Our client was the deregulated subsidiary of a major US electric utility that was facing full deregulation in their home service territory and would now be forced to identify, attract, and retain customers in a competitive market. They needed to figure out how to price its services to maximize profits in the deregulated market, the appropriate trade-off between share and price, and how pricing strategy should vary by customer segment.
They also needed to know how they should react to competitor pricing strategy and how their strategy should be adapted as the market evolved.
Our objective was to develop optimal prices by customer segment given today’s market conditions and develop an ongoing process and set of tools through which the client could evaluate and respond to market changes as the deregulated utility industry matured.
We built a model that used customer survey data already compiled by the client to predict share at given price levels. This model helped us to:
- Derive customer elasticity by customer group from survey data
- Use elasticity and usage variation to construct customer segments with widely varying profitability and price trade-off characteristics
- Predict share change for both client and competitive price changes
We then built a model of our client’s internal fixed and variable costs by customer segment and forecasted likely changes over time. This model was sensitive to changes in share that altered our economies of scale and allowed for scenario gaming – alternate strategies, wholesale power prices, etc. We then modeled the competition’s fixed and variable costs in a similar manner.
Using a dynamic optimization model to determine the optimum price by customer segment over time we were able to determine price by segment and target share, looking to maximize total profit, not price or share. This model gave the client the ability to restate results should assumptions, competitors, or customer behavior change.
We then created a process for sales managers to use the model on a daily basis in making marketing program decisions and for the marketing strategy group to use the model on an ongoing basis to answer higher level questions (for example, market entry, customer targeting, partnership deals).
We developed optimal prices for the current conditions which the client implemented.
Then we transitioned two versions of our models to the client for use in ongoing pricing strategy, one to evaluate individual pricing plans and deals to evaluate a particular partnership deals. and a more versatile version to evaluate the appropriate strategy in new markets or the appropriate reaction to market changes such as wholesale power price changes. The first model is used by sales people in the field while the second model is used by the central strategy team to make decisions at the overall business levels. These models have allowed our work to bring continued benefit to our client.