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Ready for the future of customer interaction ?
Join leading Swiss companies already embracing AI. Discover how Heidi can improve your customer service experience.
Redefining Passenger Support at TransPennine Express with Conversational AI
How TPE achieved 99.5% first-contact resolution and cut response times to just 3 seconds with Enterprise Bot
About TransPennine Express
TransPennine Express (TPE) is a British train operating company providing intercity rail services across the North of England and into Scotland. Known for connecting key cities like Manchester, Liverpool, Leeds, Newcastle, and Edinburgh, TPE plays a crucial role in the UK’s regional transportation.
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About Rhein-Main-Verkehrsverbund
The Rhein-Main-Verkehrsverbund (RMV) is one of the largest public transport networks in Germany, covering the Frankfurt Rhine-Main area. RMV operates a comprehensive network of regional rail services, buses, trams, and commuter trains, serving over 800 million passengers annually. As a key player in public transportation, RMV is dedicated to improving passenger experiences through digital innovation.
To achieve this, RMV partnered with Enterprise Bot and ACP Digital to implement a scalable, AI-powered support solution.
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Client: Rhein-Main-Verkehrsverbund (RMV)
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Solution: AI-powered Chatbot, Email Bot, and Voice Bot (upcoming)
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Objective: Improve customer service efficiency, reduce redundant queries, and enhance agent productivity
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with a request body that specifies how to map the columns of your import file to the associated CRM properties in HubSpot.... In the request JSON, define the import file details, including mapping the spreadsheet's columns to HubSpot data. Your request JSON should include the following fields:... entry for each column.
The Challenge
TransPennine Express faced the common challenges of the transport industry:
Although the chatbot was initially implemented only in the Help & Contact section, it already handled over 2,000 monthly queries.
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with a request body that specifies how to map the columns of your import file to the associated CRM properties in HubSpot.... In the request JSON, define the import file details, including mapping the spreadsheet's columns to HubSpot data. Your request JSON should include the following fields:... entry for each column.
The Challenge
RMV faced increasing pressure on its customer service teams due to:
With growing passenger demand and expanding services, RMV sought an innovative solution to automate and streamline customer support processes.
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with a request body that specifies how to map the columns of your import file to the associated CRM properties in HubSpot.... In the request JSON, define the import file details, including mapping the spreadsheet's columns to HubSpot data. Your request JSON should include the following fields:... entry for each column.
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Penny: A Digital Assistant for Modern Rail Travel
TPE’s chatbot “Penny”, based on Microsoft Azure’s Open AI Models, helps streamline customer communication and reduce pressure on support teams.
Key Capabilities:
Key Capabilities:
- Build a Conversational AI solution
- Available 24/7 to assist passengers
- Integrated with Darwin real-time departure and disruption feed (the UK rail industry’s official live train information system) and Journey Checker
- Integrated with knowledge base and LLM to answer FAQs accurately
- WhatsApp escalation handling integrated with their social dashboard
- Reduction of outdated information through continuous content improvements
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with a request body that specifies how to map the columns of your import file to the associated CRM properties in HubSpot.... In the request JSON, define the import file details, including mapping the spreadsheet's columns to HubSpot data. Your request JSON should include the following fields:... entry for each column.
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with a request body that specifies how to map the columns of your import file to the associated CRM properties in HubSpot.... In the request JSON, define the import file details, including mapping the spreadsheet's columns to HubSpot data. Your request JSON should include the following fields:... entry for each column.
Smarter Response Through Parallel Orchestration
Penny doesn’t just answer questions—it thinks fast. By running multiple processes in parallel, Penny ensures passengers receive the most accurate and relevant responses in record time.
- User stress level analysis (scoring sentiment from -1 to +1) to adapt tone and style of responses
- Persona classification (e.g., business traveller, family, accessibility needs) for more personalised interactions
- Query classification for faster and more accurate routing
- Parallel orchestration: stress, persona, and query analysis run simultaneously, dramatically speeding up response times
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with a request body that specifies how to map the columns of your import file to the associated CRM properties in HubSpot.... In the request JSON, define the import file details, including mapping the spreadsheet's columns to HubSpot data. Your request JSON should include the following fields:... entry for each column.
What our customer says
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“We are really pleased with Penny, our TPE chatbot powered by Enterprise Bot, who has come on leaps and bounds in recent months, with improved live train advice, faster responses, even better tone of voice and understanding and reaction to customer sentiment.”
Colin Kelly
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with a request body that specifies how to map the columns of your import file to the associated CRM properties in HubSpot.... In the request JSON, define the import file details, including mapping the spreadsheet's columns to HubSpot data. Your request JSON should include the following fields:... entry for each column.
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Implementation Journey
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Implemented in November 2024 -
Initially limited to the Help section, now expanding to more pages
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Feedback loop helped refine bot responses and UI placement
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Integrations with knowledge base and live disruption feeds provides accurate information when necessary
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with a request body that specifies how to map the columns of your import file to the associated CRM properties in HubSpot.... In the request JSON, define the import file details, including mapping the spreadsheet's columns to HubSpot data. Your request JSON should include the following fields:... entry for each column.
GenAI Insights: Turning Data Into Action
Enterprise Bot’s GenAI Insights dashboard gives TPE unprecedented visibility into customer interactions and service performance. This isn’t just analytics—it’s intelligence that drives decision-making.
- First contact resolution rates
- Reasons for escalations to agents
- Average time before escalation occurs
- Trends in sentiment and satisfaction
With this level of insight, TPE can identify escalation patterns, track efficiency gains, and continuously optimise Penny to meet evolving passenger expectations.
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with a request body that specifies how to map the columns of your import file to the associated CRM properties in HubSpot.... In the request JSON, define the import file details, including mapping the spreadsheet's columns to HubSpot data. Your request JSON should include the following fields:... entry for each column.
Future Outlook
Future Outlook
- Expansion of bot presence across more site pages
- Planned integrations with live train disruption systems
- Potential rollout of production-ready voice assistants
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with a request body that specifies how to map the columns of your import file to the associated CRM properties in HubSpot.... In the request JSON, define the import file details, including mapping the spreadsheet's columns to HubSpot data. Your request JSON should include the following fields:... entry for each column.
Ready for the future of customer
interaction ?
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