case studies
Predictive Analytics for E-commerce Optimization
Client: A Global Consumer Goods Corporation
What was our task?
Our client, a global corporation, wanted to optimise its e-commerce operations through predictive analytics to better understand customer behaviour and improve sales strategies.
For this assignment, we needed to implement a predictive analytics system that could provide actionable insights into customer preferences and buying patterns, optimising product recommendations and marketing activities.
What actions did we take?
- Conducted market and UX research to gather data on customer behavior.
- Utilized Python and SQL to build predictive models, leveraging a scalable cloud platform.
- Employed machine learning algorithms, including supervised and unsupervised learning, to analyze data.
- Integrated digital marketing tools for comprehensive data collection.
- Developed Power BI dashboards to visualize predictive analytics results and track key metrics.
What have we achieved?
- Achieved a 15% increase in e-commerce sales through targeted product recommendations.
- Improved customer satisfaction and engagement, as evidenced by a 10% increase in repeat purchases.
- Enhanced decision-making capabilities for marketing teams, leading to more effective campaigns.
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