What CX can learn from the taxi industry
This is not as easy as it sounds. Different staff have varying levels of capability, knowledge and experience, and tend to offer customers very different engagement experiences. The challenge is not only to keep staff brains ‘trained’ in the latest version of the desired customer engagement code but to ensure they apply this code, in context, in the same way.
Unfortunately, people tend to forget much of what they are taught. They also have different levels of engagement and motivation, which results in huge variations in how they translate what questions to ask when; what answers to give based on different responses; and what actions to take based on various business rules, customer decisions and contexts.
The push towards omnichannel exponentially increases the complexity of this challenge. Instead of training human workers to apply contextual engagement logic, you now also need to train and control different digital workers (chatbots, virtual assistants, virtual advisors).
Digital workers also need their brains coded with the latest prescribed engagement formula. And because each digital worker tends to be coded by a different team using a different technology and coding approach, the chances of them delivering a consistent experience across digital channels is low.
If you look at the spread of digital workers out there, most are struggling to give you a specific answer to a specific question, let alone navigate you through the desired customer journey.
Getting staff and digital workers within each channel to sing off the same hymn sheet is difficult enough. Now, add the additional complexity of delivering a consistent, compliant and context-relevant customer journey across channels to the mix. This means orchestrating multiple workers at multiple touchpoints to seamlessly guide a customer to the right outcome in the best possible way.
The concept is powerful. It places the customer at the centre and shapes journeys off their specific needs and channel preferences. Getting this right requires you to change from a product-centred to a customer-centred mindset. You also need to design adaptive processes that can adjust to different customer needs, rather than force customers through generic decision tree pathways that are built for company, not customer, convenience.
How to do this?
The taxi industry offers companies a viable approach to consider. It found a way to overcome the journey routing problem by converting their road maps into digital navigators. GPS navigators saved drivers from having to learn and interpret maps.
Drivers are automatically routed down the best pathways, based on their specific context. As a result, they can become productive far quicker and can focus their energy on enhancing their customer’s experience rather than recalling roads and routes. They were also spared the trouble of having to keep logbooks to prove the journeys they took – every trip is automatically tracked for them. Not only does this make billing more accurate, but it also offers invaluable journey insights for businesses to optimise their efforts.
The same can now be done for companies looking to digitise their customer journeys. Rather than investing in teams to document more detailed maps and trying to track where customers clicked on a website, they can rather build journey navigators that are capable of guiding staff and digital workers through each end-to-end customer journey, passing from one channel to the other in a consistent, compliant and context-relevant way.
These journey navigators can also, where required, hand over to robotic process automation (RPA) bots to perform required system functions in context, before then taking over again and guiding the next worker through the next part of the journey - again, in the context of what has happened before.
The implications of this are significant. Journey navigators allow companies to code end-to-end journey logic in a single format that all workers can leverage. One source of journey logic can then be used to guide multiple forms of workers through a different part of a journey so they don’t need to be trained on any of the ‘roads’ at all.
Navigators also can hand over to RPA bots where relevant, to optimise end-to-end journey automation. Plus, by keeping an updated journey record, as a chatbot hands over to a contact centre agent, who then hands over to an RPA bot who then passes it back to a courier for dispatch and delivery, the context of the journey is always carried across and it automatically shapes the subsequent decisions and actions taken.
This not only ensures a consistent, compliant and context-relevant journey, irrespective of the level of ‘training’ that the impacted workers have been given, it also ensures that a detailed journey record is always available for compliance, insights and machine learning purposes.
Journey navigators, therefore, allow companies to overcome the challenge of delivering a consistent experience across channels and ensure that desired customer journeys translate to context-relevant customer experiences without wholly depending on a trained and experienced workforce.
As journey navigation moves into the mainstream, end-to-end journey automation is increasingly becoming a reality. It’s about time.
