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StreamWise – Netflix Decision Fatigue Analytics

Author: Soundarya S
Target Role: SQL Developer + Business Analyst


The Problem

You know that feeling when you spend 20 minutes scrolling through Netflix and then just... give up and close the app? That's not just you—it's a massive problem for Netflix.

Here's what happens:

  • Users open Netflix excited to watch something
  • They scroll... and scroll... and scroll
  • Decision fatigue kicks in
  • They close the app without watching anything

Why Netflix cares:

  • Lower engagement = unhappy users
  • Unhappy users = people canceling subscriptions
  • Lost revenue and platform trust

This project digs into the data behind this frustrating user experience.


What I Actually Built

Instead of just theorizing about the problem, I built a real analytics system to measure it:

1. Data Foundation

  • Created a proper database structure (dimension + fact tables) to track viewing sessions
  • Modeled how users actually behave: browsing, scrolling, clicking, watching (or giving up)

2. Realistic Test Data

  • Generated 100+ viewing sessions that mirror real user behavior
  • Different user types, different times of day, different outcomes

3. Analytics That Answer Real Questions

  • How long are people scrolling before they watch something (or quit)?
  • Which recommendations actually work?
  • What patterns exist in users who successfully find content vs. those who give up?
  • Who's most at risk of decision fatigue?

4. Business Recommendations

  • Turned the numbers into actual actions Netflix could take
  • Identified which user groups need the most help
  • Suggested concrete UX improvements based on the data

Why This Project Matters

Here's the thing: anyone can write SQL queries.

What separates a SQL developer from a business-focused analyst is this:

  • I didn't just build tables and write queries
  • I asked: "Why are users frustrated?" and "What should we do about it?"
  • I connected technical work to a real business problem that costs Netflix millions

This project shows I can:

  • Design data models that reflect real-world behavior
  • Write SQL that answers business questions (not just technical ones)
  • Think like both an analyst AND a stakeholder
  • Turn data into decisions

Tech Stack

  • SQL Server (T-SQL) – Database design, ETL, analytics queries
  • SSMS – Development environment
  • GitHub – Version control and documentation

Documentation

Full technical writeup, SQL scripts, and business case study available in the /docs folder.

Bottom Line

This isn't just a portfolio project—it's a demonstration of how data work should connect to business impact.

I used SQL to understand why users close Netflix, and more importantly, what could fix it.

About

End-to-end SQL + Business Analytics project analyzing Netflix decision fatigue caused by poor recommendation alignment. Includes data modeling, KPI views, and BA case study.

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