Welcome to my data-driven breakdown of Twitch performance across July to September 2025. This Excel project transforms my raw streaming metrics into actionable insights—tracking viewer engagement, revenue trends, and platform performance with precision and creativity. After initial exploration of the raw data we will move on to how viewership is affected by personal presentation using Tableau and then finishing on an exploration of the numerical variables such as time spent streaming, overall follower statistics and unique vs returning viewers.
This workbook is a showcase of my ability to turn granular data into strategic dashboards. From formula-driven calculations to dynamic pivot tables, I’ve built a tool that not only analyzes but empowers decision-making my content creation and potential future marketers alike.
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📊 Data Cleaning & Structuring
- Organized daily metrics for clarity and consistency
- Applied filters and sorting to surface key performance days
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📈 Trend Analysis
- Identified spikes in revenue and engagement
- Compared performance across weekdays and weekends
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📤 Reporting & Visualization
- Created summary views for quick insights
- Used conditional formatting to highlight outliers and milestones
- Used relative and absolute references to build scalable formulas across sheets
- Linked summary dashboards to raw data using structured references
- Applied named ranges for cleaner formulas and easier navigation
- Leveraged core functions like:
SUM,AVERAGE,MAX,MINfor performance metricsIF,COUNTIF,TEXT,ROUNDfor logic and formatting
- Built nested formulas to calculate revenue per viewer and flag anomalies
- Used date functions to group and analyze trends over time
- Created pivot tables to summarize:
- Revenue by day, week, and month
- Viewer count vs. engagement metrics
- Used slicers and filters for interactive exploration
- Applied
GETPIVOTDATAfor dynamic referencing in dashboards -
- Flagged high-revenue days for content replication
- Identified low-engagement periods for optimization
- Built a scalable framework for future Twitch data imports
This isn’t just an Excel file—it’s a performance engine. By combining analytical rigor with creative formatting, I’ve built a tool that helps streamers and analysts alike make smarter, faster decisions.
Using my actual Twitch viewership data, I explored three distinct presentation styles:
- High Personal Effort: Streams where I wore makeup, hair extensions.
- Natural: Streams where I went natural
- Outfit Cut: Exploring any effect top cut has on viewership
The dashboard visualizes how these choices influenced audience size, engagement, and overall performance.
https://public.tableau.com/shared/PNF7QRY3J?:display_count=n&:origin=viz_share_link
- Side-by-Side Bar Charts to highlight viewer count differences
- Interactive Filters to explore by different personal presentation
- Color-Coded Visuals that reflect mood and contrast
- Tooltips with stream-specific metrics like viewer engagement and days of the week
- Makeup often correlated with higher initial viewership—but not always sustained
- Some of my most engaged audiences came from no-makeup streams
- The data reveals subtle patterns in audience behavior and expectations
As both a streamer and data analyst, I wanted to turn my own stats into a story. This dashboard blends personal insight with analytical rigor, showing how even small choices can have measurable impact.
- Tableau Public for dashboard design and publishing
- Excel for cleaning and structuring my Twitch data
- Markdown for documentation and portfolio polish
- Turning raw stream data into a meaningful narrative
- Designing visuals that are both personal and professional
- Using analytics to reflect on my own content and growth
Welcome to one of my proudest Power BI builds—a vibrant, interactive dashboard that further deep dives into my Twitch streaming metrics. I designed this report to do more than just visualize data—it tells a story. From viewer spikes to chat surges, every insight is wrapped in a sleek, branded experience that reflects both Twitch’s energy and my personal design aesthetic.
Curious to see it in action? View the live dashboard on Power BI.
- Built by Meg: I specialize in transforming raw data into compelling visual narratives. This dashboard is a prime example of how I blend analytical rigor with creative flair.
- Branded & Bold: Styled with Twitch’s iconic purple (#9146FF) and my own branding palette—think deep violets, soft teals, and punchy pinks meets vibrant and earthy greens—this report is as visually engaging as it is informative.
- Interactive Storytelling: With intuitive drill-downs and slicers, users can explore streaming trends, chat activity, and follower growth in just a few clicks.
- Time-Based Drilldowns: Zoom from monthly overviews into daily performance spikes for minutes streamed and max viewers.
- Game-Level Slicers: Filter chat metrics by game to uncover which titles spark the most engagement.
- Metric Toggles: Switch between chatters, messages, and followers to explore different dimensions of audience interaction.
- Custom Color Coding: Every chart and slicer is styled to match Twitch’s vibe and my personal branding—creating a seamless, professional look.
- Layout Precision: Clean, intuitive design ensures users can explore insights without friction.
- Minutes Streamed vs Max Viewers: Track how stream duration correlates with audience peaks.
- Chatters by Game: Discover which games ignite the most conversation.
- Follower Gain vs Live Views: Analyze how visibility translates into community growth.
This dashboard revealed some fascinating patterns in Twitch streaming behavior:
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🎯 Viewer Peaks Don’t Always Align with Stream Length
While longer streams often correlated with higher viewer counts, several short sessions in August and September spiked unexpectedly—suggesting that timing and game choice may outweigh duration. -
🗣️ Guild Wars 2 Dominates Chat Engagement
Among all games streamed, Guild Wars 2 consistently drove the highest number of chatters and messages. It stood out as a community magnet, outperforming more mainstream titles in engagement. -
📈 Follower Growth Mirrors Live View Surges
Follower gains showed a strong correlation with spikes in live views, especially during high-visibility streams in late September. This suggests that visibility and timing are key drivers of audience expansion. -
🎮 Game Choice Impacts Community Activity
Games like Contrast, Fall Guys, and Borderlands 3 triggered notable chat activity, while others like Calico and Fran Bow had quieter but more loyal engagement patterns.
These insights helped me refine how I visualize performance metrics and audience dynamics—turning raw Twitch data into a clear, compelling story.
- Power BI filters, slicers, and drill-through pages
- Custom themes and layout styling
- Data modeling for time-series and categorical analysis