Driving Scalable Growth through
Data-Led Performance Marketing
How a US energy provider tripled daily enrollments and cut acquisition costs by 55% in 14 months of targeted, transparent performance marketing.
A scale problem in a trust-sensitive market
Awareness wasn't the issue — converting it into consistent, cost-efficient enrollments was.
Our client is a deregulated energy provider operating across New York and Pennsylvania — two of the most competitive retail energy markets in the United States. Their offering was genuinely strong: flexible plans, transparent pricing, and customer-centric rate protection that delivered real savings versus local utilities.
Yet when the engagement began, digital acquisition had plateaued at just three enrollments per day — largely powered by organic traffic and legacy channels that had hit their ceiling. The brand had the product. What it lacked was a scalable system to communicate that value to the right audiences at the right moment.
The energy market adds a further layer of complexity. Consumer scepticism runs high — decades of misleading "low rate" promises have made prospective customers guarded. Any marketing approach had to balance performance efficiency with credibility. Volume without trust generates enrollments that churn; trust without reach leaves growth on the table.
The mandate was clear: build a data-driven acquisition engine capable of tripling daily enrollments — without sacrificing efficiency or eroding the brand's reputation for transparency.
From plateau to proven growth engine
Across every key metric, the campaign delivered measurable, compounding improvement over 14 months.
Transparency became a performance lever — proving that data-backed pricing can drive acquisition at scale, even in the most sceptical consumer markets.
per Day
Enrollment
CTR
Rate
Drop-offs
A three-phase acquisition system
Growth wasn't accidental. It followed a disciplined, phased strategy — each stage building on the last — with Google to convert, Meta to educate, and the website to seal the deal.
Phase 1 established the data foundation and surfaced critical funnel gaps. Average enrollments held at 3/day — but the groundwork for compounding scale was firmly laid.
Smart bidding, improved landing pages, and mobile UX fixes compounded rapidly. By end of Phase 2, the client was averaging 8–10 enrollments per day — a 233% increase from baseline.
The P2C framework turned transparency into a performance lever — proving that substantiated pricing claims consistently outperform vague promises. Enrollments scaled to a steady 11 per day, a 266% increase from where the campaign began.
Sales per day — progression from Phase 1 (Jul 2024) through Phase 3 (Sep 2025)
Before and after, by the numbers
A direct comparison of key performance metrics from campaign start to finish.
| Average Sales per Day | 3 / day |
| Cost per Enrollment (CPA) | $66.6 |
| Average CTR (Google + Meta) | 3.20% |
| Enrollment Rate | 2.30% |
| Funnel Drop-offs (ZIP Step) | 60% |
| Primary Acquisition Channel | Organic + Legacy |
| Average Sales per Day | 11 / day |
| Cost per Enrollment (CPA) | $29.8 |
| Average CTR (Google + Meta) | 7.80% |
| Enrollment Rate | 6.50% |
| Funnel Drop-offs (ZIP Step) | <20% |
| Primary Acquisition Channel | Google · Meta · P2C · Retargeting |
The trajectory in charts
Visual proof of how each phase contributed to compounding enrollment growth over 14 months.
Transparency at scale
What began as a small-scale digital test grew into a consistent, data-driven acquisition engine. By aligning transparency, trust, and technology, the campaign achieved measurable business growth while reinforcing credibility in one of the most sceptical consumer markets in the United States. The Price-to-Compare framework didn't just improve CTR — it changed how audiences evaluated the brand, turning a complex decision into a clear, data-backed one. From 3 to 11 enrollments per day, this engagement stands as proof that clear communication and transparent pricing can scale profitably — even in traditionally cautious industries.
Frequently asked questions
Common questions about performance marketing for energy and utilities businesses.
Initial directional signals appear within the first 4–8 weeks. Meaningful CPA improvements begin around month 3, once Smart Bidding has sufficient conversion data to optimise. In this engagement, consistent daily enrollment growth became visible from month 5 onwards — with the most significant gains in Phases 2 and 3 as bidding algorithms matured and UX improvements compounded.
P2C shows prospective customers a real-time, side-by-side comparison of the client's live energy rate versus the local utility's 12-month average — down to the pincode level. Data is refreshed every 14 days for accuracy. Rather than claiming "lower rates," P2C proves it with live data, dramatically improving CTR and enrollment rates by making the value proposition immediately credible and verifiable.
Ad performance and landing page performance are inseparable. A single ZIP code input field caused 60% of users to abandon the enrollment form in this campaign — no amount of ad spend could fix that friction. Resolving UX issues meant every acquisition dollar reached its destination. Incremental UX fixes — form simplification, progress indicators, mobile redesign — drove a cumulative 12–18% lift in completion rates.
The two platforms serve distinct roles. Google captures existing demand — users actively searching for energy providers or comparing plans. Meta builds intent — educating audiences and building brand familiarity before they search. In practice, Google drives the majority of direct enrollments while Meta warms audiences and reduces downstream CPA on Google. Together they create a full-funnel system rather than competing for the same budget.
Energy plan decisions are high-consideration — most users research multiple providers before enrolling. Retargeting re-engages those high-intent visitors who didn't convert first time. In this campaign, retargeting accounted for 22% of total conversions and Display retargeting added a further 28% in incremental enrollments. Behaviour-based triggers and optimised frequency caps ensured relevance without ad fatigue.
Yes — deregulated markets like New York and Pennsylvania are well-suited to performance marketing precisely because consumers have a genuine choice. The key is pairing channel efficiency with message credibility. Generic "low rate" claims underperform; data-backed, transparent comparisons consistently outperform because they respect the consumer's intelligence and address their primary concern: are they actually paying less?
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