What is Predictive Analysis provided by Nathan Claire Africa
Customers are becoming more demanding and benchmark your responsiveness with that of global service providers. It has therefore become imperative that you discover and respond to your customers’ and markets’ needs faster than competition by applying the most cost-effective technology solutions available to you.
By applying machine learning techniques to your current and historical data, our team of data scientists enable your decision-makers to predict the future, profile your customers and other 3rd parties to anticipate responses, mitigate risk, accelerate agility and increase business profitability by making the right decisions every time.
The capabilities that we deliver include:
- Industrialize machine learning and score card development best practices across your organization without requiring strong mathematical skills.
- Incorporate your best practices into automated workflows through scoring decisions
- Stay ahead of your competition through agility and improved risk assessment
- Design, build, validate and implement scoring models based on logistic regression, decision tree/decision rules, neural networks, and expert scorecards.
- Analyze portfolio data, visualize customer characteristics distributions and dependencies with 3D reports, associative strengths, and Kohonen maps
- Compare different scorecards and analyze their efficiency with ROC, Lorenz, Kolmogorov-Smirnov curves and many more popular model performance reports
- Improve enterprise-wide data quality in order to detect and block anomalies, such as outliers, wrong data types or missing values
- Implement automatic customer micro-segmentation and prequalify targets for better up-sell and cross-sell strategy execution
- Predict customer behaviour on both macro and micro levels
- Predict churn, retention and propensity to buy and reduce false-positives through both sensitivity and specificity scoring
- Decrease new customer acquisition costs while increasing the profitability of existing customers
- Automate strategies that drive customer engagement and loyalty
- Implement risk-based or opportunity-based pricing depending on each customers’ profile and behaviour