1. One major difference between lab purchase experiments and simulated purchase experiments is that participants only simulate the choice decision to purchase a product and so do not keep their choices in a simulation. Simulated purchase experiments are a good way to gain quick and low-cost information on buying behaviors but are often prone to bias.
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2. Actual purchase studies measure behavior, while preference-intention studies measure the intended choices that people claim they would make in a typical purchasing scenario. Preference-intention studies are generally more desirable but is usually more expensive and time-consuming than actual purchase studies.
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3. Controlled research produces more accurate estimates of the effects of the controlled variables on price sensitivity but could be very expensive to implement. Experimentally controlled studies of actual purchases may include in-store purchase experiments and lab purchase experiments. One benefit of lab purchase experiments is the ability to control the experiment to draw inferences from fewer purchases in less time compared to in-store experiment.
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4. Two reasons why companies prefer to measure preferences or intentions, rather than actual purchases include:
Survey data can be collected even before the product is designed
Purchase data costs less to collect than survey data
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5. Buy-response surveys provide more meaningful responses related to willingness to buy compared to direct questioning, both of which are uncontrolled studies of preferences and intentions. This is because it is structured more like an actual purchase decision rather than an open-ended question.
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6. Managers tend to form judgments about buyers based on qualitative observations then attempts to measure aspects of buyer behavior using quantitative research techniques. Although managerial judgment is important in the price sensitivity measurement because it helps determine the focus of the research and reduces random error and statistical problems, many companies fail to use managerial input leading to disappointing price sensitivity measurements.
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7. In-store or sophisticated lab purchase experiments should not be the first choice for frequently purchased, low-cost products because such products are bought by consumers who have low price awareness and give the purchase decision little attention.
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8. Store scanner data can generate accurate sales and price data and can be combined with panel data to track the demographic behavioral characteristics of consumers. Panel data is collected by marketing research companies from a sampling of households, who record brands purchased and prices or use special credit card to track purchases. One main advantage is that panel data is very representative of the market as a whole and collects data on everyone in the household.
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9. The simplest design for an in-store pricing experiment involves monitoring sales at the historical price to obtain a base level of sales and then initiating a price change to see how sales change from the base level. By adding a control store to the process, the researcher can identify any factors other than price that may cause changes in sales, such as other marketing variables.
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10. Trade-off analysis (also called "conjoint analysis") helps to identify the differentiation value of specific product attributes and design products with attributes customers are more willing to pay for. The researcher collects data by asking the respondent to make choices between pairs of products or levels of attributes for a specific product. The researcher then computes the value attached to each product attribute and predicts the prices the consumer would purchase the product for in the marketplace. Of all methods used to estimate price, conjoint analysis tends to provide the most useful information and strategy.
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11. In-depth interviews, typically used for controlled preferences and intentions, involves one-on-one interviews with a consumer. They help researchers understand which product/service features and benefits are important to consumers, assess monetary and psychological value of those features and benefits, as well as the customer's willingness to pay.
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12. Linear regression analysis is usually involved in synthesizing historical data to obtain the relationship between price and sales. Regardless of how well an estimated equation fits past data, its value in predicting the effect of future price changes is limited to past behaviors and data.
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13. Online research is generally less expensive and much faster than traditional research methods and tends to have better response rates. Online respondents are also representative of the entire market, allowing researchers to generalize their findings to the broader target population.
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14. A product that exists in the market for a while would have historical data available, allowing managers the ability to generate useful marketing decisions. Even if historical data has random variations, they may still provide possible directional relationships between price, sales or other marketing variables that could be examined using other research techniques.
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15. There are several different ways to measure and estimate price sensitivity and they vary in terms of advantages/disadvantages in cost, accuracy, and applicability. As a result, it is recommended that managers use the technique that is cheapest, fastest or more convenient for a given situation.
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