Talent Search Ka Mea Hana ʻImi Mea Pena na Qihang Zhang and Ruijingya Tang

ʻO Talent Search Ka Mea Hana ʻImi Mea Pena na Qihang Zhang and Ruijingya Tang he mea lanakila hanohano loa o ka 2025 A' Design Award Hao ma ka Māhele Hoʻokūkū Hoʻolālā Pilina, Launa a me ʻIke Mea Hoʻohana.

HaoPilina· 2025

Talent Search Ka Mea Hana ʻImi Mea Pena

na Qihang Zhang and Ruijingya Tang

Mea Kūʻai: Chartmetric

Mea Lanakila A' Design Award Hao ma ka Māhele Pilina

15,182

Mea Lanakila i Hōʻoia ʻIa

Hōʻoia i ke Kūlana Makana no #168884

Kipa i ka Pūnaewele Nānā ma A' Design Award Hoʻolaha Nūhou Hōʻailona Makana

Nā Waihoʻoluʻu

Ka Hoʻolālā

E Pili Ana iā Talent Search Ka Mea Hana ʻImi Mea Pena

He mea hana kikowaena pūnaewele ʻo Talent Search no ka ʻimi ʻana i nā mea pena mele. Kōkua kēia mea hana i nā limahana ʻoihana mele e ʻimi i nā mea pena hou me ka hiki nui e ulu. Hoʻohuli ʻia nā ʻikepili kahe a me ka pāpaho pūnaewele i mau kiʻi hōʻike ʻike maopopo a hana pū, me nā pakuhi, nā kānana, a me nā papa inoa koho. Kōkua kekahi ʻōnaehana kala loiloi i ka hoʻohālikelike wikiwiki ʻana o nā helu hana. Hōʻemi ʻo Talent Search i ka hilinaʻi ʻana i nā pilina pilikino a me ka manaʻo pilikino wale nō. Manaʻo ke kēia hoʻolālā e hoʻolilo i ka loiloi mea pena i mea maopopo hou aku, wikiwiki hou aku, a ʻoi aku ka hāmama i nā mea pena hou.

Ka Hoʻomaikai

E Pili Ana i ka A' Design Award Hao

Ua lanakila ka hoʻolālā Talent Search Ka Mea Hana ʻImi Mea Pena i ka A' Design Award Hao, he ʻike hoʻohanohano i hāʻawi ʻia i nā hoʻolālā maikaʻi e hoʻokō ana i nā koi ʻoihana a ʻoihana hana i manaʻo ʻia mai nā mea hoʻokumu i hana maikaʻi ʻia. Hōʻike nā lanakila Hao i ka mākau nui, ka loea kiʻekiʻe, ka ʻike akamai a me ka hiki hana noʻeau o ka poʻe i hana iā lākou. Manaʻo ʻia ʻo ka hoʻolālā Talent Search Ka Mea Hana ʻImi Mea Pena he mea hoʻokumu i mahalo nui ʻia, hoʻohiwahiwa ʻia a aloha ʻia e pono a hou. ʻO kēia hoʻolālā i lanakila i ka A' Design Award Hao e hoʻohui ana i nā hana maikaʻi loa o ka ʻoihana a loaʻa nā ʻano ʻenehana mākaukau i hui pū ʻia me ka ʻike hana a me ka makakoho. Mahalo ʻia ka hoʻolālā Talent Search Ka Mea Hana ʻImi Mea Pena no kona nānā pono a ua hoʻolālā ʻia e hāʻawi i nā hoʻomaikaʻi ola e kōkua ai i ka hana ʻana i ka honua i wahi maikaʻi aku.

Ma Hope o ka Hoʻolālā

ʻEke Nūhou

Nā hōʻoia, nā lālā hui a me nā kikoʻī ʻenehana i hāʻawi ʻia e ka mea hoʻolālā.

Nā ʻAno Kūʻokoʻa: 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.
Nā Ana a me ka Hoʻopili: 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.
Nā Lepili: Talent scouting, emerging artists, music analytics, data-driven A&R, streaming insights, social media analysis, artist discovery, music industry tool, performance metrics, data visualization
ʻEnehana Hana: 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.
Pilikia Hoʻolālā: 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.
Noiʻi: 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.
Hoʻoulu Manaʻo: 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.
Ka Lōʻihi o ka Papahana: 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.
Kaʻina Hana: 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.
Nā Lālā Hui: Qihang Zhang, Ruijingya Tang
Nā Kuleana Kiʻi: 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