– What-if scenarios to evaluate marketing strategies
– Select a set of products...
Computation steps
step 1: conjoint analysis

Partworths for attribute levels
step 2: multi-attribute utility model

Utilit...
Building blocks: Profile space
•

Profile space
Brand
Apple
Blackberry

Touch screen

Samsung
•

User
interface

Price

Ke...
Building blocks: Competitors
•

Who are the important competitors?
–
–
–

•

Customer view: look for substitutes for your ...
Building blocks: Market
• Market = your product + competitors’ products

you

Apple

Touch screen

$249

competitor 1

Bla...
Building blocks: Customers
•

Customer = partworths (each customer is a row of numbers)

Customer

Brand:
Apple

Brand:
Bl...
Exercise: Would Alex buy your product?
•

Alex: partworths (each customer is a row of numbers)

Customer

Brand:
Blackberr...
Help: Would Alex buy your product?
Customer

Brand:
Blackberry

Brand:
Samsung

User
interface:
keyboard

User
interface:
...
Solution - Utility Calculation for Alex
Brand

Price

You

Apple

Touch screen

$249

Competitor 1

Blackberry

Touch scre...
Exercise #2 – Choice Prediction
Highlight the product

Table 1

Custom
er

Brand
:
Apple

Brand:
Blackber
ry

Brand:
Samsu...
Exercise #3 – Market Share Forecast
Question: Add the number of customers purchasing each product and
compute market share...
What was the choice model used here?
Utility
of
your
product

Utility
of
Comp 1

Utility
of
Comp 2

•

How sure are you Co...
Choice rules
•

Maximum utility rule (deterministic): predict that an individual will always buy the
option with the highe...
Logit Model Rule

• Robust, industry standard
• Theoretically sound: related to maximizing utility, Nobel price (2000) to ...
Logit Model Rule Example: Alex
•

Suppose we take c = 0.1

Utility (U)

c*U

Exp(c*U)

Choice probability

You

45

4.5

9...
The Role of Confidence Parameter
Utility
of
your
product

40

25

35

40

25

Colin

27.5

40

22.5

Danielle

7.5

10

32...
How can we determine c?
• It is possible to use a choice-task as part of your ratings-based conjoint
• In practice, we oft...
Logit model choice rule: Summary
• Works for arbitrary number of products:

• Interpretation: exp(c*Uia) ~ attractiveness ...
Shape of Logit
Market shares
• Prediction of market share is the average of
the individual level probabilities of choice

ˆ
SA

1
N

i

e...
Profit Forecast
• We need marginal cost function and size of the
market in addition to market share forecast
• 1. Compute ...
Exercise #4 – Profit Forecast
•
•

A medical equipment manufacturer is looking into a new testing device. It has identifie...
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Conjoint Analysis Part 3/3 - Market Simulator

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Market simulator based on conjoint analysis

Published in: Marketing, Technology, Business
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Conjoint Analysis Part 3/3 - Market Simulator

