🎬 Netflix Movies and TV Shows – Data Visualization with Tableau

This project delivers a professional data analysis and visualization of Netflix Movies & TV Shows using Tableau.
As streaming platforms compete fiercely worldwide, this analysis provides actionable insights into content growth, genre shifts, audience targeting, and market competition.
By combining Tableau with Design Thinking, we highlight both descriptive analytics (what has happened) and strategic implications (what Netflix should do).

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🌍 Background: Netflix and the Streaming War

Founded in 1997 as a DVD rental service, Netflix has grown into the world’s largest streaming platform with 240M+ subscribers in 190+ countries. Its success is fueled by:

• Global Expansion 🌐 – Aggressive scaling post-2015 with localized content.
• Original Productions 🎬 – Heavy investment in Netflix Originals since 2013.
• Competition ⚔️ – Disney+, Amazon Prime, Apple TV+ are catching up.
• Personalization 🤖 – Advanced recommendation system enhancing user experience.

🚀 Key Drivers of Netflix’s Growth

• Innovation & Flexibility: Rapid product iteration challenged the belief that ads or heavy promotions are the only way to boost views.
• Technology: AI-driven recommendations personalize experiences, keeping engagement high.
• Content Strategy: Massive investment in originals (“By Netflix”) earned global recognition — Oscars, Emmys, BAFTA, Golden Globes, and even Grammys.

⚔️ Facing the Competition

• Disney+ 🏰 – 234M+ subs with Marvel, Pixar, Star Wars, Hulu.
  → But Netflix’s ARPU (11.76 USD) is nearly double Disney+ (5.95 USD).
• Apple TV+ 🍏 – ~25M paid subs; strong premium shows like The Morning Show but smaller library (~80 vs Netflix’s 5000+).
• Amazon Prime Video 📦 – ~190M subs; strong originals (Fleabag, Marvelous Mrs. Maisel) but mixed reputation due to user-generated content.
• Other Players: YouTube TV, Paramount+, HBO Max, Sling — each carving niche segments.

🎯 Netflix’s Marketing Shift

Marketing spend rose from $2.2B (2020) → $2.5B (2022).

• Old Strategy: Build broad brand awareness.
• New Strategy: Spotlight individual shows & movies, delivering unique experiences that strengthen customer loyalty.

User Segmentation

• Teens (13–24) prefer Anime, Action, Sci-Fi.
• Adults (25–44) watch Drama, Documentaries.
• Families (45+) lean on International Movies and Comedies.
• Key insight: Personalized recommendations must vary by age & culture.

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🔄 Netflix Strategic Flow & Design Thinking

A Fun Approach to Data Analysis

Ever wondered if you should watch Netflix? This fun flowchart gives us a great way to think about our data analysis process. Just like the chart helps you decide, our project follows a similar logical flow:

1. Start: We gather all the raw data, focusing on content supply from different countries and genres.
2. Process: We then analyze user engagement by looking at ratings and user segmentation to see what people are really watching.
3. End: Finally, we use these findings to generate strategic insights that can help Netflix stay competitive and keep viewers engaged.

Applying Design Thinking

1. Empathize – Identify user needs (local content, genre preference).
2. Define – Spot challenges (e.g., limited family content vs Disney+).
3. Ideate – Propose ideas (regional co-productions, niche genres).
4. Prototype – Create dashboards & simulate content strategies.
5. Test – Measure success with engagement & retention metrics.

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📊 Domain Insights and Visualizations

1. Content Growth Over Time

• Netflix’s catalog expanded sharply after 2015, with a peak roughly between 2018–2020.
• Post-2020 the growth curve flattens and shows signs of stabilization.
• The initial surge aligns with Netflix’s aggressive international market entry and Originals production.

🔑 Key Insight:
The flattening after 2020 signals a strategic pivot from sheer volume → curated, higher-value originals. Prioritize measuring ROI per title (cost vs engagement) and shift budget to high-LTV content.

2. Top 10 Content-Producing Countries

• USA leads by a large margin; India, UK, Canada follow.
• Emerging producers: South Korea, Japan, France (rising rapidly).
• Country mix differs by type: some countries skew toward TV shows, others toward movies.

🔑 Key Insight:
Netflix’s local-for-global strategy is working — invest selectively in regional production hubs (e.g., K-content, Indian TV) that produce exportable hits. Use country-level economics (production cost vs global viewership) to prioritize investments.

3. Trend in Publishing Genres Over Years

• Core genres: Drama, Comedy, International Movies.
• Notable growth in Anime, Docuseries, Reality segments since ~2017.
• Genre mix shifted from homogeneous (pre-2015) → diversified (post-2015).

🔑 Key Insight:
Genre diversification reduces churn by serving both mass and niche audiences (long-tail value). Prioritize personalized surfacing of niche genres to increase engagement among segmented audiences.

4. Age-Rating Category Correlations (Genre × Rating)

• Strong links: TV-MA ↔ International Movies, TV-14 ↔ International TV Shows, R ↔ Dramas.
• Mature ratings are heavily represented across international genres.

🔑 Key Insight:
Netflix aligns rating strategy with genre & region to maximize relevance. This supports highly targeted recommendation rules (e.g., promote TV-MA international titles to cohorts that historically engage with mature international drama).

5. Number of Content by Rating

• TV-MA and TV-14 constitute the largest share of titles.
• Family / G / TV-Y content is under-represented relative to the adult catalog.

🔑 Key Insight:
Netflix’s portfolio skews mature — great for young-adult retention but leaves a family-segment gap where competitors (Disney+) outperform. Consider targeted family content acquisition to diversify ARPU sources and household reach.

