Besides reducing the time needed to onboard these young talents, Alfa-bank desired to also achieve the following three objectives:
– to increase the sales volume of new hires in their first months,
– to increase the number of cross-sales of each trainee, and
– to increase customer loyalty.
Based on these project requirements, our developers have set up the roadmap to create a solution capturing all the necessary details. The main functionality, beyond covering specific use cases, was to analyse the answers given by the trainees. This required a sophisticated natural language processing algorithm to be trained based on the specific vocabulary in the banking industry.
Our client has already been using scripts to train its trainees and employees. Therefore, we were able to rely on these scripts to cover the following four customer scenarios:
The main challenge in this project was the customer environment. While the scenarios are rather straight-forward, customers in a real environment will initiate the conversation differently. These manifold ways customers provide clues about their needs are difficult to represent in a simulation. Nonetheless, our developers have analyzed customer behavior together with Alpha Bank to represent a varied number of details in the use cases. The detail richness of our solution ensures that trainees trained with the VR solution will be able to apply their knowledge in a wide range of situations with confidence.
Within two months, a team of XX people has developed the VR simulation. To achieve our objectives, we surveyed both customers and employees, created a comprehensive web application and onboarded the HR team of our client. The main objective hereby was to foster flexibility for the future use of the simulation. We have created the final product on our proprietary XMRS platform which allows our clients to adapt their simulations in the future without any coding knowledge.
The solution provided offers two modes, namely training and exam mode. While in training mode, employees will be able to see a list of possible answers to the respective situation and must speak out loud the one most appropriate in their understanding. The simulation then provides extensive feedback as to why an answer was right or wrong. While in exam mode, no answers are provided, and the trainee needs to answer by themselves with a suitable answer. The challenge hereby was that answers may differ from the script solution but nonetheless be valid. We have covered these events through our conducted interviews.
Our developers have created a speech recognition algorithm which allows Alpha Bank to rate the answers provided by their employees within the training simulation. This allows our client to rate the performance of its employees and tailor further training sessions accordingly.
Our client desired to quantify the impact our VR solution will create and asked us to validate the results with a controlled experiment. Therefore, together with our client, we have separated the next trainee intake into three groups, namely the control group, the VR group and the interactive video group.
The main comparison metrics were the success rate in the simulations, the cross-selling rate and the customer reactions and how positive they were.
Based on these three metrics, the VR group performed in all three metrics 25% above the control group and 21% above the interactive video group. This has empowered our client to roll out the VR training to all trainees with certainty of its high quality.
We have demonstrated the value of speech recognition algorithms and VR simulations when it comes to train and maintain high quality standards. Do you operate in a business with high customer interaction intensity? Discover your potential today and call us.