Customer Stories
Real-time agility with centralised and automated data intelligence
How TransPennine Express unlocked a complete picture of passenger sentiment and saved 260 hours annually with Orlo.
TransPennine Express runs regional and intercity rail services across northern England and Scotland, connecting major cities across the UK. They are on a mission to deliver a more reliable, punctual and dependable service across the towns and cities that they connect.
The challenge
Managing a high volume of daily customer interactions across multiple digital brands, social media platforms, and WhatsApp, TransPennine Express faced a critical barrier: a lack of centralised, deep-dive visibility into both passenger sentiment and operational performance.
The social media team needed to get past surface-level data and wanted a reporting solution that would uncover the actual context and sentiment behind daily passenger interactions. Without the ability to monitor themes in engagement across all channels, it was difficult for TransPennine Express to spot emerging trends, catch sudden peaks in message volumes, or isolate high-priority topics like accessibility. Crucially, the team needed to gauge whether passengers were sharing positive or negative experiences so they could easily identify issues and immediately provide support for customers in need. The desire was to become more proactive with their communications rather than being reactive, following a spike in inbound customer contact.
To achieve a complete picture of customer engagement, TransPennine Express needed to bridge the gap between high-level insights and traditional customer metrics.
The solution
TransPennine Express sought the help of Orlo’s Value Delivery Team to help them implement this dual-reporting approach that could seamlessly balance needs: an insights-driven view to track emerging themes across all messages, alongside a custom analytics view for each service channel to monitor operational performance like response times and peak engagement hours. By gaining this comprehensive visibility, the team were not only able to understand what passengers were talking about in real-time, but also optimise how effectively they were responding to them.
Orlo’s Value Delivery Team were able to work with TransPennine Express to build a tailored reporting system tailored for all of TransPennine Express’ digital brands. They were able to shift TransPennine Express away from manual data collection and fragmented native platforms, so they could establish a single source of truth across all digital channels, including WhatsApp. The solution delivered distinct, purpose-built reports designed to provide complete visibility into inbound demand and agent efficiency.
The first phase of this strategy focused on establishing an Inbox weekly overview using Orlo Insights. This equipped TransPennine Express with a weekly, data-driven breakdown of all inbound messages segmented by key topics. Utilising the advanced theme detection tool within Insights, they are now able to monitor daily channel volumes, view overall positive/negative sentiment trends, and drill down into customer emotion analysis for high-priority areas like accessibility, service disruptions, and timetable changes.
The second stage of this process looked to balance these public perceptions with internal performance data. The Orlo team put in place the ‘Inbox Behaviour Insights Report’ using the platform’s Custom Analytics tool. Focusing heavily on contact behaviour and team operational output, this report provides deep granular data segmented entirely by brand, including Transpennine Express, Hull, and Lumo.
Through custom analytics, senior leadership can now easily view peak engagement times in response heatmaps, evaluate agent efficiency metrics, and track average response times across individual service channels.
They required a dual-reporting approach that could easily balance two distinct needs. TransPennine Express used Orlo Insights to gather data to provide an actionable overview of inbound messages across their social media and WhatsApp channels on a weekly basis. This weekly Inbox overview focused on providing a breakdown of key topics mentioned across all Inbox messages. Key metrics which Orlo Insights was able to provide them with included: channel volume per day, overall positive/negative themes, as well as trends and emotions for high-priority topics such as accessibility, disruptions and timetable changes.
The results
By automating this approach, TransPennine Express have successfully replaced surface-level metrics with data storytelling, giving them the tools to not only see what passengers are talking about in real time, but to actively make team responses more efficient. The implementation has completely transformed TransPennine Express’ digital customer service strategy, shifting their operations from reactive monitoring to proactive, data-driven engagement.
One of the most immediate benefits was reclaiming 260 hours annually. By eliminating the slow process of manually collating customer service data from multiple native platforms, reports are now generated at the click of a button, successfully redirecting valuable hours back into proactive customer care and strategic planning.
In addition, TransPennine Express now possess an instant gauge of passenger sentiment, serving as a critical line of defence for brand reputation. Rather than relying on guesswork, customer tracking widgets within the Orlo Platform provide an immediate view of customer emotions and trust. Moving beyond just raw volume data, the team can now uncover the why behind customer behaviours.
This level of operational visibility has allowed TransPennine Express to optimise staff schedules and resource allocation around each digital channel’s busiest operational hours. Senior leaders within the organisation can now consistently monitor staff output and track response times across all digital channels, driving continuous improvement in the overall passenger experience and ensuring support is always actioned exactly when and where it is most needed.
Outcome
260
hours saved
Outcome
7-minute
average response rate
Outcome
62%
of responses within 0-5 minutes
Outcome
13-minute
reduction in response rate quarter on quarter
Engagement
18.1k
inbound messages dealt with over a 30-day period
