The challenge
As a global communication and technology leader, TELUS Communications faced increasing complexity in managing its wireless network across Canada’s vast and varied geography. Traditional methods of measuring customer experience (CX), such as post-call surveys or manual engineer assessments, were no longer sufficient. The sheer volume and complexity of data made it difficult to accurately capture customer perception or act quickly on emerging issues.
To maintain their position as a market leader, TELUS needed a more sophisticated, proactive approach to network optimization that could cut through the data complexity and directly translate into stronger customer experiences.
The TELUS Digital solution
In collaboration with TELUS, our team of experts developed the Customer Network Experience Score (CNES), an AI-powered framework designed to transform how networks are optimized.
CNES processes terabytes of network data and combines it with customer feedback and usage patterns to create a holistic view of network performance. Advanced machine learning models analyze hundreds of features to generate near real-time insights into both technical performance and customer perception. This includes analyzing KPIs across applications like voice calls, video conferencing, gaming, streaming and browsing, as well as contextual factors such as location, time of day and demographics.
Once trained, the model was scaled to run continuously, generating hourly predictions for every wireless customer. This gave TELUS a proactive system that could surface issues as they emerged, rather than relying solely on reactive surveys or manual troubleshooting.
With confidence scores ranging from 85-95%, CNES not only predicts customer perception, but also explains why performance issues occur. Engineers can trace problems to their underlying causes, such as congestion, latency or coverage gaps, and then prioritize fixes with the greatest technical and customer impact. The model also deepens engineers’ understanding of traditional network KPIs and how those metrics influence user perception.
The results
By correlating customer feedback with network KPIs, CNES enabled TELUS to predict user responses with high confidence and address issues proactively rather than reactively. This shift delivered measurable improvements across technical performance, customer experience and business outcomes.
Enhanced customer experience
Because CNES generates near real-time predictions, engineers could resolve issues before customers reported them. This proactive management improved overall service reliability and reduced the likelihood of frustration caused by outages, latency or slow speeds.
Tangible business impact
By directly connecting network optimization to customer outcomes, CNES enabled TELUS to make smarter investment decisions, reduce churn risk and improve service reliability at scale. The model also proved to be a strong predictor of churn, with customers holding low scores being 34% more likely to leave. These insights empowered targeted outreach and retention strategies that improved customer loyalty and strengthened brand sentiment.
Additionally, by aligning network optimization with customer perception, TELUS gained a unified view that connected network engineering with sales and marketing teams across the business — ensuring everyone worked from the same customer-centric perspective.
