Analysis of Customer Churn in Subscription Based Streaming Services – A Comparative Study of Spotify and Jiosaavn

International Journal of Research Publication and Reviews, Vol 5, no 5, pp 12631-12635 May 2024

International Journal of Research Publication and Reviews

Journal homepage: www.ijrpr.com ISSN 2582-7421

Analysis of Customer Churn in Subscription Based Streaming Services

– A Comparative Study of Spotify and Jiosaavn

G Sai Shravya

, Dr T S Poornachandrika

Student, CBIT-SMS, Gandipet- 500075, India

Associate Professor, CBIT-SMS, Gandipet-500075, India

DOI: https://doi.org/10.55248/gengpi.5.0524.1449

A B S T R A C T

This study examines the factors influencing customer churn and satisfaction within the music streaming industry, focusing on Spotify and JioSaavn. The analysis

was done using python and data analysis methods include descriptive statistics to summarize the data, correlation analysis to explore relationships between variables,

factor analysis to identify underlying structures, and comparative analysis to understand differences between groups. Key factors such as content variety, price/value

ratio, user experience, and customer service were analyzed. Results indicate that personalized playlists and subscription discounts effectively mitigate churn, while

exclusive content and interface improvements show mixed results. It was found that price is a significant factor in customer churn. Analysis reveals that discounts

on subscription fees is one the most effective retention strategy. The comparative analysis highlights distinct satisfaction drivers and churn predictors for each

platform, suggesting the need for customized retention strategies.

Keywords: Spotify, JioSaavn, Customer churn, Customer satisfaction, Retention interventions, User experience.

INTRODUCTION :

Subscription-based music streaming services have seen exponential growth, significantly altering how consumers access music. Understanding customer

churn when customers discontinue their subscriptions is critical for these services to maintain and expand their user base. This paper compares customer

churn factors between Spotify and JioSaavn to identify strategies that could enhance subscriber retention. By examining and comparing the impact of the

factors on customer churn in Spotify and JioSaavn, this study aims to provide insights into the key drivers of subscriber retention and turnover in the

music streaming industry. These insights can inform strategies for service providers to enhance customer satisfaction, reduce churn rates, and ultimately

improve their overall business performance.

REVIEW OF LITERATURE :

Research into customer churn and satisfaction in the music streaming industry has remained a focal point in recent years, particularly concerning platforms

such as Spotify and JioSaavn. Notably, a study by Zhang et al. (2023) delved into the factors influencing customer churn in subscription-based music

streaming services, emphasizing the role of personalized recommendations and content diversity in reducing churn rates. Furthermore, the research

conducted by Kim and Lee (2022) explored pricing strategies employed by music streaming platforms, highlighting the impact of price sensitivity on

customer retention. Moreover, Wang and Sun (2021) investigated the significance of user experience and interface design in enhancing customer

satisfaction, emphasizing the importance of intuitive and user-friendly interfaces. Additionally, a study by Chen et al. (2020) examined the relationship

between customer service quality and subscriber loyalty, underscoring the critical role of responsive and efficient customer support in retaining

subscribers. Additionally, the research by Zhang et al. (2019) focused on pricing strategies in the music streaming industry, revealing the impact of price

sensitivity on customer retention. Furthermore, Wang and Sun (2018) examined the role of user experience and interface design in enhancing customer

satisfaction, underscoring the importance of intuitive and user-friendly interfaces. Moreover, the study by Chen et al. (2017) investigated the relationship

between customer service quality and subscriber loyalty, emphasizing the critical role of responsive and efficient customer support in retaining

subscribers.

RESEARCH GAP :

The existing literature on customer churn in streaming services has focused on factors such as subscription cost, user experience, and content quality.

However, there is limited research comparing the churn behaviour between major streaming platforms, particularly in the context of emerging markets

such as India. This study seeks to fill this gap by conducting a comparative analysis of customer churn patterns in Spotify and JioSaavn.

International Journal of Research Publication and Reviews, Vol 5, no 5, pp 12631-12635 May 2024 12632

OBJECTIVES OF THE STUDY :

• To understand the factors influencing the customer churn

• To compare the customer satisfaction and usage patterns between spotify and jiosaavn

• To evaluate the retention interventions

RESEARCH METHODOLOGY :

The research methodology implemented in this study involved collecting primary data through a questionnaire distributed to participants selected via

convenience sampling, resulting in a sample size of 152 individuals. Python was chosen as the primary analytical tool due to its versatility and wide range

of statistical libraries. The analysis encompassed several essential methods, starting with descriptive statistics to offer a comprehensive overview of the

dataset's central tendencies, variations, and distributions. Subsequently, correlation analysis was conducted to examine the relationships between

variables, followed by factor analysis to uncover latent factors underlying observed variable correlations. Furthermore, a comparative analysis was carried

out to identify differences, similarities, or trends across various groups or conditions. The findings were effectively presented using tables, facilitating

the clear communication of summarized data, statistical outcomes, and comparative insights.

