Ensuring Subscriber Retention and Loyalty

Technology Category

Analytics & Modeling - Predictive Analytics

Applicable Industries

Telecommunications

Applicable Functions

Sales & Marketing

Use Cases

Predictive Replenishment

Services

Data Science Services

The Challenge

Coyote, a French leader in real-time road information, was facing a challenge in retaining its customer base and enhancing its service quality. The company wanted to optimize its loyalty program to encourage customers to increase device use. To achieve this, Coyote needed a technical solution that would enable them to segment its customer base by user profile, qualify incoming data, and quantify device use through anonymous data analysis. The company understood that the more data it collected, the better its service would be. Therefore, improving retention rates was crucial to enhance the service quality and acquire more users.

About The Customer

Coyote is a French company that provides real-time road information. The company was established in 2005 and has grown to have 200 employees. In 2014, Coyote generated a turnover of over € 100 million and currently has 4.8 million users across Europe. The Coyote devices allow users to interconnect to the entire community in order to warn other drivers of the different traffic hazards and traffic conditions (traffic obstruction, accident, radar, etc.) detected during their rides.

The Solution

Coyote decided to use Dataiku's Data Science Studio (DSS) to build and implement a predictive behavioral analysis application to segment customers. The application automatically compiled and processed heterogeneous and completely anonymized data, including contractual data, customer declared data, and real-time device data. This data was then processed by a machine-learning algorithm to model user behavior. The model and its results were subsequently adjusted to optimize marketing campaigns. With this score, Coyote was able to segment its user base with very high accuracy, leading to significant optimization of marketing campaigns.

Operational Impact

Increase in the performance of outbound call campaigns by 11%
Adaptation of marketing campaigns due to increased knowledge of the actual uses of the service
Significant improvement in data management

Quantitative Benefit

Efficiency of outbound call campaigns increased by 11%
Significant improvement in data management leading to more effective marketing campaigns
Increased knowledge of actual service uses leading to more targeted marketing campaigns