StreamsCharts
Making streaming analytics useful for streamers, advertisers, and decision-makers
year
2023
Category
UX Bootcamp case (real client)
Problem
Streamscharts tracks streaming analytics across platforms like Twitch and YouTube. It’s used by streamers, brands, and esports teams to keep an eye on performance.
Their Overview section was meant to give users a quick read on platform performance, but it wasn’t performing. Most users ignored it, and stakeholders weren’t confident it was adding value. We were brought in to figure out why, and how to fix it.
Problem
Streamscharts tracks streaming analytics across platforms like Twitch and YouTube. It’s used by streamers, brands, and esports teams to keep an eye on performance.
Their Overview section was meant to give users a quick read on platform performance, but it wasn’t performing. Most users ignored it, and stakeholders weren’t confident it was adding value. We were brought in to figure out why, and how to fix it.
Problem
Streamscharts tracks streaming analytics across platforms like Twitch and YouTube. It’s used by streamers, brands, and esports teams to keep an eye on performance.
Their Overview section was meant to give users a quick read on platform performance, but it wasn’t performing. Most users ignored it, and stakeholders weren’t confident it was adding value. We were brought in to figure out why, and how to fix it.
My role
This was a truly collaborative project with four designers working across the UX process. I was hands-on throughout:
Helped shape the research plan and ran user interviews
Synthesised insights into user personas and journey maps
Co-led competitor and UX pattern audits
Contributed to problem framing and “How Might We” workshops
Designed wireframes, interaction flows, and final UI directions
Participated in usability testing and validation
Presented the outcomes to the client team
My role
This was a truly collaborative project with four designers working across the UX process. I was hands-on throughout:
Helped shape the research plan and ran user interviews
Synthesised insights into user personas and journey maps
Co-led competitor and UX pattern audits
Contributed to problem framing and “How Might We” workshops
Designed wireframes, interaction flows, and final UI directions
Participated in usability testing and validation
Presented the outcomes to the client team
My role
This was a truly collaborative project with four designers working across the UX process. I was hands-on throughout:
Helped shape the research plan and ran user interviews
Synthesised insights into user personas and journey maps
Co-led competitor and UX pattern audits
Contributed to problem framing and “How Might We” workshops
Designed wireframes, interaction flows, and final UI directions
Participated in usability testing and validation
Presented the outcomes to the client team
User interviews
To design something that actually worked, we needed to understand how streamers think and what they need from analytics. We spoke to creators of all kinds: from aspiring Twitch newbies to professional streamers. Here’s what came up again and again:
Beginners found the analytics overwhelming and aimed mostly for basic stats.
Most weren’t sure how to use the data.
Many were unclear on what influenced spikes or drops in performance.
Most needed only a few metrics to make decisions (average viewers, watch time).
Some needed to compare platforms but did not know how.
User interviews
To design something that actually worked, we needed to understand how streamers think and what they need from analytics. We spoke to creators of all kinds: from aspiring Twitch newbies to professional streamers. Here’s what came up again and again:
Beginners found the analytics overwhelming and aimed mostly for basic stats.
Most weren’t sure how to use the data.
Many were unclear on what influenced spikes or drops in performance.
Most needed only a few metrics to make decisions (average viewers, watch time).
Some needed to compare platforms but did not know how.
User interviews
To design something that actually worked, we needed to understand how streamers think and what they need from analytics. We spoke to creators of all kinds: from aspiring Twitch newbies to professional streamers. Here’s what came up again and again:
Beginners found the analytics overwhelming and aimed mostly for basic stats.
Most weren’t sure how to use the data.
Many were unclear on what influenced spikes or drops in performance.
Most needed only a few metrics to make decisions (average viewers, watch time).
Some needed to compare platforms but did not know how.
Persona & Journey mapping
Based on the data we collected during the interviews, we created a streamer user persona and mapped their journey from encountering a problem to achieving success with the help of the platform. This helped us visualise drop-off points and highlight what users actually tried to do.
Persona & Journey mapping
Based on the data we collected during the interviews, we created a streamer user persona and mapped their journey from encountering a problem to achieving success with the help of the platform. This helped us visualise drop-off points and highlight what users actually tried to do.
Persona & Journey mapping
Based on the data we collected during the interviews, we created a streamer user persona and mapped their journey from encountering a problem to achieving success with the help of the platform. This helped us visualise drop-off points and highlight what users actually tried to do.
