TürkiyeRetail and e-commerce2024 – ongoingOtocash.com
Machine learning for customer segmentation and seller targeting
Otocash.com increased customer conversion rates by 20% with machine learning
Problem
Otocash.com struggled to distinguish people ready to sell their cars from visitors seeking only a valuation. Staff manually checked potential sellers.
Approach
Otocash.com worked with Nephos to build a customer-segmentation model using Azure Machine Learning and internal data. The model predicted transaction likelihood and helped target marketing spending.
Results
Takeaway
Identifying likely sellers supported both higher conversion and less manual verification by customer service staff.
Categories
- Size
- Small business
- Industry
- Retail and e-commerce
- Business function
- Marketing and salesCustomer service
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and ML
- Adoption
- Partner co-development
- Evidence
- Vendor case study
Sources
Source summaries
Microsoft reported that Otocash.com used machine learning to identify likely sellers. A company manager reported 20% higher customer conversion rates; the story also reported a 94% reduction in customer service workload.
Full details are in the original sources.
