By Maryam Miri, Rogers Communications Inc; Kevin Esdale, Rogers Communications Inc
Applying a proactive communication approach with the focus of customers with technical issues is an effective business strategy and a proven method that enhances both customer satisfaction as well as brand reputation. In a proactive program, the organizations initiate communication with customers and by keeping customers informed of feasible technical solutions, they stay ahead of possible complaints. Leveraging data driven approaches in a proactive communication program can significantly elevate the success rate. By utilizing data analytics tools, different insights, patterns, and correlations can be extracted. This helps in identifying the underlying issues and their general causations and hence, a more goal-oriented communication effort. In this paper, we describe the implementation of an end-to-end solution that by leveraging the analysis on millions of recorded data points, improves the wireless fidelity (WiFi) experience of users. In other words, by identifying and addressing the underlying in-home network issues that cause video quality degradations, we offer solutions to enhance customers' experience. To achieve this goal, we analyzed reported data from various sources such as set-top boxes (STBs), gateways (GWs), point of deliveries (PODs), and user feedback to identify patterns or trends that indicate issues affecting video quality. Then, by correlating the video quality impairments to the WiFi telemetries such as throughput, response time, and latency we isolate the WiFi degradation root causes such as poor received signal strength index (RSSI), low signal to noise ratio (SNR), and high band utilizations. Finally, by defining the root causes’ thresholds and developing a decision tree, we confidently propose educated solutions based on the root causes. By proactively reaching out to more than 5000 customers so far and employing the solutions, the results illustrate a notable improvement in the video quality. The observations of different cohorts depict that the pre-post video quality comparisons sustained greater than 70% improvement post implementations.