What is the problem?

In recent years, the advent of various OTT platforms has introduced a novel issue: the difficulty in choosing which OTT platform to subscribe to. Netflix, Amazon Prime, and Disney+ are some of the many OTT services that are well-known to the public, but the number of services is growing as localized OTT platforms like Watcha (South Korea) and Voot (India) are joining the line.

As these platforms are coming up with new ways to stand out among competitors by presenting original content, it is evident that more customers are being lost in deciding which platform would be suitable for their use. Moreover, most of the available recommendation systems are focused on suggesting the content but not the platforms that hold and provide those contents. To ease the choice dilemma, our study aims to present a guideline for choosing the appropriate OTT platform that fits one’s personal preferences. Therefore, it is the right time to analyze different OTT platforms and provide useful information for people who are not able to decide which platform fits them best.

How can technology solve the problem?

Data science is the study of data to extract knowledge and insights from the data and apply knowledge and actionable insights. Data analysis can help companies better 

• understand their customers

• evaluate their add campaigns

• personalize content

• create content strategies and develop products. 

• Ultimately, businesses can use data analytics to boost business performance and improve their bottom line.

The Idea:

So the main objective of this challenge is to investigate different OTT platform data sets and analyze the utilization of OTT platforms across the country, especially during the last 2 years, and provide insights on regions, Shows, reviews, languages, genres, etc.

Technical Architecture: