“Feel the decibels closely”: Earphones preference study using conjoint analysis

1. Introduction

The COVID-19 pandemic enforced an unprecedented change in the lifestyle of populations worldwide. Confined within the walls of their homes, consumer shopping behaviours changed drastically. The uncertainty and anxiety caused by the pandemic changed the average Indian shopper from an indulgent to a hoarder (Euromonitor International, 2021). As market sectors crashed globally because of lockdowns, essential services in the country and E-commerce, as an exception, continued.

It was observed that Consumer Electronics made up approximately 40% of India’s E-commerce retail market value (Statista, 2021).

Although the Consumer Electronics Segment remained stable during the pandemic, a few sub-segments showed a massive increase in demand. The areas that dominated these sub-segments were multi-functional devices such as smartphones, wearables, computer accessories, etc.

Among wearables, the earphones sector, which was already witnessing a change because of falling prices for premium features, showed a massive spike in revenue change by 27.5% in 2020. This increased market activity massively favoured the existing leaders of the segment – Imagine Marketing Private Limited (Boat), who further cemented their position. The increasing opportunity brought in more competition with new players entering the market and the leaders launching new chains of products according to the changing consumer demands. With many features, different audio codecs, charging methods, noise cancellation techniques, and sweat and water resistance ratings, the manufacturers must choose an optimal combination of these features to grow in the market.

The Forecast Sales of earphones in different categories for 2021 to 2026 predict an overall increase in sales in India (Euromonitor International, 2021). Therefore the findings of the study can be used by players to model their long-term product strategies.

2. Literature review

A research paper by Lei et al. (2021) seeks to examine how consumers make trade-off decisions between two key product attributes (e.g., tastiness and healthiness of food items) in a two-step choice process in which consumers first choose between product categories competing on two key attributes and then make a final choice within the selected category.

In three studies, the paper shows that when holding the actual choice options unchanged, consumers are more likely to make a more extreme final choice, prioritizing a single attribute rather than compromising when they follow a two-step choice process instead of a one-step process. A study conducted by Kaur et al. (2021) concludes the importance of social commerce stores on consumer purchase situations. They have used conjoint analysis on consumer decision-making associated with online retailers that used Facebook as part of their promotional and trading system.

Dobney et al. (2017) tried to understand whether introducing noise in the different levels of a conjoint analysis would seek to mediate the limitations of Conjoint Analysis. The limitation is that the respondents become fatigued while answering the questionnaire because of the repetitive choices. The paper, therefore, wants to understand if there is a difference in the outcome of the more realistic choices. By realistic, it means how they appear on E-Commerce websites. The noise is the slight variation in the choices. Through experimental research, the study seeks to find out if adding noise in the combination helps alleviate fatigue and therefore increases the data quality. The study shows no statistical improvements in the data quality and concludes that meaning is more important than the wording in the questionnaire choices.

3. Research methodology

4. Findings

The importance value is highest for Price (30.140) compared to the other factors, which indicates Price is the most critical factor for the customers, followed by Sweat resistance (23.853), Audio codec (16.174), Battery Backup (15.355), and Noise cancellation (14.477). (Refer to Table 1).

Based on our analysis, the respondents can be categorized into two dominant groups:

1.

One that seeks optimal features and they are willing to pay high prices for the premium segment

When we look at individual utility estimates, because of the different amalgamation of features present, we can observe the following things:

The value of the utility estimate for Passive is 0.058; this feature is preferred more by the customers than Active. Passive has a higher preference over Active Noise cancellation because the respondents are trading off Noise cancellation and choosing other combinations with features like LDAC, Battery Backup of more than 18 hours, IPX5, and low price.

The utility estimate for SBC (0.087) is higher than LDAC ( - 0.087). Therefore, SBC is most preferred by customers. SBC has a higher preference over LDAC Audio Codec because the respondents are trading off Audio Codec and choosing other combinations with features like Active Noise Cancellation, Battery Backup of more than 18 hours, IPX5, and low price.

Customers prefer IPX4 (0.098) for sweat resistance over IPX5 ( - 0.098). The reason behind IPX4 having a higher preference over IPX5 Sweat Resistance because the respondents are trading off Sweat Resistance and choosing other combinations with features like Active Noise Cancellation, Battery Backup, more than 18 hours, LDAC audio codec, and low price.

The findings show that customers prefer a high price as the utility estimate for 8001 and above is 0.295. High prices have a higher preference over low prices because the respondents are trading off low prices and choosing other combinations with features like Active Noise Cancellation, Battery Backup of more than 18 hours, LDAC audio codec, and IPX5 Sweat Resistance.

When it comes to trading off specific features:

1.

High Price (0.295)

Features with the lowest utility estimates were being traded off more.

The conjoint analysis shows the most preferred combination of features compared to the other combinations and not in isolation. The result of this study can be helpful to the manufacturers and the distributors of earphones to identify what features customers seek.

The study will benefit product design and marketing teams. It will help them tailor their products and campaigns, highlighting features preferred mainly by the larger audience, thereby helping them increase their overall market shares.

The analysis would also help create better marketing campaigns that project the features sought by a larger audience, assisting them in optimizing their marketing STPs. Thus the result of the analysis is viable both to the present market leaders who want to optimize their product line and the newcomers who wish to enter the market with products that can capture ground against these established players. It can aid in identifying where the trade-off happens and locate their customer’s decision dilemma.

6. Discussion

The study demonstrated two customer segments and their respective preferences of features. With the many options available to earphone manufacturers, this study can therefore help earphone manufacturers cater to the preferences of the different customer segments, attracting more customers and thus increasing sales.

It can also be inferred that although the general preferences of the country’s population are inclined towards the economical options, there exists a significant market for premium earphones, as shown by the customers in their willingness to pay in the premium amount ranges.

7. Summary and conclusion

Through the study, we could understand which features the customers give more importance to when selecting a pair of earphones. We were further able to study which choice the customer preferred within each feature. Therefore, we successfully quantified customer preferences and choice trade-offs through conjoint analysis.