Talent Search Mākslinieku Atklāšanas Rīks by Qihang Zhang and Ruijingya Tang

Talent Search Mākslinieku Atklāšanas Rīks by Qihang Zhang and Ruijingya Tang is a highly esteemed winner of the very prestigious 2025 Dzelzs balva A' Design Award in Saskarnes, mijiedarbības un lietotāja pieredzes dizains Competition Category.

DzelzsSaskarne· 2025

Talent Search Mākslinieku Atklāšanas Rīks

by Qihang Zhang and Ruijingya Tang

Client: Chartmetric

Dzelzs balva A' Design Award Winner in Saskarne Category

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The Design

About Talent Search Mākslinieku Atklāšanas Rīks

Talent Search ir tīmekļa rīks mūzikas talantu meklēšanai. Rīks palīdz repertuāra un talantu meklēšanas profesionāļiem atrast jaunus izpildītājus ar spēcīgu izaugsmes potenciālu. Straumēšanas un sociālo mediju dati tiek pārveidoti skaidrās interaktīvās vizualizācijās ar diagrammām, filtriem un reitingiem. Vērtēšanas krāsu sistēma atbalsta ātru veiktspējas rādītāju salīdzināšanu. Talent Search samazina atkarību no personīgajiem sakariem un subjektīviem spriedumiem. Dizaina mērķis ir padarīt talantu novērtēšanu objektīvāku, efektīvāku un atvērtāku jauniem māksliniekiem.

The Recognition

About the Dzelzs balva A' Design Award

Talent Search Mākslinieku Atklāšanas Rīks ir Dzelzs balvas A' Design Award ieguvējs, prestiža atzinība, ko piešķir labiem dizainiem, kas atbilst profesionālajām un rūpnieciskajām prasībām, kādas sagaidāmas no labi izstrādātiem darbiem. Dzelzs ieguvēji parāda to radītāju lielo prasmi, augsto specializāciju, ekspertu izpratni un radošo spēju. Sagaidāms, ka Talent Search Mākslinieku Atklāšanas Rīks būs augsti vērtēts, apbrīnots un cienīts darbs, praktisks un inovatīvs. Šis ar Dzelzs balvu apbalvotais dizains integrē nozares labāko praksi un tam ir kompetentas tehniskās īpašības, kas saistītas ar zinātību un talantu. Talent Search Mākslinieku Atklāšanas Rīks tiek cienīts par rūpību un ir izstrādāts, lai uzlabotu dzīves kvalitāti un palīdzētu padarīt pasauli labāku.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: Talent Search streamlines music scouting by leveraging data-driven insights to identify emerging artists with strong growth potential. Unlike traditional methods reliant on network referrals, it provides quantifiable performance metrics, reducing bias and scaling global talent discovery. Its intuitive design ensures data interpretability, employing accessible visualizations and an evaluative color system to enhance decision-making for industry professionals.
Dimensions & Packaging: Talent Search runs on Chartmetric’s web-based analytics platform, utilizing a scalable backend to process large volumes of streaming and social data in real time. It employs advanced data analytics for trend detection, statistical normalization techniques for data accuracy, and an interactive front-end with dynamic filtering and visualization capabilities. Optimized for efficiency, it ensures seamless navigation through complex datasets, enabling precise and data-driven talent scouting decisions.
Tags: Talent scouting, emerging artists, music analytics, data-driven A&R, streaming insights, social media analysis, artist discovery, music industry tool, performance metrics, data visualization
Production Technology: Talent Search was developed using a user-centered design approach, integrating industry research, stakeholder interviews, and iterative prototyping. Data visualization techniques enhance interpretability, employing a diverging color scale for evaluative metrics and a sequential scale for neutral data. Built within Chartmetric’s analytics platform, it leverages advanced data analytics to process streaming and social data, delivering actionable insights that empower A&R professionals in talent scouting.
Design Challenge: The biggest challenge was translating complex music industry data into intuitive, actionable insights. A&R teams rely on multiple fragmented sources, and making diverse data—from streaming numbers to social engagement—easily interpretable required extensive iteration. Balancing usability with analytical depth was key. We overcame this by refining data visualization techniques, ensuring clarity without oversimplification, and addressing industry bias by prioritizing transparent, equitable metrics.
Research: We conducted mixed-methods research to address inefficiencies in music talent scouting. The goal was to create a data-driven tool that enhances A&R decision-making. We used stakeholder interviews, competitive analysis, and data analytics to understand user needs. Data was collected through industry consultations and Chartmetric’s database. Participants included A&R teams from record labels, streaming platforms, and management agencies.

Findings revealed that traditional scouting is subjective and network-dependent, making it hard to identify emerging artists early. Our research highlighted the need for transparent, interpretable data to support talent evaluation. Based on these insights, we designed Talent Search to present key growth metrics through interactive visualizations, enabling more informed and efficient scouting.

This innovation has reshaped talent discovery by providing objective, scalable insights that reduce bias and expand access to industry opportunities. By democratizing data, Talent Search allows promising artists—regardless of background—to gain recognition based on measurable success. It streamlines business operations for A&R professionals while fostering a more inclusive and data-driven approach to music scouting.
Inspiration: Talent Search was inspired by the need for a scalable, data-driven approach to music scouting. Traditional methods rely on industry connections and live performances, limiting accessibility and objectivity. Our design leverages advanced analytics to surface promising artists early, empowering professionals with actionable insights. Rooted in research on music industry trends and A&R workflows, it ensures clarity, efficiency, and fairness in talent evaluation.
Project Duration: The project commenced in May 2023 in California and concluded in November 2024. After an 18-month development period, the Talent Search tool was officially launched on November 7, 2024.
Operation Flow: Talent Search allows A&R professionals to discover emerging artists by analyzing streaming and social media trends. Users can explore artists through interactive charts, filters, and rankings that highlight growth potential. The tool simplifies complex data into clear insights, helping users make informed scouting decisions. By presenting key performance metrics in an accessible way, it reduces guesswork and streamlines the process of identifying promising talent efficiently.
Team Members: Qihang Zhang, Ruijingya Tang
Image Credits: Image #1: Illustrator Ruijingya Tang, Talent Search Interface, 2024
Image #2: Illustrator Qihang Zhang, Talent Search Interface, 2024
Image #3: Illustrator Ruijingya Tang, Talent Search Interface, 2024
Image #4: Illustrator Qihang Zhang, Talent Search Interface, 2024
Image #5: Illustrator Ruijingya Tang, Talent Search Interface, 2024