Consumer Decision Process, Determinant Attributes, Postpurchase Dissonance, and Seller Strategies

Question One Consumer Decision Process for Buying a Smart Home Device:

A person goes through several consumer decision-making steps before deciding what to buy. Follow these steps to purchase a smart home device:

• Need Recognition: Acknowledging the need or desire for a smart home device is the first step (Hjerpe, 2022). This might happen for various reasons, such as seeing commercials, hearing about the advantages from friends or family, or having trouble managing home chores.
• Information Search: After identifying the need, the consumer will research the available options (Hjerpe, 2022). To learn more about smart home devices and their features, consumers can consult various sources, including internet reviews, tech websites, suggestions from friends, and physical retailers.
• Alternatives Evaluation: In this step, the consumer compares and contrasts several smart home gadgets based on their features, capabilities, compatibility with other gadgets, cost, and brand reputation (Chen et al., 2020). They may contrast products from several manufacturers, including Apple, Google, and Amazon, to find the one that best satisfies their needs.
• Purchase Decision: The consumer purchases after weighing the available options (Kushwaha et al., 2021). Several variables may influence this choice, such as the device’s perceived value, price, accessibility, warranty, and user reviews.
• Purchase: The consumer pays for the selected smart home equipment, whether online or at a physical store.
• Postpurchase Evaluation: The user evaluates the product’s performance concerning their expectations after using it (Chen et al., 2020). They will likely feel satisfied if the device meets or exceeds their expectations. If it falls short, people might be disappointed.

Question Two:Determinant Attributes and Compensatory Purchasing Model

The following four characteristics can be used to distinguish between Amazon, Google, and Apple smart home products:

Voice Recognition and Response: This characteristic assesses how well the device detects and reacts to voice commands.

The ability of a smart home device to regulate and integrate with various smart home device types and numbers is determined by this attribute.

Web Browsing Capabilities: This attribute assesses how well the device can browse the internet, including the search engine it uses, and it can access and retrieve data from the internet.

Price: This characteristic considers the smart home accessory’s price.

Each feature is given a weight based on its significance to the buyer to create a compensating purchasing model. On a scale of 1 to 10, the consumer then evaluates the performance of each attribute (Chen et al., 2020). The weight of each attribute is multiplied by its performance rating, and the sum of the scores for all attributes is used to determine the overall score for each brand.

The consumer can choose which product to buy based on the evaluations for importance and performance (Chen et al., 2020). If, for instance, a customer considers speech recognition and response to be of the utmost importance and finds that Amazon Echo outperforms Google Home and Apple Home Pod in this regard, the customer may opt for Amazon Echo.

Question Three: Device Features with the Greatest Impact on Consumers’ Propensity to Buy

These are the characteristics looked at in this chapter that may have the biggest effect on customers’ tendency to purchase a smart home device:

Accurate speech recognition is valued by users who want their spoken commands to be recognized and carried out.

Compatibility with Existing Devices: The smart home ecosystem is more functional and convenient when it can easily interact with and control other smart home gadgets.

Consumers may favour gadgets with more sophisticated browsing capabilities and access to a greater variety of information sources.

Price: The ability to afford a product is a major factor in consumer choice. It is crucial to have reasonable pricing concerning the device’s perceived worth.

After buying a smart home gadget, consumers may experience postpurchase cognitive dissonance or a feeling of uneasiness or doubt about the purchase decision.

Question four:

Customers may feel postpurchase cognitive dissonance after buying one of the smart home appliances listed in the case study (Amazon Echo, Google Home, or Apple HomePod) for some reasons:

• Comparing the chosen device to the characteristics and advantages of the unconsidered alternatives may cause consumers to second-guess their choice and feel dissonance (Hjerpe, 2022). They can question whether they made the best decision and whether another gadget would have met their needs more effectively.
• Perceived Performance Gap: Cognitive dissonance may result if a technology does not perform up to expectations or falls short in some other way (Chen et al., 2020). The purchaser could feel guilty or unsatisfied about their choice.
• Confirmation bias is the tendency for consumers to deliberately seek out facts or opinions that support their choice while ignoring or downplaying any unfavourable remarks about the gadget in question (Hjerpe, 2022). However, cognitive dissonance may result if individuals encounter unfavorable facts or events contradicting their initial views.
• Social influences: If a customer learns that others who already own a different smart home gadget have had excellent experiences or recommend it, it may cause them to second-guess their choice.

To help consumers resolve postpurchase cognitive dissonance, the seller can take the following steps:

• Effective Customer assistance: To handle any customer issues or worries, the vendor should offer responsive and easily available customer assistance (Kushwaha et al., 2021). This can involve assistance with using the item to its fullest potential, technical support, and troubleshooting advice.
• Apparent Communication of Features and Limits: Before a customer makes a purchase, the vendor must make sure that the features and limits of the product are made apparent to them (Hjerpe, 2022). This can assist in establishing reasonable expectations and lessen the possibility of dissonance brought on by inappropriate expectations.
• Postpurchase Follow-Up: The seller can proactively contact customers after the sale to get feedback and offer more help (Nosi et al., 2022). This can show a dedication to customer pleasure and help immediately handle any worries or difficulties.
• Offering clients who have purchased the gadget specific incentives or prizes might aid in solidifying their choice and fostering a sense of value (Chen et al., 2020). This may entail early access to new features, substantial discounts on associated goods and services, or access to unique content.
• Positive Customer Reviews and Testimonials: By reinforcing the benefits of the selected device, sharing positive customer reviews and testimonials can assist in reducing cognitive dissonance (Hjerpe, 2022). Marketing materials, social networking channels, or specific customer review sections on the seller’s website can all be used for this.

References

Chen, W. K., Chen, C. W., & Lin, Y. C. (2020). Understanding the influence of impulse buying toward consumers’ postpurchase dissonance and return intention: an empirical investigation of apparel websites. Journal of Ambient Intelligence and Humanized Computing, 1-14. https://link.springer.com/article/10.1007/s12652-020-02333-z

Kushwaha, B. P., Tyagi, V., & Shiva, A. (2021). Investigating the role of reinforcement and environmental factors in balancing the state of apprehension: evidence from India. World Review of Entrepreneurship, Management, and Sustainable Development, 17(2-3), pp. 142–160. https://www.inderscienceonline.com/doi/abs/10.1504/WREMSD.2021.114428

Nosi, C., Zollo, L., Rialti, R., & Ciappei, C. (2022). Why do consumers free ride? Investigating the effects of cognitive effort on postpurchase dissonance. Journal of Consumer Marketing, (ahead-of-print). https://www.emerald.com/insight/content/doi/10.1108/JCM-02-2021-4436/full/html?casa_token=MYdF6CdCt5UAAAAA:6sprkV6P2DYGd-63mNGnxyAToWTCykcTrtgO6sfl-VSI1ocs-XGCkb8x1CCgpG-YxvkD9XCmJhCJrgN0qi9B65DLqupHUL9PEOq4t_mCsXksE9TQDPHUPQ

Hjerpe, F. (2022). Examining the Postpurchase Behaviour of Second-hand Clothing: Extending Expectation Confirmation Theory. https://www.diva-portal.org/smash/record.jsf?pid=diva2:1682000