How can you use the expectancy-value model for consumer decision-making in market research?

1 Benefits of the model

The expectancy-value model can help you understand the drivers and barriers of consumer choice, as well as the trade-offs and compromises they make. By identifying the key attributes that influence consumer attitudes, you can design better products or services that match their needs and expectations. You can also segment your market based on different expectancy-value profiles, and tailor your marketing messages accordingly. The model can also help you test the impact of changes in attributes, prices, or promotions on consumer preferences and behavior.

2 How to apply the model

To apply the expectancy-value model, you must first define the relevant alternatives and attributes for your product or service category. Afterwards, you should conduct a survey or focus group to collect data on consumer beliefs and preferences for each alternative and attribute. These beliefs and preferences can be measured using scales, rankings, or ratings. Then, calculate the expectancy and value scores for each attribute and alternative using formulas or statistical methods. Lastly, multiply the expectancy and value scores to obtain the attitude scores for each alternative and attribute. Finally, compare the attitude scores across alternatives and attributes to interpret the results.

3 Example of the model

Let's say you want to use the expectancy-value model to understand consumer decision-making for buying a laptop. You define four alternatives (A, B, C, and D) and four attributes (performance, design, price, and warranty). You conduct a survey and collect data on consumer beliefs and preferences for each alternative and attribute. You calculate the expectancy and value scores using a five-point scale, where 1 means low and 5 means high. You multiply the expectancy and value scores to obtain the attitude scores. The table below shows the results.

| Alternative | Attribute | Expectancy | Value | Attitude |

|-------------|-----------|------------|-------|----------|

| A | Performance | 4 | 5 | 20 |

| A | Design | 3 | 4 | 12 |

| A | Price | 2 | 3 | 6 |

| A | Warranty | 4 | 2 | 8 |

| A | Total | | | 46 |

| B | Performance | 3 | 5 | 15 |

| B | Design | 4 | 4 | 16 |

| B | Price | 3 | 3 | 9 |

| B | Warranty | 3 | 2 | 6 |

| B | Total | | | 46 |

| C | Performance | 5 | 5 | 25 |

| C | Design | 2 | 4 | 8 |

| C | Price | 1 | 3 | 3 |

| C | Warranty | 5 | 2 | 10 |

| C | Total | | | 46 |

| D | Performance | 2 | 5 | 10 |

| D | Design | 5 | 4 | 20 |

| D | Price | 4 | 3 | 12 |

| D | Warranty | 2 | 2 | 4 |

| D | Total | | | 46 |

As you can see, all the alternatives have the same total attitude score, which means that consumers are indifferent among them. However, you can also see that different attributes have different weights and impacts on consumer attitudes. For example, performance is the most important attribute, followed by design, price, and warranty. You can also see that alternative C has the highest performance score, but the lowest price score, while alternative D has the opposite pattern. This suggests that consumers have different trade-offs and compromises when choosing a laptop.

4 Limitations of the model

The expectancy-value model is a useful tool for consumer decision-making in market research, however, it is not without its limitations. It assumes that consumers are rational and consistent in their evaluations, which may not be the case. Additionally, the model does not take into account the effects of emotions, motivations, social influences, or situational factors on consumer choice. It may also fail to capture the complexity and diversity of consumer preferences and behavior, particularly for high-involvement or experiential products or services. Furthermore, the model may not reflect actual purchase behavior since consumers can change their minds or encounter obstacles in the buying process.

5 Tips for using the model

To use the expectancy-value model effectively, you should select relevant and meaningful alternatives and attributes for your product or service category, and avoid too many or too few options. Additionally, use reliable and valid methods to measure consumer beliefs and preferences, and analyze the data with appropriate statistical techniques. When interpreting the results, be sure to supplement them with other sources of information. Finally, use the results to inform your product or service development, marketing strategy, or competitive analysis.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?