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Consumer Electronics and Entertainment

Q4 2025

Quantified Consumer

Streaming Competition and Profitability: Pricing Models & Retention Strategies

As streaming platforms refine their pricing strategies and content offerings, understanding consumer sentiment is critical to driving growth and retention. This flagship study provides a comprehensive analysis of the U.S. video streaming market, tracking key trends across more than a decade in consumer demand for video services across all business models. It evaluates shifts in subscription and ad-supported models, pricing sensitivity, churn drivers, and the effectiveness of bundling and promotional tactics.

The research examines how consumers navigate an increasingly fragmented streaming landscape, their willingness to pay for multiple services, and factors influencing their long-term loyalty. Additionally, the study explores engagement trends, the impact of exclusive content and original programming, and consumer demand for interactive and personalized experiences. As profitability pressures intensify, the research provides insights into how platforms can balance content investment with sustainable business models

This study draws from Parks Associates’ Q3 2025 survey of 8,009 U.S. internet households.

Purchase

Methodology & Key Terms 

Executive Summary  

Trends in the Subscription TV and Video Market 

Adoption and Spend on Pay TV  

Adoption and Spend on SVOD  

Net Promoter Score for Leading Services 

Pay-TV Churn and Retention  

Streaming Video Churn and Retention  

Ad Experience

Sign-ups and Subscription Management 

Bundling Benefits and Value 

Video Consumption by Device

Appendix 

Defining Internet households
Guide to reading Parks Associates charts

Additional research from Parks Associates

Published by Parks Associates
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Disclaimer

Parks Associates has made every reasonable effort to ensure that all information in this document is correct. We assume no responsibility for any inadvertent errors.

Analysis is supported by AI tools in Parks Associates private, secure workspace to synthesize findings and only with insights from its proprietary dataset.