Information Architecture Test
We suspected even the name of the page could be part of the problem. To validate this assumption, we ran a quick IA test with ~100 participants, asking them to complete 3 short tasks across different versions of the page label:
Overview
Platforms
Platforms Overview
Platforms Overview performed best, helping users locate the page faster.
Information Architecture Test
We suspected even the name of the page could be part of the problem. To validate this assumption, we ran a quick IA test with ~100 participants, asking them to complete 3 short tasks across different versions of the page label:
Overview
Platforms
Platforms Overview
Platforms Overview performed best, helping users locate the page faster.
Information Architecture Test
We suspected even the name of the page could be part of the problem. To validate this assumption, we ran a quick IA test with ~100 participants, asking them to complete 3 short tasks across different versions of the page label:
Overview
Platforms
Platforms Overview
Platforms Overview performed best, helping users locate the page faster.
14%
14%
14%
Success
Overview
Overview
38%
38%
38%
Success
Success
Platforms
Platforms
51%
51%
51%
Success
Success
Platforms overview
Platforms overview
Competitor audit
We reviewed 11 competitor platforms and broke down:
Which metrics they showed up front
How filtering and comparison worked
UX patterns used to simplify dashboards
Competitor audit
We reviewed 11 competitor platforms and broke down:
Which metrics they showed up front
How filtering and comparison worked
UX patterns used to simplify dashboards
Competitor audit
We reviewed 11 competitor platforms and broke down:
Which metrics they showed up front
How filtering and comparison worked
UX patterns used to simplify dashboards
Framing the Challenge
We ran “How Might We…” sessions to reframe problems into design opportunities:
How might we help users compare streaming platforms more easily?
How might we reduce cognitive overload and surface the right data at the right time?
How might we make trends and shifts feel understandable?
How might we let users adapt the page to their personal goals or metrics?
These questions helped shape the design direction: from page layout to filters and visual hierarchy.
Framing the Challenge
We ran “How Might We…” sessions to reframe problems into design opportunities:
How might we help users compare streaming platforms more easily?
How might we reduce cognitive overload and surface the right data at the right time?
How might we make trends and shifts feel understandable?
How might we let users adapt the page to their personal goals or metrics?
These questions helped shape the design direction: from page layout to filters and visual hierarchy.
Framing the Challenge
We ran “How Might We…” sessions to reframe problems into design opportunities:
How might we help users compare streaming platforms more easily?
How might we reduce cognitive overload and surface the right data at the right time?
How might we make trends and shifts feel understandable?
How might we let users adapt the page to their personal goals or metrics?
These questions helped shape the design direction: from page layout to filters and visual hierarchy.
Page 2: Individual platform pages
The platform-specific pages already existed, but they weren’t answering some of the most important questions users had.
Understanding spikes
To help users make sense of sudden changes, we added event markers directly on the performance graphs. Now, if a big event like TwitchCon or a major release causes a spike, users can see when it happened and even click through to read more — helping them connect the dots between real-world events and their data.
Platform activity
Streamers wanted to know when the best time to go live was. We added a weekly activity heatmap showing when each platform is most active, based on the past month’s data. It gives a quick visual overview of peak times — super useful for planning streams.
Language stats
Language segmentation wasn’t visible before. We introduced a language stats section to show platform performance by language (average and peak viewers/channels). This is useful not just for streamers trying to find their niche, but also for marketers identifying target audiences by region or language.
Page 2: Individual platform pages
The platform-specific pages already existed, but they weren’t answering some of the most important questions users had.
Understanding spikes
To help users make sense of sudden changes, we added event markers directly on the performance graphs. Now, if a big event like TwitchCon or a major release causes a spike, users can see when it happened and even click through to read more — helping them connect the dots between real-world events and their data.
Platform activity
Streamers wanted to know when the best time to go live was. We added a weekly activity heatmap showing when each platform is most active, based on the past month’s data. It gives a quick visual overview of peak times — super useful for planning streams.
Language stats
Language segmentation wasn’t visible before. We introduced a language stats section to show platform performance by language (average and peak viewers/channels). This is useful not just for streamers trying to find their niche, but also for marketers identifying target audiences by region or language.
Page 2: Individual platform pages
The platform-specific pages already existed, but they weren’t answering some of the most important questions users had.
