Case Study: Statewide Car Wash

Results

Increased YoY lead flow by 90% and decreased cost per conversion by 54%

A multi-location car wash chain operating across Texas partnered with us to improve the performance of their Google Ads campaigns. While the brand already had market presence and foot traffic, paid search performance varied significantly by location.

Some locations produced results, others struggled with inefficiencies, and overall lead quality lacked consistency. The client needed a scalable Google Ads management strategy that could be replicated across locations while maintaining strong local performance.

This case study highlights results from one individual location, with the same framework later applied across multiple markets statewide.

Our Approach

We approached this account with the mindset of building a repeatable acquisition engine, not a one-off campaign.

Lead-Focused Performance Max Implementation

We rebuilt Performance Max around a true lead-generation objective. Instead of allowing the campaign to optimize loosely for engagement signals, we structured it to prioritize high-intent actions that reflected real customer interest.

This included tighter audience signals, cleaner asset group structure, and alignment between ad messaging and on-site intent. The campaign was designed to attract customers actively searching for nearby car wash services, not casual browsers.

Aggressive Negative Keyword Control

One of the biggest improvements came from tightening the negative keyword list.

We eliminated searches related to employment, equipment purchases, business opportunities, and unrelated automotive services. This significantly reduced wasted impressions and prevented budget from leaking into non-converting traffic.

As a result, impression quality improved even as overall impressions increased.

Cleaner Assets Built for Trust

We introduced new creative assets focused on clarity and trust. Messaging emphasized convenience, location relevance, and service reliability. Visual assets were updated to reflect a clean, professional brand presence rather than generic stock imagery.

This helped increase engagement from users who were already close to making a decision.

Precise Location Targeting

Location targeting was tightened to focus strictly on realistic service areas around the physical location. This eliminated out-of-market traffic and improved conversion intent by ensuring ads were shown only to users who could reasonably visit the location.

Our Results

The performance improvements were clear and measurable.

The campaign generated 538 clicks from 25,902 impressions, resulting in a click-through rate of just over 2 percent. While this may appear modest on the surface, it reflected a deliberate shift toward higher-quality traffic rather than broad exposure.

The average cost per click stabilized at $1.77, which is highly efficient for a competitive local automotive service market.

Most importantly, the campaign delivered 17 verified conversions, representing a significant increase over the previous period. Conversion volume increased by nearly 90 percent, while cost per conversion dropped by more than 50 percent.

The final cost per lead settled at $55.94, down substantially from earlier performance, while maintaining strong lead quality.

These were not low-intent interactions. Each conversion represented a real customer action tied to service demand at the local level.

Why This Worked

This result came from discipline, not experimentation.

By aligning Performance Max with lead-based outcomes, aggressively filtering traffic through negatives, and tightening geographic relevance, we removed inefficiencies that commonly hold local campaigns back.

Instead of letting automation run unchecked, we guided it with structure, intent, and clean data. This allowed Google’s systems to optimize correctly and consistently.

Scalability Across Locations

This location was not an exception.

The same framework has been applied across multiple car wash locations throughout Texas, producing similar gains in efficiency and lead quality. While each market requires slight adjustments, the core strategy has proven repeatable and reliable.

This is exactly what the client needed. A Google Ads management system that works not just once, but across an entire footprint.

For multi-location local businesses, performance does not come from spending more or expanding targeting.

It comes from control.

When campaigns are built around real leads, filtered aggressively, and grounded in location-specific intent, Google Ads becomes a predictable growth channel rather than a guessing game.

This case study demonstrates how disciplined Google Ads management can produce consistent results at the local level while remaining scalable across an entire brand.

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