Periodic Reporting for period 1 - TRACS (Commercialisation of TRACS, An Artificial Intelligence Inspired, Text Response Automation system for Customer Support)
Reporting period: 2017-08-01 to 2017-11-30
Over €11bn in Europe per annum is spent globally to deliver text-based customer service. However, as 60-80% of customer queries are simple and repetitive a huge opportunity for improved customer experience and cost savings exists in automating parts of the agent workflow.
The project is aimed at addressing the market need for an effective and affordable customer service experience using an advanced artificial intelligence tools called TRACS (Text Response Automation system for Customer Support). TRACS supplies the customer service agents with response suggestions to the customers’ inquiries. This frees up agent time and improves customer satisfaction (See figure). TRACS has demonstrated automation levels of 59.7%, estimated to save 34.0% of the agent’s time per inquiry.
The first phase of the project is a commercial feasibility study. Upon validation of the commercial viability, the second phase is aimed at rapid commercialisation of TRACS in Europe and globally.
The project is aimed at addressing the market need for an effective and affordable customer service experience using an advanced artificial intelligence tools called TRACS (Text Response Automation system for Customer Support). TRACS supplies the customer service agents with response suggestions to the customers’ inquiries. This frees up agent time and improves customer satisfaction (See figure). TRACS has demonstrated automation levels of 59.7%, estimated to save 34.0% of the agent’s time per inquiry.
The first phase of the project is a commercial feasibility study. Upon validation of the commercial viability, the second phase is aimed at rapid commercialisation of TRACS in Europe and globally.
A Client Working Group (CWG) consisting of 7 diverse members was established via a systematic onboarding and sales process. Multiple activities were undertaken to assess TRACS’ performance in industry settings with the CWG members. Qualitative and quantitative feedback was collected through all stages.
The feasibility study reinforced TRACS’ strong business case. Some members of CWG have already purchased TRACS and others are in late stages of the sales process. The outcome of the study has been used to identify barriers to rapid commercialisation of TRACS. A detailed commercialisation plan was established for phase 2 of the project.
The feasibility study reinforced TRACS’ strong business case. Some members of CWG have already purchased TRACS and others are in late stages of the sales process. The outcome of the study has been used to identify barriers to rapid commercialisation of TRACS. A detailed commercialisation plan was established for phase 2 of the project.
TRACS performed well on not only short dialogues, such as live chat and tweets, but also on longer conversations like emails (which represents the largest market share).
TRACS, unlike its competition, was shown to also perform well even on small dataset sizes. This allows Small and Medium Enterprises (SMEs) to use TRACS. Successful market penetration of TRACS would mean 24x7 customer service to customers and superior customer experience that is affordable to all SMEs boosting economic growth both in Europe and globally.
Adoption of TRACS will lead to currently offshored agents being re-shored, resulting in improved EU job creation. In the future, TRACS’ generic algorithm can analyse this data to identify consumer preferences and demand, allowing businesses to transform the customer service function into a powerful strategic tool, driving additional revenues.
TRACS, unlike its competition, was shown to also perform well even on small dataset sizes. This allows Small and Medium Enterprises (SMEs) to use TRACS. Successful market penetration of TRACS would mean 24x7 customer service to customers and superior customer experience that is affordable to all SMEs boosting economic growth both in Europe and globally.
Adoption of TRACS will lead to currently offshored agents being re-shored, resulting in improved EU job creation. In the future, TRACS’ generic algorithm can analyse this data to identify consumer preferences and demand, allowing businesses to transform the customer service function into a powerful strategic tool, driving additional revenues.