Care of Agents and Store Reps
Are some of your agents and reps strong at customer retention, whereas others excel in maximizing up-sale opportunities? These profiling insights can help you understand pods of strength and key contributors for your customer service organization, improving online training, peer-to-peer interaction, manager role-playing and site visits.
The Care of Agents and Store Reps Model is a must for understanding, nurturing and growing your valuable agent base!
This model is designed to be used in any call center and for industries such as Telecom, Entertainment, Hospitality, Airlines, Retail, Banking, Health Insurance and more.
Full model price: $75,000
- $7,500 initial deposit
- $30,000 first payment (invoiced at data access)
- $37,500 final payment (invoiced at model delivery)
PRODUCT INFO
Use Case
Understanding the underlying factors of employee, store rep or call center agent performance. Offer trainings, adjust compensation and rewards, location benefits, and office freebies.
AI/ML Modeling
A range of algorithms will be tested for the best AUC/outcome like XGBoost/GBM, Neural Network, SVM, ANOVA, KNN, K-Means, etc.
Model Delivery
One-time purchase:
- Propensity scores
- Agent ranking
- Leading model predictors
- Model performance
- Insight session
On-going monthly service additionally includes:
- Tracking leading predictors
- Model monitoring
- Seemless model refresh with market trend changes
- Strategy session every 3 months of service
- 10% discount on full model price
DELIVERY AND PAYMENT
We will contact you within 2 business days of your deposit to set the engagement date and provide instructions for the required data set.
The first model payment is invoiced at the data access date. Model delivery usually occurs 3-4 weeks from the data access date. The final model payment is invoiced at the model delivery date.
REFUND POLICY
Deposit fully refundable before engagement date.
If we cannot detect a pattern for a stable model, the final model invoice will be waived and we will provide you with data assessments, findings, insights and further recommendations.