Determining the value of our QR scanning infrastructure
About this project:
The project aimed to provide clear insights into the value of the QR system, enabling data-driven decisions about its wider rollout and optimisation.
"I have found the Nurture programme a huge benefit to our business and am actively seeking future
opportunities for further projects!"
John Burton - Head of Data Analytics & Insights
Stagecoach
"Through this opportunity, I worked as a Data Analytics Intern with Stagecoach on a live project, collaborating with the fantastic DAI team led by John Burton and Anthony Blore. My work focused on QR data analysis, passenger trend analysis, and forecasting. I am excited to share that I have officially joined Stagecoach as a full-time Data Analyst"
Giri Madhumilton - Nurture Graduate & Data Analyst
Stagecoach
- Reach out to Marie to find out how Nurture can help your business to achieve goals
Executive Summary
Predictive Model | Customer Satisfaction
Objective:
Stagecoach aimed to understand the true value of its investment in QR code scanners - technology designed to simplify ticketing and enhance the passenger experience. The project’s objective was to measure the impact of QR scanners on uptake, functionality, and customer satisfaction, providing clear insights and evidence to inform future decisions and share with key stakeholders.
Solution:
Analysed passenger data from regions using QR scanners, comparing usage between different customer groups to identify trends, technical issues, and seasonal patterns. This analysis established a clear baseline for scanner performance and passenger behaviour, which was then visualised in a Tableau dashboard - giving stakeholders a powerful tool to track usage, spot issues early, and make informed decisions about future investment and rollout.
Results:
- Improved service provided for the customers
- Using data to target resource in an informed way
- Encourages innovation - colleagues across Onward can see what is possible with robust data!
Challenge
Solution
Outcome
As a business, we have committed to utilising the most modern technology to facilitate a better customer experience. In light of this, we have invested in QR code scanners to allow passengers to directly scan onboard the bus rather than having to purchase at the point of embarking.
The challenge around this is determining the value to both passengers and us as a business compared to more traditional ways for people to buy & use tickets. We are rolling out QR scanners across the country after a series of pilot schemes in different regions, but to date we have not been able to fully quantify the ROI of the machines given the multi-channel approach we have to take to allow everyone to get on our buses seamlessly.
The project aimed to produce information on how valuable the QR scanners have been in uptake, functionality and passenger experience ready for sharing with a select group of stakeholders.
The challenge was to determine the value for passengers and the business
Working on this project, the Nurture student set out to forecast passenger numbers in regions where QR scanners had been introduced - comparing data between users and non-users. This approach highlighted potential technical issues, regional variations, and seasonal usage patterns, while also providing early indicators of how the new system influenced customer loyalty and satisfaction.
By analysing this data, the project established a clear baseline of scanner usage, identified the most popular routes, and pinpointed times when technical problems were most likely to occur. These insights were visualised in a dynamic
Tableau dashboard, enabling stakeholders to monitor performance, explore trends, and make informed decisions about future investments and maintenance.
Using the data to forecast passenger numbers
The project delivered a stakeholder dashboard that provided clear, accessible insights into how the QR scanning infrastructure was being used across regions. This visibility allowed teams to monitor performance, track adoption rates, and identify patterns of usage over time.
Armed with this data, the business gained the ability to make informed decisions about where and how to invest in future infrastructure rollouts. Leaders could confidently assess the success of pilot regions, prioritise areas for expansion, and ensure that resources were allocated where they would deliver the greatest value.
Finally, the analysis enabled
early identification of technical or functional issues within the infrastructure. This proactive insight meant that interventions could be made quickly, minimising disruption to passengers and maintaining a high standard of service across all routes.
