Talent Search Ngwa Nchọpụta Ndị Nkà nke Qihang Zhang and Ruijingya Tang

Ihe emepụtara bụ Talent Search Ngwa Nchọpụta Ndị Nkà nke Qihang Zhang and Ruijingya Tang bụ onye meriri a na-asọpụrụ nke ukwuu nke 2025 Ihe Nrite A' Design Award nke Igwe na Udi Asọmpi Nhazi Ihu Ngwá Ọrụ, Mmekọrịta na Ahụmịhe Onye Ọrụ.

IgweIhu Ngwá Ọrụ· 2025

Talent Search Ngwa Nchọpụta Ndị Nkà

nke Qihang Zhang and Ruijingya Tang

Onye Ahịa: Chartmetric

Onye Meriri Ihe Nrite A' Design Award nke Igwe na Udi Ihu Ngwá Ọrụ

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Onye Meriri Onyinye A Kwadoro

Nyochaa Ọnọdụ Onyinye maka #168884

Gaa Saịtị Lee na A' Design Award Akụkọ Mgbasa Ozi Akara Onyinye

Agba

Nhazi a

Maka Talent Search Ngwa Nchọpụta Ndị Nkà

Talent Search bụ ngwa dabere na weebụ maka ịchọ ndị nkà egwu nwere ogo ọsọ. Ngwa a na-enyere ndị ọrụ ha bụ nchọpụta na nhazi ndị egwu aka ịchọta ndị nkà na-apụta ọhụrụ nwere ike ukwuu ịzụlite. A na-atụgharị data sitere na streaming na mgbasa ozi mmekọrịta ọha na eze ka ọ bụrụ eserese ndị doro anya na ndị mmadụ nwere ike iji aka ha rụọ ọrụ, gụnyere charts, ihe nzacha na ndepụta ọkwa. Usoro agba nyocha na-enyere aka ime nlele ngwa ngwa nke ọnụọgụgụ arụmọrụ. Talent Search na-ebelata ịdabere na mmekọrịta onwe onwe na ikpe aro nke onye kpọrọ ihe. Nhazi a bu n'obi ime ka nyocha nkà ghọọ ihe kwụụrụ ọtọ karịa, dịkwa mfe karịa, ma na-emeghekwara ohere maka ndị nkà ọhụrụ.

Nkwanye Ugwu

Maka Ihe Nrite A' Design Award nke Igwe

Talent Search Ngwa Nchọpụta Ndị Nkà meriri A' Design Award nke Igwe, nnabata dị ugwu e nyere design ndị dị mma nke na-emezu ihe ndị a chọrọ n'ọrụ na ụlọ ọrụ nke a na-atụ anya n'ihe e kere eke ndị e mere nke ọma. Ndị meriri na Igwe na-egosi nka buru ibu, ọkachamara dị elu, nghọta ọkachamara na ikike imepụta nke ndị kere ha. A na-atụ anya na Talent Search Ngwa Nchọpụta Ndị Nkà ga-abụ ihe e kere eke a na-asọpụrụ nke ukwuu, a na-eto na a hụrụ n'anya nke bụ ihe bara uru ma dị ọhụrụ. Design a meriri A' Design Award nke Igwe na-ejikọta ụzọ kacha mma nke ụlọ ọrụ ma nwee àgwà teknụzụ kwesịrị ekwesị jikọtara na ihe ọmụma na talent. A na-asọpụrụ Talent Search Ngwa Nchọpụta Ndị Nkà maka nlezianya ya ma e mere ya ka ọ nye mmeziwanye ndụ nke na-enyere aka ime ka ụwa bụrụ ebe ka mma.

N'azụ Nhazi a

Ngwugwu Mgbasa Ozi

Nkwurịta okwu, ndị otu na nkọwa teknụzụ nke onye nhazi nyere.

Àgwà Pụrụ Iche: 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.
Nha & Mkpuchi: 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.
Mkpado: Talent scouting, emerging artists, music analytics, data-driven A&R, streaming insights, social media analysis, artist discovery, music industry tool, performance metrics, data visualization
Teknụzụ Mmepụta: 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.
Ịma Aka Imepụta: 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.
Nchọpụta: 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.
Mkpali: 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.
Oge Ọrụ: 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.
Usoro Ọrụ: 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.
Ndị Otu: Qihang Zhang, Ruijingya Tang
Asụsụ Foto: 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