Understanding spikes
To help users make sense of sudden changes, we added event markers directly on the performance graphs. Now, if a big event like TwitchCon or a major release causes a spike, users can see when it happened and even click through to read more — helping them connect the dots between real-world events and their data.
Platform activity
Streamers wanted to know when the best time to go live was. We added a weekly activity heatmap showing when each platform is most active, based on the past month’s data. It gives a quick visual overview of peak times — super useful for planning streams.
Language stats
Language segmentation wasn’t visible before. We introduced a language stats section to show platform performance by language (average and peak viewers/channels). This is useful not just for streamers trying to find their niche, but also for marketers identifying target audiences by region or language.
Page 3: Platforms comparison
We also created a full platform comparison page that lets users add multiple platforms and compare their core metrics side by side. This page gives them a much deeper dive than the overview, making it ideal for streamers, analysts, or marketers who need to make informed decisions based on platform performance, growth trends, or language breakdowns. It’s accessible directly from both the Platforms overview and individual platform pages for quick access.
Page 3: Platforms comparison
We also created a full platform comparison page that lets users add multiple platforms and compare their core metrics side by side. This page gives them a much deeper dive than the overview, making it ideal for streamers, analysts, or marketers who need to make informed decisions based on platform performance, growth trends, or language breakdowns. It’s accessible directly from both the Platforms overview and individual platform pages for quick access.
Page 3: Platforms comparison
We also created a full platform comparison page that lets users add multiple platforms and compare their core metrics side by side. This page gives them a much deeper dive than the overview, making it ideal for streamers, analysts, or marketers who need to make informed decisions based on platform performance, growth trends, or language breakdowns. It’s accessible directly from both the Platforms overview and individual platform pages for quick access.
What Happened Next
We ran light validation sessions with users to check if our ideas were landing — and they were. The final designs doubled success rates in basic navigation tasks (like finding a platform’s key stats), and overall feedback showed a clearer, more actionable page.
The final prototype was handed back to the Streamscharts team. They had in-house designers who would take the implementation forward. Months later, we saw our ideas live on the platform. It was great to see our thinking help shape the next evolution.
What Happened Next
We ran light validation sessions with users to check if our ideas were landing — and they were. The final designs doubled success rates in basic navigation tasks (like finding a platform’s key stats), and overall feedback showed a clearer, more actionable page.
The final prototype was handed back to the Streamscharts team. They had in-house designers who would take the implementation forward. Months later, we saw our ideas live on the platform. It was great to see our thinking help shape the next evolution.
What Happened Next
We ran light validation sessions with users to check if our ideas were landing — and they were. The final designs doubled success rates in basic navigation tasks (like finding a platform’s key stats), and overall feedback showed a clearer, more actionable page.
The final prototype was handed back to the Streamscharts team. They had in-house designers who would take the implementation forward. Months later, we saw our ideas live on the platform. It was great to see our thinking help shape the next evolution.
what i learned
Designing for complexity doesn’t mean designing more.
Even when you’re entering a niche space with tons of data, the challenge is often the same: clarity over cleverness. You don’t need to know everything about the industry upfront, but you do need to talk to people, dig into their needs, and figure out what they’re really trying to do.
Most of the time, design in not about adding more — it’s about stepping back, reorganising what’s already there, and making it make sense. A great insight isn’t just about what you’re showing, it’s about helping people understand what to do with it.
what i learned
Designing for complexity doesn’t mean designing more.
Even when you’re entering a niche space with tons of data, the challenge is often the same: clarity over cleverness. You don’t need to know everything about the industry upfront, but you do need to talk to people, dig into their needs, and figure out what they’re really trying to do.
Most of the time, design in not about adding more — it’s about stepping back, reorganising what’s already there, and making it make sense. A great insight isn’t just about what you’re showing, it’s about helping people understand what to do with it.
what i learned
Designing for complexity doesn’t mean designing more.
Even when you’re entering a niche space with tons of data, the challenge is often the same: clarity over cleverness. You don’t need to know everything about the industry upfront, but you do need to talk to people, dig into their needs, and figure out what they’re really trying to do.
Most of the time, design in not about adding more — it’s about stepping back, reorganising what’s already there, and making it make sense. A great insight isn’t just about what you’re showing, it’s about helping people understand what to do with it.