High Opportunity Customer Growth Model
Looking to identify which of your lower profitability customers have the potential to become your next high-value customers? This model pinpoints the most likely candidates, helping you focus your efforts where they will have the greatest impact.
To be utilized in a range of industries like Telecom, Streaming Media Services, Entertainment, Hospitality, Airlines, Retail, Banking, Health Insurance and more.
Full model price: $55,000
- $5,500 initial deposit
- $22,000 first payment (invoiced at data access)
- $27,500 final payment (invoiced at model delivery)
PRODUCT INFO
Use Case
Utilize this model to identify customers with the highest potential to increase their purchases and boost your revenue and profitability in the foreseeable future. Perfect for crafting targeted, personalized offers that drive profitability and service revenue growth.
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.
LLMs and NLP techniques may also be used to enhance model performance.
Model Delivery
One-time purchase:
- Propensity scores
- Customer 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.