Interview about Chartmetric Mobile Music Analytics App, winner of the A' Mobile Technologies, Applications and Software Design Award 2025
The Chartmetric Mobile App revolutionizes music analytics by providing real time insights in a sleek, mobile optimized interface. Designed for industry professionals, it offers instant access to artist performance metrics, audience demographics, and playlist tracking. Unique features include interactive data visualizations, smart alerts, and seamless cross platform integration, enabling precise, data driven decision making in a fast-paced music landscape. Performance enhancements ensure faster data retrieval, while intuitive navigation and dashboards improve usability, making it more powerful.
View detailed images, specifications, and award details on A' Design Award & Competition website.
View Design DetailsAbsolutely. The journey began with a question: how can we make Chartmetric’s deep, often overwhelming music analytics feel lightweight, fast, and usable—on a phone?Chartmetric is widely used by artists, labels, managers, and marketers who rely on a wide range of data: playlist placements, follower growth, streaming trends, social insights, and more. The desktop version is powerful, but for mobile, we knew we had to rethink everything from the ground up—not just shrink the experience, but redesign it for a completely different context of use.As the lead designer on the project, I focused on translating this data-heavy environment into a smooth, mobile-first experience. I worked closely with product and engineering to identify the core scenarios where people actually needed data on the go—during meetings, backstage, while traveling—and prioritized features accordingly: Smart Filters, Artist Search, Audience Stats, and Real-Time Trends became the core of our MVP.The UI system was rebuilt entirely in Figma, optimized for thumb-friendly access, fast browsing, and clarity under pressure. I introduced modular cards, adaptive layouts, and collapsible stats that allowed users to zoom in and out of detail as needed. Every chart and metric was redesigned to be instantly scannable. I also implemented a fresh visual system that brought in Chartmetric’s branding with darker, elegant tones and subtle gradients, elevating the experience while staying accessible and performance-friendly.We developed natively on both iOS and Android using SwiftUI and Jetpack Compose, which allowed us to iterate rapidly while maintaining a premium feel. Motion played a key role too—micro-interactions helped guide users through dense information without adding friction.We validated everything through testing with real users: music executives, agents, indie artists, even tour managers. Their feedback drove refinements in information hierarchy, loading states, and shortcuts. They wanted something that felt powerful but didn’t demand effort—and we delivered.Winning the Silver A’ Design Award was a meaningful moment. It recognized not just the final visuals, but the intentional, user-driven approach behind them. This wasn’t just a mobile app—it was a shift in how music professionals access and understand their data, wherever they are.
Our decision to prioritize interactive data visualizations stemmed from one core insight: in the music industry, timing is everything. Whether you’re a label exec reviewing an artist’s momentum before a pitch meeting, or a tour manager checking city-level engagement on the road, you need clarity—fast.Traditional data dashboards often assume you’re sitting at a desk with time to analyze. But on mobile, attention spans are short, network conditions vary, and users often check data between tasks. That inspired us to design visual elements that could instantly communicate change, without requiring interpretation.We focused on clean, responsive charts that show growth trends, playlist jumps, and audience changes at a glance. For example, sparkline graphs next to follower counts or a swipeable carousel of top-performing tracks allowed users to get the full picture in seconds. These visualizations weren’t just pretty—they were functional tools designed for pattern recognition and rapid scanning.The interactivity came from asking: what if users could act on insights right from the visualization? Tap to dive deeper, long-press to compare with a peer artist, or swipe to preview another platform’s data. We built these micro-interactions to remove friction and make exploration feel fluid, not heavy.From a design standpoint, we also knew that color, contrast, and motion needed to be thoughtful—this wasn’t just about aesthetics, but cognitive load. I chose a darker UI theme with vibrant accents to highlight actionable trends while reducing visual fatigue, especially during frequent daily use.Ultimately, these visual elements enhance decision-making by empowering users to spot what matters most, right when it happens. In a fast-paced industry where a viral moment can change everything overnight, our goal was to make sure users were never a step behind—no matter where they were.
