Appendix E: Conjoint Analysis

Transcription

1 Relative importance VI Appendix E: Conjoint Analysis Price is most important for the senior consumers in this case. Followed by Golden Age channel, other channels, and movie frequency Cable Channel Package: Relative Importance Relative importance of each attribute Attribute Relative importance Movie frequency 11% Golden Age channel 28% Price 37% Other channels 24% Total 100% Can also be used to identify customer segments with different price sensitivities Helps identify the combination of attributes to price and target buyers. Can be done before the product is developed. Source: Allison et al. (1992), Conjoint analysis, American Marketing Association

2 Works best for products that are evaluated by consumers based on their attributes rather than products chosen base on their image (i.e. beer or cigarettes). 322 Attribute Positioning Include price as one of the attributes describing a product or a purchase situation. Consumers rate the importance of each attribute using a variety of scaling techniques. Those scales can be a 1 to 5 or a 1 to 10 importance. Profitable 324 Decision Making, Second Edition 1995 The foundation of this research technique is the assumption that a product can be disaggregated into individual attributes. - (e.g. A TV has attributes such as size, price, model style, etc.) 323 A non-technical discussion of applications specifically to pricing, see Patrick J. Robinson, Applications of Conjoint Analysis to Pricing Problems, in Market Measurement and Analysis pp

3 Attribute-Importance: Example for MP3 Player (Scale 1-10) Attributes: Price Quality Styling User friendliness Battery life Customer service Sound Quality Size & weight Storage capacity 326 Trade-off (or conjoint) Analysis Popular for measuring price sensitivity as well as sensitivity to other product attributes However, trade-off analysis does not simulate the actual purchase experience. Consumer is encouraged to put much more attention on specific product attributes than in real life situation. Trade-off Analysis Helps disaggregate a product s price into the value given for each attribute by consumers

4 Controlled Experiment #1: Conjoint Analysis 330 Attribute-Importance: Example for MP3 Player Attributes: Quality Styling Price User friendliness Battery life Customer service Sound Quality Size & weight Storage capacity 332 Attribute Positioning Include price as one of the attributes describing a product or a purchase situation. Consumers rate the importance of each attribute using a variety of scaling techniques. Those scales can be a 1 to 5 or a 1 to 10 importance. Profitable 331 Decision Making, Second Edition 1995 Conjoint analysis: the value of a product is equal to the sum of the utility the consumers derive from all the attributes of the product

5 Works best for products that are evaluated by consumers based on their attributes rather than products chosen base on their image (i.e. beer or cigarettes). s.gif 334 The foundation of this research technique is the assumption that a product can be disaggregated into individual attributes. - (e.g. A TV has attributes such as size, price, model style, etc.) 336 Product preference and the likelihood to buy it are in proportion to the utility a consumer gains from the product. 3 Phases of Conjoint Analysis

6 Researcher gets data by asking respondents to make choices between different levels of two product attributes. This enables the researcher to predict the prices which the consumer would pay for a product of various combinations of attributes Permits the researcher to identify the value (utility) that a consumer attaches to each product attribute trade-off analysis promises useful information for strategy formulation. Calculating price elasticity from consumer preferences. The researcher can do more than identify the price sensitivity

7 Can also be used to identify customer segments with different price sensitivities Helps identify the combination of attributes to price and target buyers. Can even be used before the product is developed. Trade-off analysis Developed initially by Paul E. Green and Vithala R. Rao, Conjoint Measurement for Quantifying Judgmental Data, Journal of Marketing Research 8 (August 1971) However, trade-off analysis does not simulate the actual purchase experience. Consumer is encouraged to put much more attention on specific product attributes than in real life situation. 343 A non-technical discussion of applications specifically to pricing, see Patrick J. Robinson, Applications of Conjoint Analysis to Pricing Problems, in Market Measurement and Analysis pp

8 Conjoint Analysis Methodology A standard market research tool regularly used since Used to measure the trade-offs people make in choosing between products, service providers, and product features. 346 Each attribute has several levels, indicating different aspects of the attribute. A questionnaire selects several product attributes and levels in order to test a variety of product combinations Questionnaire An interaction questionnaire measures consumer perception of products. The first step is to collect data. Participants are asked to respond to different product attributes. 347 Example: Attribute/Level grid Golden Years Cable Channel Attributes Movie Aired Frequency Price Programs Level 1 5 per day Level 2 0 Level 3 1 per day 12% more than you'd expect to pay About what you'd expect to pay 10% less than you'd expect to pay Excludes sports programs Excludes romance programs Includes all types of 349 programs 8

