
Wondering how to consistently produce your target leads per month?
Read our appliance repair PPC case study and discover how we helped Edellin Home Services transform its Google Ads account into a structured lead generation system that consistently produces more than 100 leads per month.
The company has been running paid advertising.
The campaigns were active.
But…
It lacked the strategic structure required to generate predictable results.
The business was already investing in Google Ads, but performance was inconsistent. Campaigns were not segmented by service, negative keywords were not properly implemented, and tracking systems were incomplete.
Without clear data visibility, it was difficult to identify which campaigns were generating profitable appliance repair leads.
To solve this problem, the entire advertising system was rebuilt from the ground up.
The strategy focused on creating a structured Google Ads architecture supported by accurate tracking, targeted campaign segmentation, and continuous optimization.
Several key components were implemented as part of the new system:
Full conversion and call tracking
Structured campaign architecture
Appliance-specific search campaigns
Comprehensive negative keyword management
Strategic use of Performance Max campaigns
Budget scaling based on real performance data
Expansion through Local Services Ads
This appliance repair PPC case study shows how a properly structured advertising system can transform inconsistent campaigns into a predictable lead generation engine.
By focusing on data, segmentation, and disciplined optimization, Edellin Home Services was able to scale its monthly lead volume while maintaining control over advertising efficiency.
The Problem
When Edellin Home Services initially approached us, the business was already running Google Ads campaigns. However, the account lacked the strategic structure needed to support scalable growth.
The company offered several appliance repair services and had strong technical expertise. Despite this, the advertising system did not effectively capture demand from customers searching for specific appliance repair solutions.
A review of the account revealed several structural issues that limited performance.
Incomplete tracking
The account did not have full visibility into conversions. Calls and form submissions were not consistently tracked, which made it difficult to determine the true cost per lead.
Unstructured campaign setup
Campaigns were built too broadly without proper segmentation. Multiple appliance repair services were grouped together, reducing ad relevance and making optimization difficult.
No defined negative keyword strategy
The account was attracting irrelevant search traffic. This included searches from people looking for DIY repair solutions, appliance parts, or employment opportunities.
Limited performance insights
Because campaigns were not segmented by appliance type or service category, it was difficult to identify which services were generating the most leads.
Inconsistent lead flow
Without proper structure and optimization, lead generation fluctuated from month to month. This made it difficult for the business to plan staffing and service capacity.
The goal was not simply to increase ad spend.
Instead, the objective was to build a structured Google Ads system capable of generating consistent, high-quality appliance repair leads.
The Strategy
The strategy behind this appliance repair PPC case study focused on rebuilding the advertising system in phases.
Each improvement created more clarity and control within the account, which made it possible to scale lead generation without increasing wasted spend.
The process began with fixing the most important issue: tracking.
Step 1: Install Proper Tracking
Before making any major campaign adjustments, the first priority was implementing full tracking across the account. Without accurate data, it is impossible to make reliable optimization decisions.
The new tracking framework captured every key conversion point.
Tracking improvements included:
Call tracking implementation
Every phone call generated through advertising campaigns was tracked. This provided clear insight into which campaigns and keywords were driving actual inquiries.
Form submission tracking
Website forms were integrated with conversion tracking to measure online service requests.
Campaign-level attribution
Each conversion was connected to its specific campaign source, allowing performance comparisons across campaigns.
Service-level performance visibility
Tracking allowed the team to analyze lead volume and conversion rates by appliance type.
For the first time, the account provided reliable data on several critical metrics:
Cost per lead
Conversion rates
Lead volume by appliance type
Performance by campaign
This new level of visibility allowed optimization decisions to be based on real performance data rather than assumptions.
Step 2: Rebuild Campaign Architecture
Once tracking was in place, the next step was restructuring the entire campaign architecture. The previous setup grouped multiple services together, which limited targeting precision.
The new system introduced a structured campaign framework designed around service categories and search intent.
The account was reorganized into several campaign types.
Search campaigns segmented by appliance
Dedicated campaigns were created for specific appliance repair services. This allowed the ads and keywords to match the exact service customers were searching for.
Brand campaigns
Brand-focused campaigns captured searches for the company name. This ensured the business remained visible for customers already familiar with the brand.
Service-specific campaigns
Additional campaigns targeted high-intent appliance repair searches related to specific problems and services.
