Case Study
Our success stories with different brands demonstrate the transformative power of data and AI in various industries
Adding Value Using Data Science
About the Client
The client is a renowned luxury automobile manufacturer with a global presence, known for its high-performance vehicles and exceptional customer service. The company offers a wide range of premium cars and comprehensive after-sales services to maintain customer satisfaction and loyalty.
Understanding the Challenge
Implementation by DataCouch
- Data Collection and Preprocessing
- Gathered data from multiple tables, including customer information, car details, service repair parts, and service history.
- Conducted rigorous preprocessing to ensure data accuracy, consistency, and integration across different sources.
- Exploratory Data Analysis (EDA)
- Applied EDA techniques to uncover patterns, trends, and correlations within the data.
- Provided insights into customer behavior, service preferences, and common service issues.
- Model Development
- Decline Services Prediction: Developed machine learning models to predict the likelihood of customers declining recommended services using historical service data, customer demographics, and past interactions.
- Next Best Service Recommendation: Created algorithms to recommend the next best service for each customer based on their car’s service history, usage patterns, and predictive maintenance needs.
- Likelihood to Service: Built predictive models to estimate the probability of a customer scheduling a service appointment within a specific timeframe, considering past service behavior, car usage, and seasonal trends.
- Next Best Service Offer: Generated personalized service offers using machine learning models analyzing customer preferences, purchase history, and engagement metrics.
- Parts Replacement Time Optimization: Developed models to predict the optimal time for parts replacement based on usage data, wear and tear patterns, and historical replacement cycles.
- Integration and Deployment
- Integrated predictive models and insights into the client’s CRM and service management systems.
- Created a real-time dashboard to visualize key metrics and provide actionable insights to service managers and customer service representatives.
- Set up automated alerts and recommendations to ensure timely and personalized service offers.