9 Example: Conjoint Tasks If two cable channels were identical in every way, how important would the DIFFERENCE between two cable channel profiles be to you? 1 movie aired per day 10% less than you d expect to pay No romance programs 5 movies aired per day About what you d expect to pay All types of programs Questionnaire conclusions The conjoint/decision tasks and the final selection exercises are completely interactive In the last questionnaire step, participants are given profiles (which contain all the examined attributes) of the test product or service, and are asked to express the likelihood they would purchase such it on a 100 point scale. 351 There are computer package (i.e. ACA TM, Adaptive Conjoint Analysis) that generate an optimal set of trade-off tasks for each participant. The tasks are derived from participant information on which attributes they value

10 2. Statistical Analysis of the Data Conjoin analysis: examines the variation in respondent choice, thus calculating a utility for each level of each attribute. Features which a respondent is reluctant to give up from one choice task to another is considered to be of higher utility Utility: a measurement of a consumer s relative strength of preference for each level of each product attribute. index numbers that measure how valuable or desirable a particular feature is to the respondent. 355 Estimating utilities A least squares updating algorithm is used to estimate consumer utilities. Initial estimates are based on the participant s rank orders of preference and his/her ratings of attribute importance

11 These estimates are updated after each trade-off task. Therefore the initial estimates have decreasing influence as the interview progresses. For modeling purposes, the final estimates are scaled in order for the sum of each participant s utilities accurately predicts his/her likelihood of buying the product The final estimates are true least squares, with the same weight being applied to each of the participant s answers. 359 However, when reporting aggregates or comparing segments, utilities must be rescaled so that the sum of the differences between the maximum and minimum level of each attribute equals the number of attributes times

12 The best method to analyze the utilities is to examine the gaps between utility levels within an attribute. the gap differentiates the importance between utility levels within an attribute. 362 For example, if the attributes Price and TV size have average importance scores of 5.1 and 2.5 respectively, it does not mean that Price is more important than TV size. /images/big_screen.jpg 364 The algorithm for this statistical analysis is highly complex. Therefore a computer program will most efficiently tabulate the data. Once the utility values are derived, we can compare attribute preferences. 363 Conjoint analysis reveals that on average, participants perceived that the difference between a price of 10% more than you d expect to pay and a price of 10% less than you d expect to pay as more important than the difference between TV sizes and 365 screen styles. 12

13 The absolute values of the utilities have no inherent meaning. The importance of this research technique is in the calculation of the range between the lowest and highest levels of utility value within each attribute. 366 examine the effect of alternative product profiles using a market simulator. 368 Utility values and importance scores can be used to parse populations into homogenous groups to: predict preference or acceptance among groups with homogenous utility values Market Simulation Describes each product (TV set) profile in terms of its attributes Adds the participant s value for all of a product s attributes and uses this data to determine the relative value of each product to each participant

14 Sample Chart: Acceptance likelihood is calculated by adding up the sums of the attribute level utilities contained in the product profile. (Attribute Levels) The chart shows: products that contain attribute levels for which respondents have higher utility values, produce a higher degree of acceptance likelihood. 371 Data Collection The participants are first asked to rank order their preference for the various levels within each attribute. this step is important, because preference for various levels may not be linear

15 Ranking Sample Conjoint Tasks Preference Ratings/Rankings 5 per day Please rate each of the following aspects of Movie Aired Frequency in terms of how desirable they are, assuming all other aspects are equal Extremely Undesirable Extremely Desirable Sample question: If two cable channels were the same in every way, how important would the difference between the two features shown below be to you? If two cable channels were identical in every way, how important would the DIFFERENCE between the two features shown below be to you? 0 1 per day P&B LLC DBA POPULUS Next, the participant is asked, how important the difference between different levels of a single attribute is to them. This provides the researcher with information on the distance (of preference) between levels of an attribute. 375 Conjoint Tasks Once data have been collected, participants are given to choose from pairs of cable channels (conjoint tasks). Each profile describes 2-4 attributes. Participants are asked which of the two channel descriptions they prefer more

16 It is acceptable to repeat the conjoint task procedure several times to gather information on preference for the various attributes and levels. 378 Example: Attribute/Level grid Golden Years Cable Channel Attributes Movie Aired Frequency Price Programs Level 1 5 per day Level 2 0 Level 3 1 per day 12% more than you'd expect to pay About what you'd expect to pay 10% less than you'd expect to pay Excludes sports programs Excludes romance programs Includes all types of 380 programs Example: Conjoint Tasks If two cable channels were identical in every way, how important would the DIFFERENCE between two cable channel profiles be to you? 1 movie aired per day 10% less than you d expect to pay No romance programs 5 movies aired per day About what you d expect to pay All types of programs 379 Example: Cable TV Packages A cable company is selling different packages to its customers. These vary in: Price Movie aired frequency Sports channel (yes/no) Other channels on top

