Talent Search Outil de découverte d'artistes par Qihang Zhang and Ruijingya Tang

Le design Talent Search Outil de découverte d'artistes par Qihang Zhang and Ruijingya Tang est un lauréat très estimé du prestigieux 2025 A' Design Award de Fer dans la catégorie Design d'Interface.

FerInterface· 2025

Talent Search Outil de découverte d'artistes

par Qihang Zhang and Ruijingya Tang

Client : Chartmetric

Lauréat du A' Design Award de Fer dans la catégorie Interface

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Couleurs

Le Design

À propos de Talent Search Outil de découverte d'artistes

Talent Search est un outil web dédié à la détection de talents musicaux. Il aide les professionnels de l'artistique et du répertoire (A&R) à repérer les artistes émergents dotés d'un fort potentiel de croissance. Les données issues du streaming et des réseaux sociaux sont traduites en visualisations interactives claires, avec graphiques, filtres et classements. Un système de couleurs évaluatif facilite la comparaison rapide des indicateurs de performance. Talent Search réduit la dépendance aux réseaux personnels et au jugement subjectif. Le design vise à rendre l'évaluation des talents plus objective, plus efficace et plus ouverte aux nouveaux artistes.

La Reconnaissance

À propos du A' Design Award de Fer

Talent Search Outil de découverte d'artistes est lauréat de l'A' Design Award de Fer, une reconnaissance prestigieuse décernée à de bons designs qui répondent aux exigences professionnelles et industrielles attendues de créations bien conçues. Les lauréats Fer démontrent la grande compétence, la haute spécialisation, la compréhension experte et la capacité créative de leurs créateurs. Talent Search Outil de découverte d'artistes est censé être une création très estimée, admirée et chérie, pratique et innovante. Ce design lauréat de l'A' Design Award de Fer intègre les meilleures pratiques de l'industrie et présente des caractéristiques techniques compétentes associées à un savoir-faire et à du talent. Talent Search Outil de découverte d'artistes est respecté pour sa rigueur et est conçu pour apporter des améliorations de la qualité de vie qui contribuent à faire du monde un monde meilleur.

Les coulisses du design

Dossier de presse

Crédits, membres de l'équipe et détails techniques fournis par le designer.

Propriétés Uniques: 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 & Emballage: 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.
Mots-Clés: Talent scouting, emerging artists, music analytics, data-driven A&R, streaming insights, social media analysis, artist discovery, music industry tool, performance metrics, data visualization
Technologie de Production: 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.
Défi de Conception: 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.
Recherche: 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.
Durée du Projet: 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.
Flux Opérationnel: 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.
Membres de l'Équipe: Qihang Zhang, Ruijingya Tang
Crédits Images: 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