-VP of Technical Operations
Servicing customers in over 40 states, this company is one of the largest cable and internet service providers in the United States. This ISP holds customer satisfaction as a top priority, as millions of customers across the country rely on their entertainment and communication services.
The operations team at this ISP was 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 a simple notification that the customer’s On Demand queue is 80% full to an error code signifying they were unable to purchase a PPV show), users, and geographical areas made it impossible to try to manually baseline the data. The team was tasked with putting thresholds on the data and quickly saw it wasn’t possible. They were bombarded with tens of thousands of alerts each day and 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 on demand, 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.
Since 2013 the operations team at the ISP has been using Prelert’s Anomaly Detective® 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 Anomaly Detective: “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.”
Anomaly Detective helped the team at the ISP reduce the noise of their status code alerts and prioritize and rank problems by severity, impact, and rarity so the teams knew where to focus their time. It even identified rare events and status codes that the support team didn’t even know existed.
The software allowed them to see: