Review Pricing a marketing research Value of Information EVPI = |EMVwPI – EMVwoI|

Review

Pricing a marketing research Value of Information

EVPI = |EMVwPI – EMVwoI|EVPI = |EMVwPI – EMVwoI|

2

0

-5

Success

0.5

Failure

0.5

25

0

Approve

Disapprove

Approve

Disapprove

EMV(the best alternative with free perfect info) = 12.5

With perfect information

Approve

Disapprove

Success

0.5

Failure

0.5

25

0

-5

EMV(the best alternative without new info) = 10

Without information

Suppose with 50% of chance, the product will be a great success, bringing $40 million in revenue; and 50% of chance it will be a failure, bringing $10 million.

EVPI = EMVwPI - EMVwoI = 12.5-10 = 2.5millionThe most you are willingness to pay for any information

Example from Previous Class

The estimated R&D cost is estimated to be $20 million and the marketing cost is $5 million.

Suppose with 1/3 of chance, the product will be a great success, bringing $90 million in revenue; with chance of 1/3 it will be a failure, bringing $15 million revenue, and with 1/3 it will be a disaster and will generate zero revenue.

What is the value of the marketing research here? The answer is $11.67 million

1. Identify the status quo course of action when no marketing research (info) is available.

Expected Cost

Expected Revenue

Status quo course of action

2. Identify the scenario(s) in which marketing research will change the course of action.

Scenario # 2

When the revenue is $15 million

Scenario # 3

When the revenue is $0 million

3. Determine the gain conditional on the relevant scenario(s).

Scenario # 2

The conditional gain is

Scenario # 3

The conditional gain is

4. Multiply the conditional gain and the probability for the occurrence of the scenario. Notice that in this case, there are 2

scenarios (#2 and #3) in which the research has the potential to change status quo course of action and be valuable.

Thus, we need to calculate the expected value of the marketing research, accounting for both scenarios.

Expected Revenue

EVA - based on product differentiation

Reference Valueor

Reference Price

PositiveDifferentiation

Value

NegativeDifferentiation

Value

Total Economic Value

+$

- $Final $

8

Importance of Differentiation Value

Selling hot dogs at the street corner of NYC

Your cost

Competitor cost

Case A Case B

Your cost

Competitor cost

WTP

WTP

9

Importance of Having Differentiation Value

Netflix Cleanfilms.com

Inventory

Approx. 100,000 Approx. 1,000

# of distribution center

40+ 1

Price charged For 2 at a time

$17.99 $19.99

Secret of survival?

10

A not-so-fairy-tale ending

• In 2006, Judge Richard P. Matsch of the United States District Court for the District of Colorado ruled that it was a copyright violation to distribute re-edited movies without the consent from the movie studios.

• Cleanfilms.com notified its subscribers the loss of the battle while ensuring them that they commit to rent only the “clean” films. • Cleanfilms.com went out of business soon after.

• The Directors Guild of America and the Motion Picture Association of America sued most of these industry players for copyright infringement and claims regarding derivative works.

11

Value Communication

12

Value Communication

Competitor Our Magazine

Advantage

Circulation 1,400,000 1,550,000 11%

Readers per copy 1.8 2.1

Readership 2,520,000 3,255,000 29%

% See ad 9.20% 14.50%

% Motivated/ad seen

1.6% 2.2%

% Sold/motivated 20% 20%

# Readers sold 742 2077 180%

Sales per customer

$180 $200

Gross margin 30% 30%

Value of ad $40,062 $124,601 221%

Cost of ad $29,000 $67,400

Return on ad $11,062 $57,201

13

Value Measurement (Chapter 13)

3The Strategy and Tactics of Pricing

Techniques for Measuring Price SensitivityTechniques for Measuring Price Sensitivity

• Simulate Purchase Experiments

• Trade-off (Conjoint) Analysis

• Direct Questioning

• Buy-response Survey

• Depth InterviewPreferences and Intentions

• In-store Experiments

• Laboratory purchase experiments

• Historical Sales Data

• Panel Data

• Store Scanner DataActual Purchases

Experimentally ControlledUncontrolledVariable Measured


Cell 1:Uncontrolled Studies of Actual Purchases





• Depth Interview

Preferences and Intentions




• Panel Data

• Store Scanner Data

Actual Purchases

Experimentally Controlled

UncontrolledVariable Measured

Measuring Price Sensitivity: Uncontrolled Conditions

“+” Easy availability of data

“-” Reliability (confounding factors such as such as number of brands, number of competitors, competitors actions, frequency of advertising, and changes in the economic condition)

Appropriate for existing products Inappropriate for pricing new products or when a new pricing strategy is being introduced that has not been implemented by the company in the past.