User research was the foundation of this app—without it, we would’ve risked building a tool that looked nice but didn’t work in the real world of music professionals.We began with a series of interviews and usability tests across different segments: indie artists, label A&Rs, DSP editors, and even music educators. One pattern became immediately clear—users often checked data in short bursts, and what they needed wasn’t everything, but what’s changed. That insight drove the creation of the swipeable milestone cards.These cards surface significant events—like “added to a top playlist,” “follower spike,” or “crossed 1M streams”—and let users browse them with a single thumb swipe. It mirrors the way people naturally flip through stories or feeds, but each card is dense with context. I wanted to balance emotional impact ("your track is trending in Brazil") with strategic value ("consider retargeting this region"). The swipe pattern keeps it lightweight, while the content stays meaningful.The smart alerts system came from similar research. Many users were overwhelmed by data noise—they didn't want a daily report of 50 metrics, but they did want to know when something big happened. So we introduced tiered thresholds and contextual triggers: alerts only appear when there's a notable deviation or milestone, not just routine activity. The system also learns from user behavior over time, fine-tuning what “notable” means based on past interactions.We tested early versions of both features with artists on tour, marketers in campaign cycles, and executives in pitch meetings. Their feedback led to improvements like stacked card previews, customizable alert settings, and support for multiple languages and genres.By grounding our features in real workflows—not assumptions—we created a mobile experience that feels alive, responsive, and truly helpful. In a fast-moving industry, surfacing the right insight at the right time makes all the difference.
Integrating multiple data sources like Spotify, Apple Music, TikTok, and YouTube sounds straightforward—but in reality, each platform speaks a different “language,” updates on its own schedule, and defines success differently. Designing a unified, real-time mobile experience on top of that complexity was one of our biggest challenges.From a product and design perspective, one of the first issues we encountered was data latency. While Spotify updates certain stats hourly, TikTok might have a longer delay, and YouTube’s metrics fluctuate depending on content type. This inconsistency created friction in how we displayed timelines, comparisons, and trend summaries—if we weren’t careful, we risked showing users misleading or outdated insights.To solve this, we worked closely with our backend and data teams to implement a synchronization layer that flagged each data source with freshness metadata. In the app, I designed subtle visual cues (like timestamp badges and dimmed trend lines) to help users instantly know whether a stat was truly “real-time” or last updated hours ago. This built trust without overwhelming users with technical noise.Another challenge was standardizing metric definitions. For example, what counts as “engagement” on TikTok isn’t the same as it is on YouTube. I led the effort to unify terminology and reorganize dashboards by intent rather than by platform—for instance, grouping by “Audience Growth” or “Content Virality” rather than source. That decision made comparisons more intuitive and user actions more focused.We also needed to optimize for performance. Pulling and rendering cross-platform data in real time on mobile is taxing. I collaborated with engineering to design a staggered loading experience: users see high-priority data first (like follower spikes), while less urgent metrics load in the background. Motion and placeholder states help smooth over delays and keep the experience feeling fast and modern.Ultimately, the goal wasn’t just to show all the data—it was to show the right data, at the right time, in a way that felt consistent, reliable, and actionable. And that meant bridging technical realities with thoughtful UX every step of the way.
Balancing comprehensive analytics with the constraints of mobile interfaces was one of the most intellectually demanding aspects of designing the Chartmetric Mobile App. Our desktop platform is trusted by thousands of music professionals worldwide for its breadth of data—spanning playlist performance, social metrics, audience geography, market-level trends, and more. But bringing that level of complexity to mobile without overwhelming users required a deliberate and systems-level design approach.My first step was to deconstruct user goals by role and scenario: What does an A&R executive need in a meeting? What does a manager want to check before a campaign launch? What insights does an indie artist seek while on tour? By identifying the most time-sensitive, high-value interactions across user types, I was able to define a core analytics layer suitable for mobile consumption—without sacrificing strategic depth.I designed an adaptive card-based layout that surfaces key metrics upfront—followers, playlist adds, chart movements—with the ability to tap into deeper views as needed. This hierarchical structure allowed for a professional-grade experience while maintaining clarity and responsiveness on smaller screens. I also implemented modular dashboards that reorganize automatically based on content type and screen size, ensuring consistent usability across devices.The challenge was not just visual compression, but information prioritization and cognitive load management. I worked closely with our data and product teams to simplify language, reduce redundant metrics, and create visual cues—such as color-coded trend indicators and collapsible sections—to help users process data quickly and accurately.From a UX architecture standpoint, I introduced progressive disclosure techniques that enable power users to dive into layered insights, while allowing casual users to stop at headline metrics. This dual-mode interaction model was critical to maintaining our professional integrity without alienating users less familiar with data analysis.Furthermore, I collaborated with engineers to ensure that performance stayed smooth even with dynamic, multi-source datasets. By using native frameworks like SwiftUI and Jetpack Compose, and optimizing for asynchronous loading and offline caching, we preserved a premium, real-time feel that music professionals expect.In short, I treated mobile not as a limitation, but as an opportunity to distill complexity into clarity. The result is a tool that professionals can trust in high-pressure environments—without losing access to the depth that makes Chartmetric essential to their work.
