Tariff-Level Customer Base Forecasting and Scenario Simulation for Energy Sales Planning

Problem and Context

An energy utility needed a more reliable way to forecast its future customer base at tariff level so it could improve procurement planning, sales target setting, and pricing decisions. The challenge mattered because customer stock development depended on both active and passive churn, market-relative price positioning, and varying acquisition levels across segments. Additional complexity came from small tariff populations, tariff migrations, internal tariff switches, and the need to reflect crisis-related market effects without distorting a realistic planning baseline.

-18%

reduction in tariff-level customer stock forecast error

91.2%

accuracy in historical customer base change forecasting

-67%

reduction in manual effort to build and compare tariff scenarios

Approach and Solution

The project combined transparent baseline logic, advanced forecasting, and configurable simulation into a modular planning framework. Working closely with stakeholders, the team first built a stable churn view that separated passive and active churn and improved tariff-level forecasts across customer groups. Smaller tariff populations were grouped where needed to increase reliability, while business reviews were used to refine the main churn drivers and planning assumptions. The forecast outputs were then embedded into an Excel-based simulation that allowed business users to test tariff-level scenarios across price positions, acquisition volumes, time periods, and customer groups without further technical effort.

Results and Impact

The initiative gave the client a more transparent and scenario-driven basis for planning customer volumes, energy procurement, and sales targets at tariff-type level. It translated churn behavior, market-relative pricing, and acquisition assumptions into a configurable monthly simulation, improved forecast quality, and created a scalable framework for sensitivity analysis across products and market conditions. The solution also strengthened interpretability and made future scope extensions easier.

Tariff-Level Customer Base Forecasting and Scenario Simulation for Energy Sales Planning

Problem and Context

-18%

91.2%

-67%

Approach and Solution

Results and Impact

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Steffen Illig

Partner, Project Manager and Expert for Data Analytics

steffen.illig@5v-strategy.com