Web service real time prediction: Background
BVLab was approached by an offshore company that was struggling with contact center capacity planning. The company had a large contact center with multiple teams handling customer inquiries, but they were finding it difficult to accurately predict how many agents were needed to handle the volume of calls and messages that they received on a daily basis. This was resulting in long wait times for customers and overstaffing, which was costly for the company.
Difficulty in predicting agent requirements led to long wait times and costly overstaffing
Solution
The e-commerce company implemented the Shipping Fees Optimizer, and the results were immediate. The real-time data provided by the solution allowed them to adjust their pricing dynamically, resulting in increased profitability and customer satisfaction.
The solution was based on machine learning algorithms that analyzed historical data from the contact center, as well as real-time data from the company’s systems. The algorithms were able to identify patterns and trends in the data, and to make accurate predictions about future demand.
Machine Learning
Algorithms
Real-Time Data Analysis
Predictive Staffing
The web-service real-time prediction solution was integrated with the company’s contact center systems, allowing managers to access real-time data and insights about call volumes, agent availability, and predicted demand. This allowed them to make informed decisions about staffing levels, and to adjust staffing in real-time to meet changing demand.
Real-Time Insights Dashboard
Results
After implementing the web-service real-time prediction solution, the offshore cmpany saw significant improvements in their contact center operations. They were able to accurately predict demand and adjust staffing levels in real-time, resulting in shorter wait times for customers and reduced costs for the company.
Conclusion
Overall, the web-service real-time prediction solution developed by BVLab helped the offshore company to improve their contact center operations and achieve better business outcomes.
- Reduce costs: By optimizing staffing levels and reducing overstaffing.
- Improve customer satisfaction: By reducing wait times and improving the overall customer experience.
- Increase efficiency: By providing real-time insights into customer demand and agent availability.