Talent Search Sesebelisi sa ho Fumana Baetsi ba Bonono ka Qihang Zhang and Ruijingya Tang

Moralo oa Talent Search Sesebelisi sa ho Fumana Baetsi ba Bonono ka Qihang Zhang and Ruijingya Tang ke mohlodi oa khau e hlomphehang haholo ya 2025 Moputso oa Tšepe oa A' Design Award Mokhahleong oa Tlhodisano oa Moralo wa Sebopeho, Tshebedisano le Boiphihlelo ba Mosebedisi.

TšepeSebopeho· 2025

Talent Search Sesebelisi sa ho Fumana Baetsi ba Bonono

ka Qihang Zhang and Ruijingya Tang

Moreki: Chartmetric

Mohlodi oa Moputso oa Tšepe oa A' Design Award Mokhahleong oa Sebopeho

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Mohlodi oa Khau ea Netefaditsweng

Netefatsa Boemo ba Khau bakeng sa #168884

Etela Sebaka Sheba ho A' Design Award Tokollo ya Boraditaba Baeche ya Moputso

Mebala

Moralo

Mabapi le Talent Search Sesebelisi sa ho Fumana Baetsi ba Bonono

Talent Search ke sesebelisi se thehiloeng inthaneteng bakeng sa ho batla batho ba nang le talenta ea 'mino. Sesebelisi sena se thusa litsebi tsa baetsi ba bonono le repertoire ho fumana baetsi ba bonono ba hlahang ba nang le monyetla o matla oa kholo. Data ea streaming le mecha ea litaba tsa sechaba e fetoleloa ho ba ponahatso e hlakileng le e sebetsanang, e nang le litšoantšo tsa likhomphutha (charts), lisefo, le maemo. Mokhoa oa mebala oa tekolo o thusa papiso e potlakileng ea litekanyetso tsa tshebetso. Talent Search e fokotsa boitshetleho ho marang-rang a botho le kahlolo ea maikutlo. Moralo ona o ikemiselitse ho etsa hore tekolo ea talenta e be ntlha e hlakileng, e sebetsang hantle le e bulehileng haholoanyane ho baetsi ba bonono ba bacha.

Kamohelo

Mabapi le Moputso oa Tšepe oa A' Design Award

Talent Search Sesebelisi sa ho Fumana Baetsi ba Bonono ke mohapi oa Moputso oa Tšepe oa A' Design Award, kananelo e hlomphehang e fuoang meralo e metle e finyellang litlhoko tsa porofeshenale le tsa indasteri tse lebelletsoeng ho lintho tse hlahisitsoeng tse entsoeng hantle. Bahapi ba Tšepe ba bontša bokhoni bo boholo, bokhethehi bo phahameng, kutloisiso ea litsebi le bokhoni ba boqapi ba baqapi ba bona. Talent Search Sesebelisi sa ho Fumana Baetsi ba Bonono e lebelletsoe ho ba ntho e hlahisitsoeng e hlomphuoang haholo, e ratoang le e ratehang, e sebetsang le e nang le mehopolo e mecha. Moralo ona o hapileng Moputso oa Tšepe oa A' Design Award o kenyelletsa mekhoa e metle ka ho fetesisa ea indasteri mme o na le litšobotsi tsa theknoloji tse nang le bokhoni tse amanang le tsebo le talenta. Ka lebaka la botlalo ba eona, Talent Search Sesebelisi sa ho Fumana Baetsi ba Bonono e tšoanelehela tlhompho mme e entsoe ho fana ka ntlafatso ea bophelo e thusang ho etsa hore lefatše le be sebaka se molemo.

Ka Mora Moralo

Sete ya Boraditaba

Litlhaku, ditho tsa sehlopha le lintlha tsa botekgeniki tse fanoeng ke moetsi wa moralo.

Boleng bo Ikhethang: 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.
Boholo le Phuthelo: 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.
Lithegi: Talent scouting, emerging artists, music analytics, data-driven A&R, streaming insights, social media analysis, artist discovery, music industry tool, performance metrics, data visualization
Theknoloji ya Tlhahiso: 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.
Phephetso ya Moralo: 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.
Dipatlisiso: 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.
Kgothaletso: 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.
Nako ya Projeke: 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.
Tsamaiso ya Mosebetsi: 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.
Litho tsa Sehlopha: Qihang Zhang, Ruijingya Tang
Litlotla tsa Setshwantsho: 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