Customer Experience Training: Waiting at the Station

The first time learners use Bodyswaps, an onboarding sequence familiarises them with the features of the app, takes them through an avatar selection and embodiment activity, and prepares them for the experience to come. 

In the onboarding, learners will: 

• Find out how this training is different from the rest
• Select their avatar
• Discover their virtual journal
• Learn how to navigate and use the tools and settings

After the onboarding activity, the learner meets Fawiza, a member of station staff, on the platform. She introduces the importance of good customer service skills and highlights the positive impact they can have on a customer’s journey. She explains that this module allows the learner to practise these skills in a safe environment without real-world stakes.

Next, the learner is introduced to Jeremy’s situation: he is meeting friends for lunch in High Wycombe before going on to Wembley Stadium. Unfortunately, his train has been delayed and he’s concerned about the impact to his plans.

The learner is then invited to answer a few Likert-type survey questions to gauge their confidence about the following key skills:

• Handling customers who are in a heightened emotional state
• Putting the customer in control of the solution
• Making the customer feel valued

These self-reflection questions will be repeated in the debrief at the end, to assess how the learner’s confidence levels have changed.

Note: If you wish to receive data about how the learner’s confidence levels have changed as a consequence of the training, it’s important that they complete this introduction and the debrief at the end.

To demonstrate what customer service skills look like in practice, the learner watches a panicked Jeremy try to get information about his delayed train and how it will affect his plan from Fawiza, who is engaged in talking to another customer.

In this observation activity, the learner clicks or taps the ‘Good’ button whenever they witness Fawiza react appropriately and helpfully and the ‘Bad’ button whenever she reacts inappropriately or unhelpfully. Visual feedback is provided in real time to indicate whether the learner has identified each example.

As the conversation progresses, it becomes clear that Fawiza’s divided attention is being taken by Jeremy as deliberate unhelpfulness, and he becomes more and more frustrated. When she is unable to provide the information that he needs to work out how the delay will affect the rest of his journey, he breaks off angrily.

At the end, the learner receives a summary feedback panel showing buttons that indicate which events were identified. Clicking each one allows the learner to replay Fawiza’s good and bad reactions and see an explanation of how they helped or hindered the situation.

At this point, it’s time for the learner to try taking the reins and help Jeremy. Before they do, they’re given some advice about how best to proceed in a way that will calm Jeremy down.

In this freeform interaction, the learner is invited to speak to Jeremy in their own words, keeping a conciliatory tone and maintaining their professionalism. Behind the scenes, analytics tools pick up on the keywords and rate of speech that demonstrate whether or not the learner is staying calm, apologising, and offering help in a way that will de-escalate the situation.

Once the learner has said their piece, they swap bodies with Jeremy to see how their speech looked from his point of view. After that, they receive the feedback from the analytics tools to help refine their performance, at which point they can either try again to achieve a better result or move on to the next topic.

Now that Jeremy is feeling more at ease, the learner can help him regain control of his journey and feel like a welcome and respected customer.

In this scaffolded conversation, the learner chooses how to respond to Jeremy in a sequence of six multiple-choice exchanges. Once each response is chosen from the list of three, Jeremy answers, after which more detailed feedback is given to show the learner the benefits (and drawbacks, if applicable) of the answer they selected.

At each stage, the learner’s goal is to select the response that encapsulates all three criteria of good customer service: good handling of customer emotion, putting the customer in control, and making the customer feel valued. These ideal responses calm Jeremy down and help him plot the next steps of his journey, showing the learner the positive impact of good service. Responses that meet only two criteria may help Jeremy find a way forward, but don’t leave him feeling valued, or vice versa – and responses that don’t meet any only antagonise him.

Finally, the scene changes to the train carriage, where the learner sees Jeremy discuss the success of his journey over the phone with his friends. Depending on how good a service the learner provided, his mood and prospects may have improved significantly despite the delay – or become much worse.

At the end of the conversation, the learner is shown some summary feedback on the direction of their responses as a whole. This also highlights which criteria the learner’s answers skewed towards, or whether they managed to hit all three.

The Likert-type survey questions from the start of the course are repeated here, to gauge the change in the learner’s confidence after playing through the module.

Note: With soft skills training, it is not unusual to find that learners’ confidence levels actually fall upon completion. This is because people are often overconfident in their ability to communicate or empathise before the training begins. As the experience raises self-awareness, confidence levels may fall in response.