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targeted vs. standard campaigns
with proprietary targeting
at significantly lower spend
direct list + lookalike layer
This client is an established residential and commercial garage door service provider serving a competitive local market. Their business runs entirely on inbound service calls — homeowners and property managers reaching out for installation, repair, spring replacement, and opener service.
Like many local service businesses, they had been running Meta ads for some time. They were generating calls — but at a cost that made scaling feel impossible. Something had to change.
Garage Door Services — residential & commercial
Local Service Market (Withheld)
Meta Advertising (Facebook & Instagram)
30-Day Controlled Campaign Test
$35–$90 per phone call using standard Meta targeting — unpredictable volume, high waste
Lower cost per qualified contact while maintaining or increasing call volume
The client came to us with four active Meta campaigns — all running simultaneously across their local market. While calls were coming in, the cost was difficult to justify. Depending on the campaign, they were paying anywhere from $35 to $90 for a single qualified phone call.
The core issue wasn’t the platform. Meta is a powerful tool. The issue was the audience data feeding it. Standard Meta targeting relies on passive behavioral signals — people who once engaged with home improvement content, liked a hardware store page, or scrolled past a home renovation video. That’s not the same as someone who is actively searching for a garage door company right now.
$35–$90 per call with no consistency across campaigns
Meta’s native targeting cast too wide a net
Reaching people with general interest, not active intent
High CPL made it hard to justify increasing budget
Our solution was to introduce a proprietary targeted data layer — a real-time list of consumers actively searching for garage door services in the client’s local market. Rather than relying on Meta’s passive interest signals, we fed the algorithm something far more valuable: verified purchase intent.
To ensure a rigorous, apples-to-apples comparison, we ran both campaign types simultaneously: standard campaigns continued without changes, while the targeted data campaigns launched alongside them in the same market, same platform, same 30-day window.
Identified consumers actively searching for garage door services in the client’s local market using our proprietary data pipeline — not demographic guesses, real intent signals.
Loaded the intent list as a Meta custom audience, then constructed a lookalike audience seeded from those same high-intent profiles — doubling the audience value from a single data source.
Standard campaigns ran unchanged while targeted campaigns ran in parallel. 30 days. Same market. Same platform. Clean data for a definitive comparison.
Meta Advertising (Facebook & Instagram)
Concurrent A/B: Standard vs. Targeted Data
Proprietary in-market consumer intent list — local garage door service searchers
Direct list targeting + Lookalike audience built from same data
Phone call (contact action) — inbound service calls
30 days — same window for both campaign types
Local service market — identical geographic targeting across all campaigns
We sourced a real-time list of local consumers actively searching for garage door services in the client’s market. This data identifies people at the moment of purchase intent — not casual browsers, not general home improvement fans.
The in-market data list served as a high-quality seed for Meta’s lookalike audience builder. The resulting audience reflected the profile of real, active buyers — extending reach while maintaining quality. One data source, two performing audiences.
Standard and targeted campaigns ran simultaneously in the same geographic market. This eliminated external variables and produced a clean, verifiable performance comparison — straight from Meta Ads Manager.
Real-time consumer intent data identifying active garage door service searchers in the client’s local market — the core targeting advantage that drove the CPL drop.
The in-market list was loaded directly into Meta as a custom audience, giving the ad algorithm a high-quality pool to serve — and measure — with precision.
Seeded from the in-market list to build a scaled audience of consumers who mirror the behavior and demographics of verified garage door buyers. Extends reach without sacrificing quality.
Campaigns ran across Meta’s full placement inventory, allowing the algorithm to optimize delivery to the highest-performing surfaces for inbound call generation.
Cost-per-phone-call was the primary success metric, measured directly in Meta Ads Manager as a contact action — providing a clean, apples-to-apples comparison across campaigns.
Standard and targeted campaigns ran simultaneously — same market, same platform, same time window — eliminating seasonal and external variables from the comparison.
All figures sourced directly from Meta Ads Manager. Standard and targeted campaigns ran concurrently in the same geographic market over the same 30-day period.
| Metric | Targeted Data Campaigns | Targeted Data Campaigns | Result |
|---|---|---|---|
| Cost Per Phone Call | $35 – $90 | $10 – $15 | ↓ Up to 72% lower |
| Contacts Per Campaign | Inconsistent / unqualified | 20 – 38 contacts | Higher quality & volume |
| Audience Source | Meta Interest Targeting | In-Market Intent List | Active vs. passive intent |
| Lookalike Layer | Not used | Yes — seeded from data list | 2× audience reach |
| Overall Efficiency | Baseline — high cost, high variance | Consistent, scalable CPL | Same budget, more calls |
| Standard Campaigns — No Data Targeting | Avg: ~$62.50/call | |
|---|---|---|
| Campaign | Spend | Cost/Call |
| Standard — Campaign A | — | $35 |
| Standard — Campaign B | — | $45 |
| Standard — Campaign C | — | $80 |
| Standard — Campaign D | — | $90 |
| Targeted Data Campaigns — In-Market + Lookalike | Avg: ~$11.54/call | |
|---|---|---|
| Campaign | Spend | Cost/Call |
| Targeted — Campaign 1 (25 contacts) | $237 | $9.48 |
| Targeted — Campaign 2 (20 contacts) | $203 | $10.15 |
| Targeted — Campaign 3 (38 contacts) | — | $10–15 |
Meta’s standard targeting reaches people who have shown general interest in home services. Our proprietary data reaches people who are actively searching for your specific service in your market right now. That distinction drives the entire CPL gap.
Most lookalike audiences are seeded from website visitors or broad email lists — audiences of mixed intent. Ours was seeded from verified in-market buyers. When the seed is right, the lookalike is right.
When Meta’s algorithm receives higher-quality engagement signals from a more qualified audience, delivery efficiency improves. The targeted data advantage doesn’t just hold — it gets stronger as campaigns run and optimize.
The 30-day test didn’t just produce better numbers — it validated a repeatable system. The client now has a proven, data-backed Meta advertising strategy that can be expanded with confidence. More budget doesn’t mean more wasted spend; it means more qualified phone calls at a predictable, manageable cost.
And because this targeted data approach is not specific to garage doors or any single market, the same methodology is available for any service-based business, in any market we cover.
Identified consumers actively searching for garage door services in the client’s local market using our proprietary data pipeline — not demographic guesses, real intent signals.
Loaded the intent list as a Meta custom audience, then constructed a lookalike audience seeded from those same high-intent profiles — doubling the audience value from a single data source.
Standard campaigns ran unchanged while targeted campaigns ran in parallel. 30 days. Same market. Same platform. Clean data for a definitive comparison.
average cost per phone call
average cost per phone call
recovered per 100 qualified phone calls at same volume
“We had been running Meta ads for a while but always felt like we were paying too much for each call. When the targeted data campaigns launched, the difference was immediate and obvious. Seeing $9 phone calls in the same dashboard where we were used to seeing $80 — that’s when we knew this was different. We’re not guessing anymore.”
Garage Door Company Owner
This targeted data approach works for garage doors, HVAC, roofing, plumbing, and any other service where homeowners actively
search for help. Let’s see what it can do for your market.