  1. 1. MRKT 354 Marketing Management II Session 7 Market Simulator
  2. 2. Overview • • • • Building Blocks Choice Rules Market share forecasting Profit forecasting Menu
  3. 3. Market simulator Excel Solver Price Manual Input Product Characteristics Product Specification Competing products Individual partworths Market share forcasting Market Shares Cost Demand Profit Market Simulator
  4. 4. Market share forecasts • Market simulators – What-if scenarios to evaluate marketing strategies – Select a set of products to represent the market • Often start with the current market as base case – Each product is represented by its levels on each feature – Use each respondent’s utility function to calculate his/her utility for each product in the choice scenario – use a decision rule to predict choice for each consumer – Aggregate the predicted choice (probability) across respondents to calculate predicted market shares Us Us+them
  5. 5. Computation steps step 1: conjoint analysis Partworths for attribute levels step 2: multi-attribute utility model Utilities for competing products step 3: choice model Probabilities of choice individual level step 4: straight addition Market share forecasts aggregate level Us Us+them
  6. 6. Building blocks: Profile space • Profile space Brand Apple Blackberry Touch screen Samsung • User interface Price Keyboard Any price $99 to $399 Suppose we are Apple, and our product is: Apple Touch screen $249
  7. 7. Building blocks: Competitors • Who are the important competitors? – – – • Customer view: look for substitutes for your product Perceptual maps helpful Better to include too many rather than too few: conjoint will deal with lack of actual competition, but it cannot magically account for an excluded competitor Simplistic example: 2 competitors Blackberry Touch screen Samsung Keyboard $199 $149
  8. 8. Building blocks: Market • Market = your product + competitors’ products you Apple Touch screen $249 competitor 1 Blackberry Touch screen $199 competitor 2 Samsung Keyboard $149
  9. 9. Building blocks: Customers • Customer = partworths (each customer is a row of numbers) Customer Brand: Apple Brand: Blackberry Brand: Samsung User interface: keyboard User interface: Touch screen Price: Utility $99 vs. $399 Alex 20 10 0 0 10 30 Bonnie 10 10 0 0 10 30 Colin 0 10 10 0 20 15 Danielle 0 0 0 20 0 15 Ella 0 20 0 0 0 15 Utility function = sum of product’s partworths
  10. 10. Exercise: Would Alex buy your product? • Alex: partworths (each customer is a row of numbers) Customer Brand: Blackberry Brand: Samsung User interface: keyboard User interface: Touch screen Price: Utility $99 vs. $399 Alex • Brand: Apple 20 10 0 0 10 30 Market: choice-sets Brand User interface Price You Apple Touch screen $249 Competitor 1 Blackberry Touch screen $199 Competitor 2 Samsung Keyboard $149 Utility
  11. 11. Help: Would Alex buy your product? Customer Brand: Blackberry Brand: Samsung User interface: keyboard User interface: Touch screen Price: Utility $99 vs. $399 Alex • Brand: Apple 20 10 0 0 10 30 Reminder on how to interpret the price partworths – – – • For other price points: use interpolation – – • Partworth for $99 is 30 utils Partworth for $399 is 0 utils Partworth Gap = 30 uitls Partworth for $L is (MaxPrice – L) * (partworth gap)/(MaxPrice – MinPrice) In this case this interpolation formula becomes: Partworth for $L = (399 – L) * 0.1 Now calculate utility for each product
  12. 12. Solution - Utility Calculation for Alex Brand Price You Apple Touch screen $249 Competitor 1 Blackberry Touch screen $199 Competitor 2 • User interface Samsung Keyboard $149 Alex is most likely to buy ( ) – Key idea: utility maximization (We can predict what each customer will buy) Utility
  13. 13. Exercise #2 – Choice Prediction Highlight the product Table 1 Custom er Brand : Apple Brand: Blackber ry Brand: Samsu ng User interfac e: keyboar d User interface: Touch screen Price: Utility $99 vs. $399 Utility of your product Utility of Comp 1 Utility of Comp 2 Alex 20 10 0 0 10 30 45 40 25 Bonnie 10 10 0 0 10 30 35 40 25 Colin 0 10 10 0 20 15 27.5 40 22.5 Danielle 0 0 0 20 0 15 7.5 10 32.5 Ella 0 20 0 0 0 15 7.5 30 12.5 you • Question: Highlight the product chosen by each customer in Table 1. Assume that customers choose the product which gives the maximum utility with the probability of 1 (deterministic choice rule.) Comp 1 Comp 2 Apple Black berry Sam sung Touch screen Touch screen Keyboa rd $249 $199 $149
  14. 14. Exercise #3 – Market Share Forecast Question: Add the number of customers purchasing each product and compute market shares in Table 2. Custom er Brand : Apple Brand: Blackber ry Brand: Samsu ng User interfac e: keyboar d User interface: Touch screen Price: Utility $99 vs. $399 Utility of your product Utility of Comp 1 Utility of Comp 2 Alex 20 10 0 0 10 30 45 40 25 Bonnie 10 10 0 0 10 30 35 40 25 Colin 0 10 10 0 20 15 27.5 40 22.5 Danielle 0 0 0 20 0 15 7.5 10 32.5 Ella 0 20 0 0 0 15 7.5 30 12.5 Table 2 • Forecast: you Comp 1 Comp 2 Product # persons buying % share Apple Black berry Sam sung Your product ( ) ( )% Competitor 1 ( ) ( )% Touch screen Touch screen Keyboa rd Competitor 2 ( ) ( )% $249 $199 $149
