Telecom quality of service
Improve the quality, increase the renewal rate, reduce the bad payers
Challenge
Telecom companies have a long history of using data. However they face a number of challenges currently affecting their profitability: poor customer service, lack of marketing innovation, slowing sales, and increasing collection services.
This telecom client wanted to reduce customer churn and eliminate bad payers.
To reduce client churn overall, it needed a better quality of service : The client also needed to know what motivates customers to call the hotline and to delay payments.
The challenge was to identify and detect key service variables that have high customer impact. To find and to correct bugs, identify early faulty devices, and set up Key Performance Indicators (KPI) related to the customer’s perception.
Solution
Machine Learning methods were implemented to identify and detect technical challenges that have high customer impact, to detect and correct bugs, weed out faulty devices, and suggest new KPIs.
Thankfully, the detection of bugs, challenges, as well as the implementation of very effective KPIs, the telecom client has registered a significant improvement in the quality of service: a large reduction in calls to the hotline (-15%), reduction in the number of developers working on bug detection (-25%), improvement of customer satisfaction rate (+10 points).
By setting up predictive maintenance processes for early detection of faulty equipment, the operator recorded a sharp reduction in the number of incidents, representing 5,000 devices per month.
That led to a subsequent reduction in the loss of subscribers, the number of outstanding payments, representing 30% of the overall measured outstanding problems.
Why Octopeek?
The Telecom industry needs to move from ad-hoc experimentation with AI to enable everybody within the organization to use it to improve both operational efficiency and deliver business value. Octopeek aims to be the platform that democratizes AI in the enterprise: it makes possible a dynamic creation and provisioning of full-fledged enterprise AI applications, customizable by business analysts.
