Talent Search Taputapu Kimi Kaitoi nā Qihang Zhang and Ruijingya Tang

Ko te hoahoa Talent Search Taputapu Kimi Kaitoi nā Qihang Zhang and Ruijingya Tang he kaitoa whakahirahira o te 2025 A' Design Award Rino i te Wāhanga Whakataetae Hoahoa Atanga, Tauwhitiwhiti me te Wheako Kaiwhakamahi.

RinoAtanga· 2025

Talent Search Taputapu Kimi Kaitoi

nā Qihang Zhang and Ruijingya Tang

Kiritaki: Chartmetric

Kaitoa o te A' Design Award Rino i te Wāhanga Atanga

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Kaitoa Tohu Manatokohia

Manatokohia te Tūnga Tohu mō #168884

Torohia te Pae Tirohia i te A' Design Award Pānui Pāpāho Tohu Tohu

Ngā Tae

Te Hoahoa

Mō Talent Search Taputapu Kimi Kaitoi

He taputapu ipurangi a Rapu Toi mō te rapu tāleti puoro. Ka āwhina tēnei taputapu i ngā tohunga kaitito me te repertoire ki te kimi i ngā kaitoi e puta ake ana kei a rātou te kaha nui ki te tipu. Ka whakawhitia ngā raraunga toha ripene me ngā pāpāho pāpori hei whakaahua ā-kanorau mārama, whakaporowhitatanga, e whai ana i ngā kauwhata, ngā tātari me ngā rangatū. He pūnaha tae aromatawai e tautoko ana i te whakatairite tere o ngā ine mahi. Ka whakaitihia e Rapu Toi te whakawhirinaki ki ngā hononga whaiaro me te whakatau ā-tangata. Ko te whāinga o te hoahoa kia kaha ake te tōkeke, te whaihua me te tuwhera ki ngā kaitoi hōu i te aromatawai tāleti.

Te Whakamihi

Mō te A' Design Award Rino

Ko Talent Search Taputapu Kimi Kaitoi te toa o te A' Design Award Rino, he whakaaetanga whai mana e hoatu ana ki ngā hoahoa pai e whakatutuki ana i ngā hiahia ngaio me te ahumahi e tūmanakohia ana mai i ngā mahi kua hoahoatia pai. Ko ngā toa Rino e whakaatu ana i te pukenga nui, te tohungatanga teitei, te māramatanga mātanga me te kaha auaha o ō rātou kaihanga. E tūmanakohia ana ko Talent Search Taputapu Kimi Kaitoi he mahi whakanuia, whakamīharotia, aroha nui, he whaihua, he auaha hoki. Ko tēnei hoahoa i toa i te Rino e whakakotahi ana i ngā tikanga pai rawa o te ahumahi, ā, he āhuatanga hangarau pūkenga tōna e hono ana ki te mōhio me te pūmanawa. E whakahonoretia ana a Talent Search Taputapu Kimi Kaitoi mō tōna tōtika, ā, i hoahoatia hei whakapai ake i te kounga o te oranga me te āwhina i te ao kia pai ake.

I Muri i te Hoahoa

Kete Pāpāho

Ngā whakamihi, ngā mema o te rōpū me ngā taipitopito hangarau i whakaratohia e te kaihoahoa.

Āhuatanga Motuhake: 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.
Inenga & Pēketanga: 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.
Tūtohu: Talent scouting, emerging artists, music analytics, data-driven A&R, streaming insights, social media analysis, artist discovery, music industry tool, performance metrics, data visualization
Hangarau Whakanao: 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.
Wero Hoahoa: 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.
Rangahau: 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.
Whakaaweawe: 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.
Roanga o te Kaupapa: 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.
Rerenga Mahi: 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.
Ngā Mema o te Rōpū: Qihang Zhang, Ruijingya Tang
Whakamana Whakaahua: 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