Turn operational data into a better customer journey.
Mobility services generate data from vehicles, infrastructure, schedules, ticketing systems, weather services, and other operational systems. For the operator, these signals are essential for understanding what is happening across the network. For the customer, what matters is much simpler: knowing what is happening and what it means for their journey.
D4 can connect these different sources and turn operational events into contextual information that can be delivered directly to customer facing applications and services.
Customers experience the disruption, but rarely see the context.
A delayed vehicle, a missed connection, or a change in service can be caused by many different events. Vehicle position, traffic, weather, infrastructure problems, schedules, and downstream connections may all contribute to what a customer ultimately experiences.
Operational systems may contain this information, but they are generally designed to help the operator manage the network rather than explain it to the customer.
The challenge is turning complex operational data into timely information that is relevant to an individual journey.
Connect operational events with the journey around them.
D4 can combine live vehicle and infrastructure data with schedules, location, weather, traffic, and other operational information.
A workflow can determine what is happening, establish how it affects the current service, and combine that with information about the customer's journey or the wider network.
For example, a delayed vehicle can be correlated with its current location, the expected arrival time, the next connection, and other relevant service information. Instead of simply exposing the raw delay, D4 can produce a structured result that explains the operational impact.
Governed AI can be used where interpretation is useful. It can turn structured operational context into a clear explanation or recommendation, while the workflow controls what information the model receives and how its response can be used.
The final result can be delivered through a customer facing API to a mobile app, website, notification service, digital display, or other customer channel.
Operational data connected to the customer journey.
- Vehicle data
Location, speed, status, and real time movement of vehicles. - Schedule data
Planned departure, arrival, route, and connection information. - Infrastructure data
Events and status information from stations, roads, tracks, or other infrastructure. - Traffic and environmental data
Traffic conditions, weather, and other external factors affecting the network. - Service events
Delays, cancellations, disruptions, changes, and operational incidents. - Journey data
The route, connections, and relevant context needed to understand the impact on an individual journey. - Historical data
Previous operational events and journey patterns that can provide additional context.
Give customers information that actually helps.
Instead of simply telling a customer that a service is delayed, a customer facing application can provide the information that matters to them.
A notification might explain that a vehicle is delayed, whether a connection is still possible, and what the expected impact is on the journey. The same underlying operational data can also be used by internal teams to understand network performance and identify recurring problems.
D4 creates a separation between the complexity of the operational data and the simplicity of the customer experience. The customer sees a clear answer while the platform handles the data, context, workflow, and processing behind it.
This allows operators to create richer customer experiences without requiring every customer facing application to connect directly to every underlying operational system.
Want to turn operational data into a better customer experience?
Talk to us about the data behind your customer journey and what you would like to make possible.
