CASE STUDY
Pacific Power Finds 8,270 High-Propensity Candidates
Pairing income propensity with energy use surfaced customers conventional screening had missed
Pacific Power's Low-Income Discount program in Oregon had reached 69,190 participants, but enrollment had plateaued. Traditional screening methods, including self-attestation and census-block targeting, were no longer finding enough new candidates.
Using Bidgely's Analytics Workbench, Pacific Power identified non-participants with a high probability of earning below $70,000, then prioritized those in the top 20% of energy use. The analysis surfaced 8,270 high-propensity candidates. A single targeted touchpoint converted 2.3% of them into 187 new enrollments.
The snapshot covers the four-step targeting approach, examples of traditional and digital outreach, and how Pacific Power is extending the model to four-person households for its 2026 campaign.
Improve Program Performance With Precision Targeting
Identify customers most likely to participate so you can drive higher enrollment, lower cost per kWh, and stronger results.
Drive Measurable ROI From Existing Data Investments
Unlock new operational and program value from AMI and meter data utilities already own.
Deliver Measurable Impact Across the Utility Enterprise
Turn today’s data into tangible gains in efficiency, engagement, and system performance.
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