When designing the push notification system for the Chartmetric Mobile App, we knew that value had to come before volume. Music professionals are constantly bombarded with notifications—from social media, DSPs, and internal communication channels—so anything we introduced had to be timely, relevant, and immediately actionable.Rather than sending generic updates, we focused on identifying event-based triggers that would carry strategic meaning depending on the user’s role. For example, an A&R executive might care about early-stage momentum (such as a track charting on a viral playlist), while a digital marketer may prioritize geographic spikes or follower surges that could inform targeting. While we did not implement full persona-based notification customization in the first release, the foundational logic was informed by real user workflows.To guide this prioritization, I participated in several rounds of qualitative user interviews during the early research phase—speaking with label reps, indie artists, and music marketing teams. We asked them directly: “What type of alert would make you take action immediately?” Their responses were clear. Notifications needed to highlight deviation from normal patterns—not routine metrics. That insight shaped our focus on alerts for playlist adds, sudden growth, chart debuts, or drops, rather than static updates.Working with product and data teams, we categorized our notification system around high-signal, low-noise events—milestones that could influence strategic decisions or reflect shifts in an artist’s trajectory. I then translated these events into a clear visual and content system, ensuring alerts were concise, branded, and easy to act on. Each notification directs users into a relevant view within the app, rather than simply surfacing raw data.Although deeper persona-based customization is still part of our longer-term roadmap, the initial system was purposefully designed to serve cross-functional roles by focusing on shared priorities: traction, timing, and turning points. In the fast-moving world of music, those are the alerts that truly matter.
One of the most unexpected insights that emerged during development was just how emotionally driven many decisions in the music industry still are—even among data-savvy professionals. We went into the project assuming that users primarily wanted precision, depth, and dashboards. And while that’s certainly true, we discovered that professionals often use data as a narrative tool, not just an analytical one.For example, an indie artist might not open the app looking to analyze audience retention curves—but they will check if they’ve crossed a milestone, like 10K followers or a playlist add from a tastemaker. Those moments carry emotional weight. Similarly, A&R reps use data not only to filter talent, but also to build stories they can pitch to their internal teams. That reframed how we thought about the product: not just a utility, but a source of validation, momentum, and storytelling.This insight directly influenced features like the swipeable milestone cards, which highlight meaningful events in a narrative format. It also shaped the tone of the copy, the visual hierarchy, and even the design of notifications—favoring clarity and confidence over technical jargon.Another unexpected finding was how often people used the app collaboratively, even though it’s technically a single-user experience. Managers would screenshot data to send to labels, marketers would airdrop visual charts during team meetings, and artists would share audience stats with potential collaborators. These behaviors highlighted the need for information that’s not just consumable—but shareable and persuasive.Finally, we saw that speed and certainty often trump comprehensiveness. Users were less interested in exploring every data point, and more focused on what’s changed, what’s urgent, and what’s actionable. That guided our design decisions around information prioritization, quick summaries, and push-based updates.In short, we entered the project thinking about analysts—and we ended up designing for storytellers, collaborators, and decision-makers under pressure. That shift in mindset was one of the most meaningful outcomes of the entire design process.