Using Past Data

Measuring Price Sensitivity: Uncontrolled ConditionsAnalysis of Historical Data

Historical data is used to develop models that explain sales of goods and services.

Models are usually regression models (econometrics).

Models are limited by the range of data provided and the quality of the data.

The assumption is that the past is a good indicator of the future.

Example: Measuring New Home Sales


Aggregate Sales Data

Data is typically collected on weekly or monthly cycles and aggregated across retail outlets. Data can generally be broken out by retail channel.

“+” Cheap Abundant

“-” Interpretation issue Lack of statistical power

Appropriate for Inappropriate for


Panel Data Consumers keep track of purchases (size, amount, price, where purchased, when purchased, etc.). Consumer diaries are then aggregated to provide market information and brand by brand information. “+”

Short time horizon. Individual-level prices Demographics info. Competitor Information

“-” Biased sample of population Buyer identity


Scanner Data

Data is collected on a store-by-store basis (prices and volume of sales data are collected). Can be linked with demographic information.

“+” More representative sample

“-” Lack of competitor information

Appropriate for Inappropriate for


Cell 3:Uncontrolled Studies of Preferences and Intentions





• Depth Interview





• Panel Data


Actual Purchases



• “-” Direct questioning regarding willingness-to-play potentially highly misleading.

• “+”• Data cheap and quick to collect • Can be used to measure WTP of durable/expensive products• Useful for obtaining detailed information for making economic value calculations.

• Buy-response surveys present the respondent with a price and ask if he or she would buy at that price. Since this question is structured more like a purchase, with no opportunity to bargain, the responses are more reasonable.



Cell 2:Experimentally Controlled Studies of Actual Purchases





• Depth Interview





• Panel Data


Actual Purchases



Measuring Price Sensitivity: Controlled Conditions

In-Store Purchase Experiments

Most common method is to use two or more retail outlets that have similar characteristics (experiment and control).

“+” Ability to disentangle price and other promotion

“-” Can be extremely expensive. Competitors’ actions can contaminate results (special sales promotions, advertising)

Appropriate for products sold through

Inappropriate for products of


Laboratory Purchase Experiments

These experiments attempt to simulate the real store purchase experience. Mall intercepts an example of laboratory experiments.

Very adaptable.

“+” Inexpensive. High validity Control for demographics

“-” Artificial (Heightened consumer awareness)

Appropriate for products that are

Inappropriate for products that are


Cell 4:Experimentally Controlled Studies of Preferences and Intentions





• Depth Interview





• Panel Data


Actual Purchases



Difference between laboratory experiment and simulated experiment “+” Conjoint analysis can be conducted very quickly and at a low cost.

“-” Validity

Appropriate for determining what familiar attributes to include (and at what levels to include them at) during the product/service design process.

Inappropriate for attributes that are


Conjoint Analysis

Most methods used to calculate consumer preference are compositional. For example, consumer ratings of attribute importance represent a compositional approach.

Conjoint analysis is a decompositional approach to measuring consumer preferences. Consumers rate a product while evaluating several product attributes simultaneously.

Conjoint Analysis

Consumer preference data is collected for several product configurations.

Product configurations are presented such that various trade-offs can be assessed on a monetary basis.

Data can be reported on an individual or aggregate basis, which is useful for segmenting a market based on price or other product attribute.

Sensitivity analysis can be conducted with the data to assess the impact that changes in attributes have on price sensitivity.


Discussion Questions

For each scenario below, which method should be used to measure price sensitivity?

– You want to determine price sensitivity for an existing brand oforange juice.

– You are a long distance telephone company trying to determine what causes price sensitivity and how price sensitive consumers are in their selection of a long distance telephone service.

– You are a hotel chain trying to determine what features to include in a room (color TV, free toiletries, etc.).

– You are a laundry detergent maker introducing a flanking brand and want to see how many sales you will take away from your flagship brand as well as from competitors' brands. It is important, however, that competitors not find out about the test. Otherwise, they will be forewarned of the new brand's introduction.

Next Lecture

Cost and cost-plus pricing, BEP

Read Chapter 1

Documents

Review Pricing a marketing research Value of Information EVPI = |EMVwPI – EMVwoI|