Market Penetration & Churn Reduction with Price Simulation & Steering
A key player in the Dutch energy market was losing market share due to the competitive price pressure and was struggling with the low conversion rate on acquisition deals.
Reduce customer churn and increase conversion success rate of new deals
To enable sales to negotiate better deals, the Price manager at SME division wanted to know
- How can pricing be customized based on different sales channels and automated online?
- How should renewal subscriptions be priced to avoid switching over to competition?
- How should acquisition deals be priced?
Price Recommendation Model with Price Simulation and Steering
To effectuate the new strategy for reducing customer churn and improving acquisition performance, with the least amount of penalty on margin, some advanced simulation and scenario analysis models were built on top of the existing dynamic pricing models (also based on real-time data from the Energy Exchange).
Pricing managers used this to run scenarios to assess the business impact of different points of the margin-conversion tradeoff curve and provide sales with real-time price recommendations and guidance on how to price each customer deal. This algorithm is built into the quotation system and online sales portal and can be steered by sales to meet the changing business needs.
- MRD Proprietary Pricing AutoML
- Markov Chain Monte Carlo Methods
- Reduced customer churn by 23%
- Increased deal win probability by 7%