Company A is a US based Netflix competitor. Rather than charging a monthly fee, Company A charges a low annual fee of $19.99 and allows users to rent movies for a discounted rate compared to other services. Company A is focused on growing users in English speaking countries. Company A has two key initiatives for 2020:
- Produce new Company A exclusive movies to differentiate the platform.
- Personalize the Company A experience via Product & Marketing.
You’ve been brought into Company A to support these goals and you’ve been tasked with two separate items:
- Find insights regarding customer preferences to determine the types of movies to produce.
- Build out curated user data tables that enable personalization efforts.
- Finding the genre out of 5 genres (Family, Comedy, Crime, Action, and Thriller) has the highest probability of success based on revenue.
- Finding the genre out of 5 genres (Family, Comedy, Crime, Action, and Thriller) recommended the team based on customer engagement.
- Describing the data for marketing that can help to answer marketing teams' questions.
The movies metadata dataset contains information of each movie such as movie id, genres, title, duration, budget, genres, revenue.
| Movies_metadata | |
|---|---|
| belongs_to_collection | string |
| budget | float |
| genres | string |
| id | float |
| original_language | string |
| original_title | string |
| overview | string |
| popularity | float |
| poster_path | string |
| production_companies | string |
| production_countries | string |
| release_date | string |
| revenue | float |
| runtime | float |
| spoken_languages | string |
| status | string |
| tagline | string |
| title | string |
The movilens_rating dataset contains information about each user’s vote details.
| Movilens_rating | |
|---|---|
| Index | float |
| movie_id | float |
| rating | float |
| rating_date | string |
| user_id | float |
In movies_metadata dataset genres column convert to JSON format (replace single quotes with double quotes) and parse each genre to the columns with Postgres Functions.