A retail energy provider learned which customer and product mixes were actually profitable.
In deregulated markets, a complex mix of products and contracts made it hard to tell which customers and deals paid off over time. We built the analytics to evaluate profitability by product, customer, and deal — and the churn behind it.
Challenge
Competing in deregulated markets meant offering a complex mix of products and contract options to attract, retain, and serve customers — which made it genuinely hard to tell which product and customer mixes were profitable on a long-term basis once you accounted for forecast demand, supply, and variance to actuals.
Approach
We built the analytics to evaluate profitability where it actually lives — by product, by customer, and at the deal level — alongside the churn behavior that erodes it, so pricing and retention decisions could be made on long-term profitability rather than headline volume.
Technology
A profitability and churn analytics layer over retail product, customer, and deal data, reconciling forecast demand and supply against actuals.
Outcome
The provider can see which product and customer mixes pay off over the life of the contract, and which churn away before they do — so acquisition and retention spend follows long-term margin instead of short-term volume.
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Explore the analytics
Synthetic data — a hands-on view of the kind of dashboard this engagement delivered.
Interval Usage Analytics
Interval usage across demographics to surface trends, anomalies, and outliers — synthetic data.