6. Distribution of Content by Country (detailed)

• Country distribution shows concentration in a few hubs but increasing tail of smaller producing countries.
• Some countries produce more TV formats; others focus on films.

🔑 Key Insight:
Leverage smaller-country content as cost-effective experimentation (lower production cost, potential viral global hits). Build a fast A/B pipeline to test and scale region-originated formats with global appeal.

7. Cast Distribution (cast-size / cast-diversity by genre)

• Genres like Drama, International Movies, Comedies have larger casts and higher cast-diversity.
• Larger ensembles correlate with longer runtimes / multi-episode formats.

🔑 Key Insight:
Investing in ensemble, star-driven productions increases discoverability across markets. Use cast-network analytics to identify cross-market actor clusters for co-productions and targeted promotion.

8. Number of Rating's Content by Year (Temporal evolution)

• TV-MA & TV-14 show rapid growth since 2010 with acceleration during global expansion.
• G/PG content remains relatively flat over the same period.

🔑 Key Insight:
Temporal patterns confirm a deliberate tilt toward maturity-focused storytelling. For long-term resilience, combine this focus with selective family-oriented investments to keep multi-generational households engaged.

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📊 Final Integrated Dashboard

• Interactive filters for ratings, genres, and regions.
• Unified storytelling: Content growth ➝ Ratings ➝ Countries ➝ Segmentation.
• Built for both analytical exploration and executive reporting.

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📈 Executive Insights

• Netflix dominates mature-rated global content, but weak in family-friendly space where Disney+ excels.
• Regional hubs (India, Korea, Japan) drive growth, proving the success of the “local-for-global” model.
• Content strategy has shifted from volume (2015–2020) → curation & Originals (post-2020).
• Personalization & niche genres (anime, docuseries) are critical for user retention.
• Star-driven productions enhance cross-market appeal and strengthen Netflix’s global brand.

📊 Executive Takeaways

① Strategic pivot confirmed: Focus on curated Originals with strong ROI and retention, not sheer volume.
② Local-for-global works: Scale investments in regional co-productions and expand global distribution of local hits.
③ Audience concentration risk: Mature-content dominance retains young adults but leaves the family segment untapped.
④ Long-tail genres = stickiness: Enhance recommendation algorithms to push anime, docuseries, and other niche content.
⑤ Talent economics matter: Use cast-network insights to guide content planning, marketing, and partnerships.

✅ Recommended Next Steps

• Short-term (0–6M):

  • Deploy title-level ROI dashboards (cost, first-28-day views, retention lift).
  • Improve personalization for niche genres to increase long-tail watch time.

• Mid-term (6–12M):

  • Pilot family-content acquisition program in US + India; measure household penetration impact.
  • Establish cast-network KPIs to inform co-production and talent contracting.

• Long-term (12M+):

  • Scale successful family and regional strategies globally.
  • Continuously refine data-driven segmentation for retention and ARPU optimization.

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🛠️ Methodology & Data Transparency

• Data Source: Kaggle’s Netflix Movies and TV Shows dataset (~8,800 titles, up to 2021), originally compiled from Flixable + Netflix public catalog.
• Preprocessing Steps:
  • Cleaned missing values in country, cast, and date_added.
  • Standardized genre and merged sub-categories (e.g., “Intl. Movies” vs “International Movies”).
  • Split dataset into Movies vs TV Shows for separate analysis.
• Limitations:
  • Dataset ends at 2021 → excludes recent Netflix Originals.
  • Some metadata (e.g., viewership, budget, churn impact) is not public.
  • Genre overlap (multi-tagged shows) may slightly inflate counts.

⚖️ Including methodology + limitations improves research transparency and aligns with academic best practice.

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🌍 Comparative Benchmarking

Netflix’s growth is clearer when placed in industry context:

• Disney+ → Family-first positioning. Strong catalog of Marvel, Pixar, and Star Wars makes Disney+ the clear winner in G/PG-rated content.
• Amazon Prime Video → Broad distribution (bundled with Prime), but relatively low engagement per title.
• Apple TV+ → Fewer titles, but high ROI per show (e.g., Ted Lasso, The Morning Show) with strong awards presence.

📌 Netflix dominates global mature-rated content, but competitors highlight gaps in family appeal (Disney+), distribution bundling (Amazon), and prestige-per-title strategy (Apple TV+).

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🔮 Future Opportunities for Netflix

To sustain leadership, Netflix should look beyond descriptive growth into strategic foresight:

1. AI-Driven Content Creation

   • Generative AI for script ideation, subtitle localization, and personalized trailers.
   • Reduces production cost + accelerates global releases.

2. Gamification & Interactive Content

   • Expand Bandersnatch-style interactive shows.
   • Drives engagement, rewatchability, and differentiates from rivals.

3. Partnership Ecosystem

   • Collaborate with telecom operators (e.g., bundle Netflix with 5G data plans).
   • Boosts ARPU + strengthens market penetration in emerging economies.

4. Sustainability & ESG Branding

   • Invest in carbon-neutral productions and green studios.
   • Enhances brand equity, attracts ESG-focused investors, and improves compliance in EU markets.

🚀 These moves can future-proof Netflix while balancing brand identity (“edgy, global, personalized”) with untapped growth pockets (family, interactive, ESG).

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👨‍💻 Author

• Author: TheHien04
• Role: Data Analyst | Tableau Developer
• Dataset: Kaggle — Netflix Movies and TV Shows (~8.8K entries) Kaggle Netflix Titles
• License: Academic & educational purposes
• Tools: Tableau, Python (Pandas), SQL