Tlanāhuatīlli Talent Search Tlahtlanextiloni Tlaixmatilistli ītēchcopa Qihang Zhang and Ruijingya Tang cē cencā mahuizzō tēmacēhualōni īpan huēyi 2025 Mahuizolli A' Design Award Tepoztli īpan Tlaixnamiquiliztli, Nenonotzaliztli ihuan Tlatequipanoliznemiliztli Tlachihchihualiztli Nēhuilīztli Tlamantli.
TepoztliTlaixnamiquiliztli· 2025
Talent Search Tlahtlanextiloni Tlaixmatilistli
īpal Qihang Zhang and Ruijingya Tang
Tlanāhuatīlli: Chartmetric
Mahuizolli A' Design Award Tepoztli Tēmacēhualōni īpan Tlaixnamiquiliztli Tlamantli
Tlaneltīlīlli Tēmacēhualōni
Xictlaneltilia Tēmacēhualli ītēchcopa #168884Tlanēxtilistli
Ītechcopa Talent Search Tlahtlanextiloni Tlaixmatilistli
Talent Search se tlahtlanextiloni tlen web tlen kitemoa tlacah akin cualli tlacaquiliztli quipiah itech cuicatl. Nin tlahtlanextiloni quinpalehuia in tequitiltin akin quitemoah huan quitlaliah cuicatl (artist and repertoire) inic quinextican yancuic tlaixmatinih akin huelis huei mohuicazqueh. In tlaixmachiotl tlen streaming huan social media mocuepa tlaixnextilli huan tetlapaleuiloni ica machiotl, ichtequiloni huan tlatecpanaliztli. Se cualli tlapalli tlanahuatiloni tepalehuia ma monequiltican achitzin ihuan achitzin ompa tlen quineltoca. Talent Search quitlacihuia ma amo miec monequi tlacah teixmatilistli huan iyollo tlanextiliztli. In neltocalistli quinequi ma yezqui ocachi melahuac, ocachi cualli huan ocachi tlapouhqui ipampa yancuic tlaixmatinih.
Tēixīmachōtiliztli
Ītechcopa Mahuizolli A' Design Award Tepoztli
Talent Search Tlahtlanextiloni Tlaixmatilistli ca in quicuic in Mahuizolli A' Design Award Tepoztli, tlamahuizoliztli tlen momaca in cualli dizayno in quitlalia in tlen monequi ipan tequitl ihuan tlachihualiztli in quimaca in cualli tlachihualli. In quicuicah Tepoztli quinextia in hueyi tlamatiliztli, toltecayotl ihuan ihuelitiliztli intlachihuanime. Ca quinequi in Talent Search Tlahtlanextiloni Tlaixmatilistli ca tlazohtli, mahuiztic, yancuic ihuan motequiuhtia. Ni dizayno in quicuic Tepoztli quihuelitia in tlamatiliztli ihuan quipia chicahualiztli tlen tepoztli. Talent Search Tlahtlanextiloni Tlaixmatilistli quicualtia in nemiliztli ihuan quihuelitia in cemanahuac ica cualli.
Tlanēxtilistli Ītēixpan
Āmatl Tlanextīliztli
Tlapōhualli, tēquitqueh īwan tēchmachilīztli ōquinmaca in tlanēxtīlīlli.
- Cē Zan Ītēchcopa
- 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.
- Huēyiliztli īhuān Tlacualtepēhualli
- 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.
- Tōcāitl
- Talent scouting, emerging artists, music analytics, data-driven A&R, streaming insights, social media analysis, artist discovery, music industry tool, performance metrics, data visualization
- Tlachīhualiztli Māchiyōtl
- 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.
- Tlanāhuatīlli Nētēcahuilīztli
- 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.
- Tlatēmōliztli
- 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. - Tēyōllālīliztli
- 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.
- Tēquitl Cāhuitl
- 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.
- Tēquitl Ōhuitl
- 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.
- Calpolli Tlācah
- Qihang Zhang, Ruijingya Tang
- Īxiptla Tlanēxtīlli
- 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
Tlacōhualli
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