Price Orientation Framework for Energy Pricing Decisions

Problem & Context

An energy utility needed a more data-driven way to set prices for residential default-supply electricity tariffs while balancing customer stability and revenue potential. The business wanted to understand which price position versus the market would keep the customer base at an economically attractive long-term level. This mattered because portfolio price drift, passive churn, active switching behavior, and exceptional market phases made pricing decisions difficult to judge using intuition alone.

Approach & Solution

The project developed a pricing guidance framework built around observed customer behavior, portfolio dynamics, and stakeholder interpretation. Using historical tariff, customer stock, inflow, and churn data, the team assessed how switching behavior changed with different price positions versus the market. This created a practical decision view in which market-relative pricing became the key steering variable. The solution combined customer inflow, passive churn, and price-driven switching into clear guidance for identifying a commercially attractive price corridor and an economically sound target position versus the market.

Results & Impact

The initiative gave the client a more transparent and analytically grounded basis for residential energy pricing decisions. It translated observed churn behavior and portfolio dynamics into practical guidance for setting tariff prices relative to the market, clarified when prices were likely too low, too high, or in a stable target range, and created a scalable foundation for recalibrated pricing guidance as market conditions change.

5

core assumptions used to define structured pricing guidance

1

market-relative price elasticity model per tariff

50%

faster response to market price changes

Your Contact

Dr. Steffen Illig

Partner and Expert for Data Analytics

+49 176 579 82284

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