Dataiku Case Studies Coyote: From Churn Analysis to Predictive Safety

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	Coyote: From Churn Analysis to Predictive Safety Dataiku

Coyote: From Churn Analysis to Predictive Safety

Dataiku

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Industries	Automotive Telecommunications
Applicable Functions	Logistics & Transportation Sales & Marketing
Use Cases	Predictive Maintenance Traffic Monitoring Vehicle Telematics
Services	Data Science Services System Integration
Challenge	Coyote, a European leader in real-time road information, uses IoT-based devices and mobile applications to warn drivers of traffic hazards and conditions. The company collects extensive data on the different uses of its community, such as mileage, time spent on the road, or the number of alerts issued by the community members. Initially, Coyote started with predictive analytics for improving their customer retention. However, they wanted to leverage the value of their vast data sources and implement a data-driven strategy at the heart of their core products and services. They aimed to improve road safety using IoT devices. Read More
About Customer	Coyote is the European leader in real-time road information. The company uses IoT-based devices and mobile applications that enable their users to warn other drivers of traffic hazards and conditions that are detected while driving. Through its connected devices, Coyote collects extensive data on the different uses of its community, such as mileage, time spent on the road, or the number of alerts issued by the community members. The company aims to improve road safety using IoT devices. Read More
Solution	Coyote developed a project using Dataiku to leverage vast amounts of IoT-derived data to identify steep, potentially dangerous turns on car roads and develop a dynamic recommended speed limit model to prevent road accidents. The machine learning model facilitated the detection of speed limit anomalies and enabled Coyote to estimate the global quality and reliability of the displayed speed limit. The project involved identifying all S-curves in France and calculating their angle, developing a dynamic recommended speed limit model based on this data, building and releasing a database of dangerous road curves, and monitoring and service optimization. Dataiku provided the end-to-end solution for connecting to data, building the dynamic speed limit model, feature engineering, deployment of database, data visualization and visual AutoML, and model monitoring and optimization. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Industries

Automotive

Telecommunications

Applicable Functions

Logistics & Transportation

Sales & Marketing

Use Cases

Predictive Maintenance

Traffic Monitoring

Vehicle Telematics

Services

Data Science Services

System Integration

Challenge

Coyote, a European leader in real-time road information, uses IoT-based devices and mobile applications to warn drivers of traffic hazards and conditions. The company collects extensive data on the different uses of its community, such as mileage, time spent on the road, or the number of alerts issued by the community members. Initially, Coyote started with predictive analytics for improving their customer retention. However, they wanted to leverage the value of their vast data sources and implement a data-driven strategy at the heart of their core products and services. They aimed to improve road safety using IoT devices.

About Customer

Coyote is the European leader in real-time road information. The company uses IoT-based devices and mobile applications that enable their users to warn other drivers of traffic hazards and conditions that are detected while driving. Through its connected devices, Coyote collects extensive data on the different uses of its community, such as mileage, time spent on the road, or the number of alerts issued by the community members. The company aims to improve road safety using IoT devices.

Solution

Coyote developed a project using Dataiku to leverage vast amounts of IoT-derived data to identify steep, potentially dangerous turns on car roads and develop a dynamic recommended speed limit model to prevent road accidents. The machine learning model facilitated the detection of speed limit anomalies and enabled Coyote to estimate the global quality and reliability of the displayed speed limit. The project involved identifying all S-curves in France and calculating their angle, developing a dynamic recommended speed limit model based on this data, building and releasing a database of dangerous road curves, and monitoring and service optimization. Dataiku provided the end-to-end solution for connecting to data, building the dynamic speed limit model, feature engineering, deployment of database, data visualization and visual AutoML, and model monitoring and optimization.

Impact #1	Coyote was able to develop a dynamic recommended speed limit model to prevent road accidents.
Impact #2	The machine learning model facilitated the detection of speed limit anomalies and enabled Coyote to estimate the global quality and reliability of the displayed speed limit.
Impact #3	Coyote was able to build and release a database of dangerous road curves.

Impact #1

Coyote was able to develop a dynamic recommended speed limit model to prevent road accidents.

Impact #2

The machine learning model facilitated the detection of speed limit anomalies and enabled Coyote to estimate the global quality and reliability of the displayed speed limit.

Impact #3

Coyote was able to build and release a database of dangerous road curves.

Benefit #1	Coyote's marketing campaigns saw an 11% increase in efficiency thanks to increased knowledge of the actual uses of the service.
Benefit #2	Coyote was able to successfully deploy and continuously optimize their predictive maintenance products and services for delivering quality driver assistance and improving road safety.

Benefit #1

Coyote's marketing campaigns saw an 11% increase in efficiency thanks to increased knowledge of the actual uses of the service.

Benefit #2

Coyote was able to successfully deploy and continuously optimize their predictive maintenance products and services for delivering quality driver assistance and improving road safety.

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Overview

Coyote: From Churn Analysis to Predictive Safety

Operational Impact

Quantitative Benefit