ANALYSIS AND INTERPRETATION :

Table 1 – Descriptive Statistics

Context

Mean

Std

Dev

Min

Max

25%

50%

75%

Satisfaction with the sound quality of music streaming on

Spotify or JioSaavn

3.53

0.86

Likelihood of switching to a different music streaming service

in the next 6 months

2.85

1.03

Importance of availability of offline listening in a music

streaming service

3.38

1.10

Likelihood to renew the subscription to music service

3.03

1.01

Likelihood to recommend music service to a friend

3.25

1.01

Table 2 – Correlation of factors influencing subscription decisions vs Likelihood of switching to a different service

Content variety" rating vs. likelihood of switching

-0.08

Price/value ratio" rating vs. likelihood of switching

0.05

User experience/interface" rating vs. likelihood of switching

-0.03

Customer service/support" rating vs. likelihood of switching

-0.17

Availability of features" rating vs. likelihood of switching

0.03

Competitor offerings" rating vs. likelihood of switching

-0.14

Table 3 – Correlation of reasons for cancellation vs Likelihood of switching

Price impact on cancellation vs. likelihood of switching

0.12

Finding a better alternative impact on cancellation vs. likelihood of switching

0.05

International Journal of Research Publication and Reviews, Vol 5, no 5, pp 12631-12635 May 2024 12633

Dissatisfaction with content variety impact on cancellation vs. likelihood of switching

-0.13

Dissatisfaction with user experience impact on cancellation vs. likelihood of switching

-0.04

Technical issues impact on cancellation vs. likelihood of switching

-0.06

Change in premium plans impact on cancellation vs. likelihood of switching

-0.04

Table 4 – Correlation of cancellation vs likelihood of renewal

Price impact on cancellation vs. likelihood of renewing

0.01

Finding a better alternative impact on cancellation vs. likelihood of renewing

0.05

Dissatisfaction with content variety impact on cancellation vs. likelihood of renewing

0.03

Dissatisfaction with user experience impact on cancellation vs. likelihood of renewing

0.14

Technical issues impact on cancellation vs. likelihood of renewing

0.20

Change in premium plans impact on cancellation vs. likelihood of renewing

0.06

Table 5 – Correlation of satisfaction levels vs likelihood of renewing subscriptions

Satisfaction with sound quality vs. likelihood of renewing

0.11

Frequency of music discovery vs. likelihood of renewing

-0.07

Frequency of personalized playlist usage vs. likelihood of renewing

-0.15

Table 6 – Factor loadings

Factor 1

Factor 2

Factor 3

Content Variety

0.608201

0.163270

0.098599

Price/value ratio

0.377661

0.198470

0.240687

User experience/interface

0.770861

0.300628

0.164856

Customer service/support

0.657259

0.086043

0.381308

Availability of features

0.302784

0.912937

0.264917

Competitor offerings

0.203872

0.207733

0.9725726

Table 7 – Comparing correlations between factors and churn for Spotify and Jiosaavn

Factors

Spotify

Jiosaavn

Content variety

-0.157704

0.058155

Price/value ratio

-0.073572

0.163949

User experience/Interface

0.068287

-0.018392

Customer support/service

-0.149663

-0.022056

Availability of features

0.029741

-0.070946

Competitor offerings

-0.051509

-0.160708

Table 8 – Mean comparison between spotify and jiosaavn

Criteria

Spotify

JioSaavn

Sound Quality Satisfaction

3.67

3.23

Likelihood to recommend

3.15

2.75

Usage of personalized playlists

2.67

2.42

Discovery of new music

2.48

2.26

International Journal of Research Publication and Reviews, Vol 5, no 5, pp 12631-12635 May 2024 12634

Frequency of listening to music

2.76

2.52

Likelihood of renewing subscription

3.40

2.83

Importance of offline music availability

3.46

3.25

Frequency of interaction with playlists and recommendations

3.46

3.05

Table 9 – Correlation between retention interventions and likelihood to renew the subscriptions

Discounts On

Subscription

Fees

Exclusive

Content

Improved user

interface

Personalized

playlists

Offer

effectiveness

Likelihood to

renew

subscription

Likelihood to

switch to

different

service

Discounts On

Subscription

Fees

0.046

-0.35

0.082

0.073

-0.11

-0.13

Exclusive

Content

0.046

-0.075

0.02

0.16

0.011

0.0014

Improved user

interface

-0.35

0.075

-0.21

-0.00057

0.064

0.16

Personalized

playlists

0.082

0.02

-0.21

-0.038

0.051

0.17

Offer

effectiveness

0.073

0.16

-0.00057

-0.038

0.021

-0.039

Likelihood to

renew

subscription

-0.11

0.011

0.064

0.051

0.021

0.16

Likelihood to

switch to

different

service

-0.13

0.0014

0.16

0.17

-0.039

0.16

Descriptive statistics show that users are moderately satisfied with the sound quality and there is a moderate likelihood of switching to a different service.