17 Cable TV Package Options Attribute Movie aired frequency Levels of attributes measured in survey Level 1 per day 2 per day 3 per day 4 per day Sports channel Yes No Price $10 $12 $14 $16 Computation of utilities Respondents were asked to imagine 8 different packages, differing only in two attributes. Other channels 1 channel 2 channels 3 channels 4 channels All possible variations would be 4 x 2 x 4 x 4 = 128 Too complicated to have consumers rank all of these options. That s why some product concepts have to be chosen. Computation of utilities Sample questionnaire and a movie aired frequency of 4 per day 3 per day 2 per day 1 per day You could have a sports channel Yes No 1 most preferred, descending Source: Kotler (1997), Marketing Management

18 Computation of utilities Trade-off matrix I Movie aired frequency Yes Sports channel No 4 per day per day per day 3 7 Computation of utilities Trade-off matrix III Sports channel Other channels 4 channel 3 channels 2 channels 1 channels Yes No per day Computation of utilities Trade-off matrix II Computation of utilities Trade-off matrix IV Sports channel Price $10 $12 $14 $16 Yes No Other channels Price 4 channel 3 channels 2 channels 1 channels $ $ $ $

19 Computation of utilities Trade-off matrix V Movie aired frequency Other channels 4 channel 3 channels 2 channels 1 channels 4 per day per day Computation of utilities Depending on the answers, utilities are derived by a statistical program. 2 per day per day Source: Kotler (1997), Marketing Management 392 Computation of utilities Trade-off matrix VI Movie aired frequency Price $10 $12 $14 $16 4 per day per day per day per day Computation of utilities Example for pairwise products of utilities Movie aired frequency Yes Sports channel No per day.4.28 (1).09 (5) 3 per day.3.21 (2).06 (6) 2 per day.2.14 (3).06 (7) 1 per day.1.12 (4).03 (8)

20 Example of a respondent s utilities Attribute Level Utility Attribute Level Utility Movie aired frequency Sports channel 4 per day.315 Price $ per day.311 $ per day.271 $ per day.103 $ Yes.769 Other 4 channels.471 No.231 channels 3 channels channels channels.001 Relative importance II First step: Calculating the range for each attribute Range = Highest utility Lowest utility for that attribute 394 Source: Allison et al. (1992), Conjoint analysis, American Marketing Association 396 Relative importance I Using these utilities, the relative importance is calculated. Relative importance points out which attributes influence the consumer most. Source: Allison et al. (1992), Conjoint analysis, American Marketing Association 395 Relative importance III Attribute Range for each attribute Range Movie aired channel.212 Sports channel.538 Price.728 Other channels.470 Total Source: Allison et al. (1992), Conjoint analysis, American Marketing Association

21 Relative importance IV Second step: Calculating the relative importance of each attribute Relative importance = Range / Total range Relative importance VI Price is most important for the consumers in this case. Followed by sports channel, other channels and movie aired frequency. Source: Allison et al. (1992), Conjoint analysis, American Marketing Association Relative importance V Relative importance of each attribute Attribute Relative importance Movie aired channel 11% Sports channel 28% Price 37% Other channels 24% Total 100% Respondent s utilities for selected packages I For each package the overall utility is calculated. Overall utility = Sum of all weighted average utilities Source: Allison et al. (1992), Conjoint analysis, American Marketing Association 399 Source: Skiera/Gensler (2002), Berechnung von Nutzenfunktionen und Marktsimulationen mit Hilfe der Conjoint-Analyse (Teil II)

22 Respondent s utilities for selected packages II Nr. Other channels Package Configuration Sports channel Movie aired frequency Price Utilities Overall Utility 1 4 channels Yes 2 per day $ = channels No 3 per day $ = channels Yes 1 per day $ = channels No 4 per day $ = channels Yes 4 per day $ = channels No 3 per day $ = channel Yes 2 per day $ = channel No 3 per day $ = Example result II The configuration package number 5 with the lowest price, 2 extra channels, a sports channel and a movie aired frequency of 3 per day is the most preferred. 404 Example result I First package would have been the most attractive, but the price is too high