This project leverages SQL to uncover valuable business insights from Instagram's user database. These insights help marketing teams launch effective campaigns, identify trends, and improve user experience while enabling strategic growth.
The primary goal of this project is to extract actionable business insights to:
- Launch new marketing campaigns.
- Decide on features to build for an app.
- Track app success by measuring user engagement.
- Improve user experience to support business growth.
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Database Creation:
- Utilized DDL and DML SQL queries provided by the product manager to create and populate the database.
- Used MySQL Workbench to manage the database.
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Insights Generation:
- Ran SQL queries to derive meaningful insights from database tables.
- SQL (DDL, DML)
- MySQL Workbench
- Data Analytics
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Rewarding Most Loyal Users:
- Identified the 5 oldest users on the platform to reward them.
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Re-engaging Inactive Users:
- Found users who haven't posted and suggested sending promotional emails to encourage activity.
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Declaring Contest Winner:
- Determined the user with the most likes on a single photo for contest recognition.
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Hashtag Research:
- Identified the most effective hashtags for partner brands to maximize reach.
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Optimal AD Launch Timing:
- Analyzed which days are best for ad campaigns to maximize engagement.
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User Engagement:
- Measured active user participation to track platform health.
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Bots and Fake Accounts:
- Detected dummy accounts to maintain platform integrity and enhance user experience.
From the analysis, the following conclusions were drawn:
- Marketing teams can reward loyal users and re-engage inactive ones via targeted emails.
- Effective hashtags and optimal days for ad campaigns can boost visibility.
- Monitoring user engagement offers actionable growth metrics.
- Removing bots and fake accounts improves overall user satisfaction and trust.