Servicing customers in over 40 states, one of the largest cable and internet service providers (ISPs) in the United States holds customer satisfaction as a top priority, as millions of customers across the country rely on their entertainment and communication services.
Wrangling Thousands of Alerts a Day to a Meaningful Few Was Impossible
This ISP's operations team is in charge of monitoring the status codes of millions of cable set-top boxes across the country, but the sheer volume of possible status codes (ranging from simple notifications to error codes), users, and geographical areas made it impossible to manually baseline the data. The team was tasked with putting thresholds on the data but quickly realized that it wasn’t possible.
Bombarded by tens of thousands of alerts each day, they were struggling to identify and prioritize the alerts that represented issues which could impact a larger number of users and impact customer satisfaction. For example, if video On Demand failed in one geography, it would represent a potential huge loss in income both from customers unable to purchase shows or movies, as well as from disgruntled customers overwhelming the customer support hotline.
The bottom line: The ISP could not physically threshold their data in any realistic manner or sort through the clutter of status code alerts to identify alerts that represented real service issues.
Automatic Anomaly Detection Busts Through the Noise
Since 2013 this ISP's operations team has been using Prelert to better understand status codes and errors that have a wider impact on their user base, reducing the noise of these alerts to more accurately identify problems and improve customer satisfaction.
The ISP’s VP of Technical Operations was excited from their first trial of Prelert: “We knew that Prelert was on to something when we saw their ability to automatically plunk out the anomalies in our real-time data without any effort. But we were really excited by its ability to pull related anomalies out of multiple data types simultaneously.”
Prelert Reduces Noise and Identifies High-Impact Anomalies in Near Real-Time
Prelert helped this ISP's operations team significantly reduce the noise of their status code alerts and prioritize and rank problems by severity, impact, and rarity so the team knows where to focus their time.
Going a step further, Prelert even identified rare events and status codes that the support team didn’t know existed.
Prelert allowed them to see:
See what Prelert can do to proactively identify IT Operations issues and performance problems within your organization.