  15. 15. What was the choice model used here? Utility of your product Utility of Comp 1 Utility of Comp 2 • How sure are you Colin will buy Comp 2? Alex 45 40 25 • Bonnie 35 40 25 How sure are you Alex will buy your product? Colin 27.5 40 22.5 Danielle 7.5 10 32.5 • Ella 7.5 30 12.5 you Comp 1 Comp 2 Apple Black berry Sam sung Alex gets 0.1 utils per dollar saved (5 utils / $50). What if Blackberry (comp 1) discounts by $50? What will Alex buy? Touch screen Touch screen Key board $249 $199 $149
  16. 16. Choice rules • Maximum utility rule (deterministic): predict that an individual will always buy the option with the highest estimated utility – Simple to apply – Puts too much confidence in our utility measurement, not empirically valid – Unstable: the entire prediction can tip with a miniscule discount Improvement idea: assign probability of choice instead of 0/1! • Logit model (probabilistic): predict that an individual will most likely buy the option with the highest fitted utility, but there is some uncertainty.
  17. 17. Logit Model Rule • Robust, industry standard • Theoretically sound: related to maximizing utility, Nobel price (2000) to Daniel McFadden for developing this model • c = confidence parameter ~ how confident are you in your utility estimates?
  18. 18. Logit Model Rule Example: Alex • Suppose we take c = 0.1 Utility (U) c*U Exp(c*U) Choice probability You 45 4.5 90.02 90.02/[90.02+54.6+1 2.18]=0.57 Competitor 1 40 4 54.60 54.60/[90.02+54.6+1 2.18]=0.35 Competitor 2 25 2.5 12.18 12.18/[90.02+54.6+1 2.18]=0.08
  19. 19. The Role of Confidence Parameter Utility of your product 40 25 35 40 25 Colin 27.5 40 22.5 Danielle 7.5 10 32.5 Ella • 45 Bonnie Low confidence (c=0.01) Utility of Comp 2 Alex • Utility of Comp 1 7.5 30 12.5 Medium confidence (c=0.1) • High confidence (c=1) Custom er You Comp 1 Comp 2 Custom er You Comp 1 Comp 2 Custom er You Comp 1 Comp 2 Alex 36% 34% 30% Alex 57% 35% 8% Alex 99% 1% 0% Bonnie 34% 36% 31% Bonnie 33% 55% 12% Bonnie 1% 99% 0% Colin 32% 37% 31% Colin 20% 68% 12% Colin 0% 100% 0% Danielle 30% 31% 39% Danielle 7% 9% 84% Danielle 0% 0% 100% Ella 30% 38% 32% Ella 8% 78% 14% Ella 0% 100% 0% Share 33% 35% 32% Share 25% 49% 26% Share 20% 60% 20%
  20. 20. How can we determine c? • It is possible to use a choice-task as part of your ratings-based conjoint • In practice, we often use – c = 100/ [12 * Max of Rating Scale] • With 100 point rating scales, this gives – c = 100/1200 = 0.083 (a reasonable value based on dozens of past studies)
  21. 21. Logit model choice rule: Summary • Works for arbitrary number of products: • Interpretation: exp(c*Uia) ~ attractiveness of product A to person I, and logit is just ratio of attractiveness to total attractiveness of market offerings
  22. 22. Shape of Logit
  23. 23. Market shares • Prediction of market share is the average of the individual level probabilities of choice ˆ SA 1 N i exp( c U iA ) exp( c U ij ) j Us Us+them
  24. 24. Profit Forecast • We need marginal cost function and size of the market in addition to market share forecast • 1. Compute predicted market share s(P,p) • 2. Compute predicted marginal costs c(P) • 3. Compute predicted profit = {# of customers x s(P,p)} x {p – C} Us Us+them
  25. 25. Exercise #4 – Profit Forecast • • A medical equipment manufacturer is looking into a new testing device. It has identified a number of key product characteristics among which price and accuracy are deemed the most important. The company issued a conjoint analysis which you carried out. It turned out only two types of customers exist in this market. Segment 1 is 60% of the market, segment 2 is 40% of the market. The following table of partworths at the segment level was obtained. Attribute Level Price Accuracy $13,000 Segment 1 0 20 Segment 2 • $15,000 0 15 $11,000 99.9% 99% 95% accuracy accuracy accuracy 40 55 25 0 30 15 10 0 The total size of the market is 100 units. The competition consists of only one firm. It offers a midpriced (i.e. price = $13,000) testing device that delivers 99% accuracy. Your costs to manufacture and develop the various levels of accuracy are as follows Costs Variable Fixed 99.9% accuracy 11000 200000 99% accuracy 10000 150000 95% accuracy 9500 50000 • • If you decide to launch the me-too option the best you will be able to do is to get half of the market and you can maximally charge the price of your competitor. Consider two product launch options: (A) 99.9% accuracy at price of $15,000, (B) 95% accuracy at price of $11,000. Which product would be more profitable for you to launch in this market? Show your work by calculating expected profit for each option. (Note: Assume that the utility differences are large enough to use the deterministic maximum utility rule.)

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