The design of the Chartmetric Mobile Music Analytics App was grounded in a broader, accelerating shift in how professionals interact with data: moving from static dashboards to dynamic, context-aware analytics—especially on mobile.In recent years, we’ve seen a clear trend toward “decision-oriented design”—visualizations are no longer just about presenting numbers clearly, but about guiding users to what matters most, in the least amount of time. That principle shaped our entire approach: instead of overwhelming users with dense graphs or spreadsheets, we focused on lightweight, modular components that surface trends, anomalies, and milestones with clarity and intent.The use of swipeable cards, smart filters, and condensed trend lines wasn’t just a UI choice—it was a response to how mobile users behave. They’re time-constrained, often distracted, and need insight at a glance. This aligns with the broader design evolution toward “progressive complexity”—starting with simple summaries that can expand into detailed views if needed, a pattern we fully adopted through collapsible stats, interactive graphs, and layered navigation.Another major trend we tapped into is the increasing importance of motion and micro-interactions in data tools. Motion isn’t just decorative—it communicates state changes, confirms actions, and makes transitions feel natural. We used animation deliberately to soften the transitions between views, reinforce hierarchy, and help users build mental models as they explore layered data.Importantly, we also recognized that mobile analytics tools must be emotionally intelligent—providing information in a way that respects cognitive load and encourages trust. This meant using clear language, accessible contrast, and a visual system that reflects professionalism and stability, not overwhelm.Ultimately, the app reflects a convergence of several trends: mobile-first thinking, minimalist UI for complex systems, and a growing expectation that even the most powerful data tools should feel intuitive. We didn’t just design a visualization layer—we designed an experience that helps users take action with confidence, which is where true accessibility lies.
As the music industry becomes increasingly global, digital, and data-driven, the expectations placed on mobile analytics tools will continue to rise. Looking ahead, I see several meaningful directions where the Chartmetric Mobile App—and mobile music analytics as a whole—can evolve to meet these shifting demands.First, there’s a growing need for hyper-personalized insights. As users grow more sophisticated, they don’t just want access to raw data—they want to know what it means for them. I envision future versions of the app offering AI-powered contextual recommendations, where data isn’t just displayed but interpreted. For example, if an artist is gaining unexpected traction in a new country, the app could suggest audience engagement strategies or timing for a targeted release. These insights would need to be lightweight, explainable, and action-ready, especially on mobile.Second, the increasing blending of social, video, and streaming platforms calls for better cross-platform narrative tools. Rather than viewing TikTok, Spotify, and YouTube separately, professionals need holistic timelines and fan behavior mapping across channels. Mobile apps can play a critical role in stitching these fragmented stories together in a visual, digestible way—perhaps through multi-source overlays or audience journey maps.Third, I believe in a future where collaboration is more deeply embedded into the mobile experience. Today, many users screenshot data and send it via chat. But what if teams could annotate a trendline, share a milestone card in-app, or create a lightweight report together—directly from mobile? As remote work continues and campaign cycles speed up, design can support real-time, on-the-go decision-making among distributed teams.Lastly, as the industry continues to confront issues around equity, localization, and representation, there’s opportunity for mobile analytics tools to surface non-obvious success—from emerging genres, underserved markets, or overlooked creators. Designing features that support discovery beyond the mainstream will be crucial in shaping a more inclusive music ecosystem.In short, I see the future of mobile music analytics not just as faster or smarter—but as more human-centered: tools that not only present data, but elevate the strategic and creative decisions behind the music itself.
My core advice is this: don’t start with the data—start with the decision. Designers working with complex analytics often feel the need to represent every metric, every filter, and every dimension. But mobile users rarely open an app just to explore; they open it because they want to understand something quickly or make a decision confidently. Your job as a designer is to shorten the distance between insight and action.One of the most valuable lessons I learned while designing the Chartmetric Mobile App is the power of constraints. Mobile devices force you to be intentional. Every pixel has to earn its place. That means deeply understanding why a metric matters in context, and how users interpret it when they’re in motion—often multitasking or under pressure.I also encourage designers to think in layers of clarity. Not everything needs to be visible upfront. Use progressive disclosure, collapsible sections, and microinteractions to create a flow that rewards exploration without demanding it. Let users get the top-line story immediately, with the option to dive deeper only when needed.Another principle I’d emphasize is designing for pattern recognition, not just presentation. When working with trendlines, comparisons, or timelines, your visuals should help users see change, not just numbers. Design charts that highlight movement, detect anomalies, and tell visual stories—this builds user confidence and speeds up comprehension.And finally, listen actively—not just to what users ask for, but to what they struggle with, repeat, or ignore. In our case, features like milestone cards and smart alerts didn’t emerge from a product wishlist—they came from observing real workflows and unmet needs across roles.In short: clarify, prioritize, and humanize. Your success isn’t measured by how much data you show—but by how many decisions you help someone make, confidently and fast.
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