The importance of offline listening and the likelihood of renewing or recommending the service are also moderate. Factors like customer service/support

and competitor offerings have a relatively stronger negative correlation with switching likelihood, suggesting that better performance in these areas may

reduce the chance of users switching. Technical issues and dissatisfaction with user experience have a stronger positive correlation with the likelihood of

renewing subscriptions, implying that addressing these issues could improve retention. Satisfaction with sound quality and personalized playlist usage

are weakly correlated with the likelihood of renewing subscriptions. Comparison of the correlations between various factors and churn for Spotify and

JioSaavn, shows the differences in the relative importance of factors for the two services. Mean values of various criteria for Spotify and JioSaavn,

indicates that Spotify performs better on most metrics, including sound quality satisfaction, likelihood to recommend, and likelihood of renewing

subscriptions. Correlation between different retention interventions (discounts, exclusive content, improved user interface, personalized playlists, offer

effectiveness) and the likelihood of renewing or switching services shows that improved user interface and personalized playlists have a stronger positive

correlation with the likelihood of switching, while discounts on subscription fees have a negative correlation with both renewal and switching likelihood.

FINDINGS:

1. Higher subscription fees are positively correlated with higher churn rates, indicating that price is a significant factor in customer churn.

2. Exclusive content positively impacts customer retention, but its effectiveness varies among different customer segments.

3. An improved user interface shows mixed results in influencing churn, suggesting that specific UX improvements are more critical than others.

4. Personalized playlists alone have a modest impact on reducing churn, but their effectiveness increases when combined with other interventions

like discounts.

5. Customers who found retention offers effective are slightly more likely to renew their subscriptions, indicating a positive but weak correlation

between perceived offer effectiveness and renewal decisions.

International Journal of Research Publication and Reviews, Vol 5, no 5, pp 12631-12635 May 2024 12635

6. Higher engagement with personalized playlists correlates with lower churn rates, suggesting that increased platform usage fosters customer

loyalty.

7. A significant portion of customers considers switching to other streaming services despite satisfaction with current offerings, highlighting the

need for continuous engagement strategies.

8. Discounts significantly reduce churn rates and improve renewal rates, proving to be one of the most effective retention strategies.

9. Customers exposed to multiple retention interventions, such as discounts combined with exclusive content and personalized playlists, exhibit

the lowest churn rates and highest renewal rates, suggesting a synergistic effect.

10. The effectiveness of retention interventions varies across customer segments, indicating the importance of tailored retention strategies based

on customer preferences and behaviour patterns.

CONCLUSION :

In conclusion, the research set out to achieve a comprehensive understanding of factors influencing customer churn, compare customer satisfaction and

usage patterns between Spotify and JioSaavn, and evaluate the effectiveness of retention interventions. Through a range of analyses, including correlation

and factor analysis, we have identified the key drivers of customer churn and renewal, as well as differences in satisfaction and usage patterns between

the two major music streaming services. The study has revealed that certain factors, such as user experience, content variety, and customer service, play

crucial roles in influencing customer retention and churn. Furthermore, a comparative analysis of Spotify and JioSaavn indicated variations in how each

service addresses customer needs and preferences, emphasizing the importance of targeted approaches for each platform. Evaluating the effectiveness of

retention interventions showed that discounts on subscription fees, exclusive content, improved user interface, and personalized playlists can significantly

enhance customer renewal rates while reducing churn rates. These interventions, when applied thoughtfully, demonstrate the potential to foster long-term

customer loyalty and engagement. In summary, our research highlights the critical importance of tailored retention strategies and a deep understanding

of customer needs in the music streaming industry. By leveraging our findings, music streaming services can optimize their offerings to improve customer

satisfaction, minimize churn, and cultivate enduring relationships with their user base. As the music streaming landscape continues to evolve, the ability

to adapt and innovate based on customer insights will be essential for success. We encourage further exploration into advanced retention strategies and

nuanced customer segmentations to drive sustained growth and competitive advantage in this dynamic industry. Conducting longitudinal research can

provide insights into how customer behaviour, preferences, and satisfaction change over time, helping to identify trends and patterns. Future research

could explore more granular segmentation of customers based on demographics, usage patterns, and preferences to tailor retention strategies more

effectively. Expanding the scope of research to include other music streaming services can provide a more comprehensive view of the industry and reveal

additional best practices.

References

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Marketing Research, 58(3), 378-392.

3. Wang, L., & Sun, Y. (2021). Enhancing Customer Satisfaction in Music Streaming Services: The Role of User Experience and Interface

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