Case Study: How a Regional Solar Installer Cut Cost Per Lead 65% and Broke Into AI Overviews — OnyxRank
**Industry:** Residential Solar Installation (3-state service area)
**Plan:** [OnyxRank](https://onyxrank.com) Growth
**Timeline:** 6 months
**Result:** SEO audit score improved from **22 → 91**; organic sessions up **367%**; blended cost per lead down **65%**; qualified quote requests up from 18/mo to 61/mo
The Challenge
A mid-size residential solar installer — roughly 40 employees, three crews, licensed and NABCEP-certified across three neighboring states — had a good reputation on the ground and a bad one in Google's eyes. Referrals and paid search kept the pipeline alive, but paid cost-per-click for solar keywords had climbed past $18, and blended cost per lead was sitting at **$148**. Margins on a $22K average install couldn't absorb that forever.
The root problem wasn't effort — the company had a blog, a handful of service-area pages, and a marketing person posting occasionally. The problem was structure. Three things were working against them:
1. **They were invisible next to marketplaces.** Searches like "solar installer [city]" and "how much does solar cost in [state]" were dominated by lead-gen aggregators (EnergySage-style marketplaces) and national installers with ten times the content footprint. The company's own service-area pages were thin, near-duplicate copies of each other with a city name swapped in — exactly the kind of content Google's algorithms are built to suppress.
2. **Core Web Vitals were failing on mobile**, where most of their traffic originated. Hero images on service pages were 2-4MB uncompressed, there was no lazy loading, and Largest Contentful Paint averaged 5.8 seconds. Slow pages were losing rankings and losing visitors before the page even rendered.
3. **Zero presence in AI Overviews.** Top-of-funnel research queries — "is solar worth it in [state]," "solar tax credit explained," "net metering vs battery storage" — were exactly the kind of question searchers now get answered directly in AI Overviews before they ever click a link. The installer had no content built to be cited: no clear definitional answers, no FAQ schema, no cited statistics.
The Approach
[OnyxRank](https://onyxrank.com) started with a full technical and content audit, which came back at 22/100 — a site that was functional but structurally invisible.
**Technical fixes first.** Images were compressed and served in modern formats, lazy loading was implemented site-wide, and render-blocking scripts were deferred. LCP dropped from 5.8s to 1.9s on mobile within the first three weeks. LocalBusiness, Service, and FAQ schema were added across every service-area and location page so Google (and AI crawlers) could parse exactly what the business offered and where.
**Programmatic local pages, done right.** Instead of duplicate city pages, OnyxRank rebuilt the service-area template to pull in genuinely unique data per location: average peak sun hours, the specific utility's net metering policy, local permitting timelines, and state-specific incentive stacking (state credit + federal credit + utility rebate where applicable). Fourteen service-area pages went from interchangeable filler to pages that actually answered "what would this cost and how fast would it pay off, here, specifically."
**GEO-structured pillar content.** For the big informational queries driving AI Overview traffic, OnyxRank restructured content around direct, quotable answers up top — a two-sentence definitional answer followed by supporting detail, source citations for every statistic, and FAQ blocks marked up with schema. This is the format AI Overviews and chat assistants pull from; vague, marketing-toned intros get skipped.
**E-E-A-T signals.** Author bios were added for the NABCEP-certified electricians actually writing and reviewing the content, and a real project gallery went up — permitted installs, before/after shots, and homeowner-reported production numbers, all tied to specific service-area pages.
**Off-site.** Local news mentions, a renewable energy directory placement, and two HOA/community publication features built relevant local authority without resorting to generic directory spam.
The Results
Over six months:
- **SEO audit score: 22 → 91**
- **Organic sessions: ~2,100/mo → ~9,800/mo** (+367%)
- **Page-1 rankings for local install keywords: 2 pages → 14 pages** (one per service area)
- **AI Overview citations: 0 → 11 target queries**, including "solar tax credit explained" and "net metering vs battery storage"
- **Qualified quote requests: 18/mo → 61/mo**
- **Blended cost per lead: $148 → $52** (-65%), as organic began carrying volume paid search had been shouldering alone
- **Mobile LCP: 5.8s → 1.9s**
The installer didn't cut its paid budget — it redirected it toward the highest-intent bottom-funnel terms, while organic took over the research-stage traffic that used to leak to marketplaces and never come back.
Key Takeaways
- **Duplicate local pages are worse than no local pages.** Templated city pages with swapped names get filtered by Google's algorithms. Real, location-specific data (utility rates, incentives, sun hours) is what earns rankings — and what a searcher actually needs.
- **Core Web Vitals aren't a technicality — they're a rankings and conversion lever.** A 3-second LCP improvement compounds: better rankings, lower bounce, more form completions.
- **AI Overviews reward answerable content, not marketing copy.** If your top-of-funnel content doesn't state a direct answer in the first two sentences with a cited source, it won't get pulled into AI-generated answers — and that's a growing share of research-stage search traffic.
- **High-ticket, considered purchases benefit most from organic economics.** When your paid CPL is already near $150, every point of organic share directly improves margin — this installer didn't grow revenue by spending more, it grew revenue by spending smarter.
Want Results Like These?
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