Talent Search Ártista Jekuaauka Rembiporu Qihang Zhang and Ruijingya Tang omba'apóva

Talent Search Ártista Jekuaauka Rembiporu Qihang Zhang and Ruijingya Tang omba'apóva ha'e rembiporuarã oñemba'eguaséva 2025 A' Design Award Fiero pegua Jehechaukaha Jejapo Ñeha'ã Categoría-pe.

FieroJehechaukaha· 2025

Talent Search Ártista Jekuaauka Rembiporu

Qihang Zhang and Ruijingya Tang -gua

Mba'eporuhára: Chartmetric

A' Design Award Fiero Rembiporuarã Jehechaukaha Categoría-pe

15,182

Premio Rembiporuarã Oñemoneĩva

Emoneĩ Premio Reko #168884 Peg̃ua

Eike Tendápe Ehecha A' Design Award-pe Marandu Myasãi Mba'ete Jeguerohory

Sa'y

Diseño

Talent Search Ártista Jekuaauka Rembiporu Rehegua

Talent Search ha'e peteĩ web rehegua tembiporu música mba'e katupyry jehekarãva. Ko tembiporu oipytyvõ umi profesional artista ha repertorio jehekarãvape ojuhu hag̃ua ártista opu'ãva ha ikatupyryetéva. Streaming ha redes sociales rehegua mba'ekuaarã ojehecha porã hag̃uáicha ojehai jey grafiko, filtro ha ranking reheve, interactivo ha kláro. Peteĩ sistema ára colores mba'e mba'eporãngue ohechauka omoirũva ojoavy hag̃ua pya'e umi rendimiento apopyre. Talent Search ombyaikuei tekotevẽ umi kuatiahai retãygua ha ñe'ẽ jejapo subjetivo rehe. Ko diseño ojapose talento jehechakuaa oiko hag̃ua hetave objetivo, hetave eficiente ha ijurujáva umi ártista pyahúpe g̃uarã.

Jeguerohory

A' Design Award Fiero Rehegua

Talent Search Ártista Jekuaauka Rembiporu ohupyty A' Design Award Fiero, peteĩ ñehechakuaa prestigioso oñeme'ẽva diseño iporã-pe ohupytýva requisito profesional ha industrial oñeha'ãrõva creación iporã oñemoĩva-gui. Umi ganador Fiero ohechauka habilidad guasu, especialización yvate, comprensión experta ha capacidad creativa umi creador rehegua. Oñeha'ãrõ Talent Search Ártista Jekuaauka Rembiporu ha'eha creación ojehayhúva, admirada ha estimada, práctica ha innovadora. Ko diseño ohupytýva A' Design Award Fiero ombojoaju mejor práctica industria rehegua ha oguereko característica técnica competente ojoajúva conocimiento ha talento ndive. Talent Search Ártista Jekuaauka Rembiporu oñerespeta hembiapo cuidadoso rupi ha oñemoĩ ome'ẽ hag̃ua mejora calidad de vida rehegua oipytyvõva yvy ape iporãve hag̃ua.

Diseño Rapykuéri

Marandu Aty

Diseñador ome'ẽva'ekue crédito, aty pegua ha mba'e técnico.

Mba'e Iñambuéva: 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.
Tuichakue ha Ñemyenyhẽ: 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.
Ñe'ẽ Rape: Talent scouting, emerging artists, music analytics, data-driven A&R, streaming insights, social media analysis, artist discovery, music industry tool, performance metrics, data visualization
Ñeapopy Tecnología: 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.
Diseño Jepy'apy: 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.
Ñesẽheka: 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.
Inspiración: 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.
Proyecto Ára Tuichakue: 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.
Mba'apo Rape: 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.
Aty Rembiguái: Qihang Zhang, Ruijingya Tang
Ta'ãnga Mba'eñemoneĩ: 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