Ender Turing Analysesoftware für Callcenter by Lidiia Suslova is a highly esteemed winner of the very prestigious 2023 A' Design Award in Bronze in Interface-Design Competition Category.
BronzeInterface· 2023
Ender Turing Analysesoftware für Callcenter
Client: Ender Turing
A' Design Award in Bronze Winner in Interface Category
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The Design
About Ender Turing Analysesoftware für Callcenter
Ender Turing ist eine cloudbasierte Softwareplattform für das Qualitätsmanagement in Callcentern. Ein Echtzeit-Dashboard ermöglicht es Supervisoren und Führungskräften, die Leistung anhand von Live-Aktualisierungen zu überwachen. Zu den dargestellten Kennzahlen zählen Anrufvolumen, durchschnittliche Bearbeitungszeit, Erstlösungsquote, Kundenzufriedenheitswerte und Verfügbarkeit der Agenten. Eine automatisierte Vorbewertung von Anrufen und Chats verkürzt die Qualitätsprüfungen, und flexible Filter erlauben es, eine kleine Stichprobe statt sämtlicher Gespräche auszuwählen. Bewertungsbögen lassen sich ohne technische Unterstützung erstellen und bearbeiten. Die Benutzeroberfläche wird in mehr als zehn Sprachen angeboten.
The Recognition
About the A' Design Award in Bronze
Ender Turing Analysesoftware für Callcenter ist Gewinner des A' Design Award in Bronze, einer hochprestigeträchtigen Anerkennung für herausragende Designs, die sich durch Kreativität, Einfallsreichtum und Scharfsinn auszeichnen. Bronze-Gewinner sind reichlich geschickte und auffallend kreative Artefakte, die die große Erfahrung, Fantasie und Findigkeit ihrer Designer belegen. Von Ender Turing Analysesoftware für Callcenter wird erwartet, dass es ein hochgeschätztes, bewundertes und geliebtes Objekt ist, das bemerkenswert professionell und innovativ ist. Dieses mit dem A' Design Award in Bronze prämierte Design verkörpert bewährte Verfahren in Kunst, Wissenschaft, Design und Technologie und ist hervorragend in seiner Liebe zum Detail. Ender Turing Analysesoftware für Callcenter befriedigt Bedürfnisse auf großartige Weise, berührt Wünsche, bezaubert Gefühle und spricht die Neugier an.
Behind the Design
Press Kit
Credits, team members and technical details provided by the designer.
- Unique Properties
- A real-time dashboard allows supervisors and managers to monitor call center KPIs and agent progress with live updates. It displays metrics such as call volume, average handle time, first call resolution, customer satisfaction scores, and agent availability. This helps identify areas of improvement, detect issues, and optimize call center performance through proactive management and data-driven decision-making, leading to improved efficiency, customer satisfaction, and business outcomes.
- Dimensions & Packaging
- The primary function of Ender Turing engine is to help users create and train AI models that can understand and generate human-like language. The platform provides a range of NLP capabilities, including text classification, sentiment analysis, entity recognition, language translation, and text summarization, among others. Users can build custom models using Ender Turing's drag-and-drop interface or integrate pre-trained models into their applications using the platform's API.
- Tags
- Artificial intelligence (AI), Natural language processing (NLP), Machine learning, Text classification, Sentiment analysis, Data processing, Text summarization API, Cloud-based platform, Language modeling, Text mining, Call center, Scoring
- Production Technology
- We used a data-driven design approach to gather feedback for our design, which involved observing and interviewing customers of the product. All of our decisions were based on identifying user pain points and areas of frustration. As a result, we developed a product solution that eliminates most pain points for call center supervisors, increases their productivity, reduces stress and frustration, and features an intuitive UX interface covered with more than 10 language options.
- Design Challenge
- Experiments were done to test hypotheses and validate design decisions. We found that our users are non-technical and prefer a more prominent communication style. We avoid using complex logic constructions and heavy interface decisions. Our UX solutions are continuously simplified.
- Research
- As we maintain ongoing communication with our end users, including data center supervisors and stakeholders, we have collected data through a range of research methods, such as interviews, surveys, and observations.
This has allowed us to gain valuable insights into usesr needs, preferences, and behaviors, which will inform the design of effective solutions that meet their specific requirements. - Inspiration
- Call centers handle up to 1000 calls per agent per day. Measuring and analyzing this data with metrics similar to those used by humans is crucial to improve client service and call center productivity. A productive call center saves businesses revenue and promotes polite and friendly communication with customers, enhancing a business's reputation, improving customer satisfaction, and increasing their overall quality of life.
- Project Duration
- The project started in June 2020 in Tallinn, Estonia. The Design for the Project started at January 2022 and still developing and enhancing. Product was nominated as winner at Latitude59 pitching competition in May 2022, Tallinn, Estonia and took 2nd place at Infoshare Startup Contest where been selected among 500 startups from all over the world in October 2022, Gdansk, Poland.
- Operation Flow
- Our solution provides a 20-fold increase in speed for scoring calls and chats. This is made possible by automated AI pre-scoring and call center quality assurance. Using flexible filters, you can randomly select only a small number of calls and chats for quality monitoring, rather than monitoring all of them.
Moreover, our system allows for flexible setup of scorecards with no limitations. This means that you will no longer need engineers or Excel sheets to modify or create new scorecards. - Patents
- Scientific publications:
1. Transferability Evaluation of Speech Emotion Recognition Between Different Languages
January 2022
DOI:10.1007/978-3-031-04812-8_35
In book: Advances in Computer Science for Engineering and Education (pp.413-426)
Ievgen Iosifov
Olena Iosifova
Oleh Romanovskyi
Vladimir Sokolov
2. Automated Pipeline for Training Dataset Creation from Unlabeled Audios for Automatic Speech Recognition
July 2021
DOI:10.1007/978-3-030-80472-5_3
In book: Advances in Computer Science for Engineering and Education IV (pp.25-36)
Oleh Romanovskyi
Ievgen Iosifov
Olena Iosifova
Vladimir Sokolov
3. Analysis of Automatic Speech Recognition Methods
January 2021
Conference: Cybersecurity Providing in Information and Telecommunication SystemsAt: Kyiv, Ukraine
Olena Iosifova
Ievgen Iosifov
Vladimir Sokolov
Oleh Romanovskyi
Igor Sukaylo
4. Sentence Segmentation from Unformatted Text using Language Modeling and Sequence Labeling Approaches
October 2020
DOI:10.1109/PICST51311.2020.9468084
Conference: 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T)
Ievgen Iosifov
Olena Iosifova
Vladimir Sokolov
5. Methods and components of natural language processing
August 2020 Adaptive automatic control systems 1(36):93-113
DOI:10.20535/1560-8956.36.2020.209780
Olena Iosifova
Ievgen Iosifov
Oleksandr Rolik
6. Techniques Comparison for Natural Language Processing
June 2020
DOI:10.5281/zenodo.3895814
Conference: 2nd International Workshop on Modern Machine Learning Technologies and Data ScienceAt: Lviv-Shatsk, Ukraine
Olena Iosifova
Ievgen Iosifov
Oleksandr Rolik
Vladimir Sokolov
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