Performance Max campaigns
Once search campaigns were stable, Performance Max campaigns were introduced to expand reach across additional Google inventory.
Each campaign included several structural improvements.
Dedicated ad groups
Keywords were grouped based on closely related search intent, which improved ad relevance.
Clean keyword segmentation
Organizing keywords by appliance type helped increase targeting precision.
Strong negative keyword lists
Negative keywords filtered out irrelevant search traffic.
Clear budget allocation
Budgets were distributed across campaigns based on service demand and performance.
This structured campaign architecture reduced wasted spend and improved ad relevance for potential customers.
Step 3: Implement a Negative Keyword System
A major source of wasted budget in the original account was irrelevant search traffic. Without negative keyword management, ads were appearing for searches that had little chance of converting into real appliance repair jobs.
To address this issue, a comprehensive negative keyword system was implemented.
Key improvements included:
Cross-campaign negative keyword lists
Shared lists ensured irrelevant queries were excluded across multiple campaigns.
DIY repair exclusions
Searches from users looking for instructions or tutorials were filtered out.
Job seeker filtering
Keywords related to employment opportunities were excluded to prevent ads from appearing to job applicants.
Low-intent query blocking
Searches related to appliance parts or unrelated services were excluded.
These improvements significantly improved lead quality. Ads were now being shown primarily to users actively searching for appliance repair services.
Step 4: Introduce Performance Max Strategically
Once the search campaigns were optimized and producing stable results, Performance Max campaigns were introduced as a strategic expansion layer.
Performance Max can capture additional demand across Google’s advertising network, including display placements, YouTube, and other inventory.
However, these campaigns work best when supported by strong search campaign data.
In this system:
Search campaigns remained the backbone
High-intent search campaigns continued to capture the majority of appliance repair demand.
Performance Max expanded reach
The campaign helped identify additional opportunities and reach potential customers across other Google channels.
Campaign control remained focused on search
Search campaigns maintained the highest level of control over keyword targeting and lead quality.
This balanced approach allowed the account to expand visibility while maintaining performance stability.
Step 5: Scale Budget Based on Results
With the new campaign architecture and optimization systems in place, the next step was strategic budget scaling.
Rather than increasing budgets blindly, investment decisions were based on measurable performance indicators.
Scaling decisions were guided by:
Cost per lead performance
Campaigns with strong lead efficiency received increased budgets.
Conversion consistency
Campaigns showing stable conversion rates were considered reliable candidates for scaling.
Service-level profitability
Appliance repair services generating the most valuable leads received greater investment.
As budgets increased gradually, lead volume also increased in a controlled and predictable way.
Step 6: Launch Local Services Ads
To further expand visibility, Local Services Ads were introduced alongside the existing Google Ads campaigns.
Local Services Ads offer several advantages for home service companies.
Key benefits included:
Top-of-search placement
LSAs appear at the very top of search results, often above traditional paid ads.
Google-backed trust signals
The Google Guaranteed badge increases trust and credibility with potential customers.
Pay-per-lead structure
Instead of paying per click, businesses pay only when a customer contacts them directly through the ad.
Adding Local Services Ads created another channel for capturing high-intent appliance repair leads.
The Results
The results of this appliance repair PPC case study demonstrate how structured campaign management can significantly improve advertising performance.
After rebuilding the Google Ads system, Edellin Home Services experienced several key improvements.
More than 100 leads per month
The new campaign structure generated consistent monthly lead volume.
Predictable demand generation
Lead flow stabilized, making it easier for the business to plan staffing and scheduling.
Improved advertising efficiency
Negative keyword management and campaign segmentation reduced wasted spend.
Higher lead quality
Ads reached customers actively searching for appliance repair services.
With consistent lead generation, the business was able to scale its operations and expand its team to meet increasing demand.
Before the restructuring, ads were running but lacked strategic direction.
After the transformation, the advertising system became a reliable acquisition engine capable of supporting long-term growth.
Key Takeaways
This appliance repair PPC case study highlights several important lessons for home service businesses using paid advertising.
Tracking is essential before scaling
Accurate data provides the insights needed to make effective optimization decisions.
Campaign structure improves performance
Segmentation by service and search intent increases ad relevance and conversion rates.
Negative keywords protect advertising budgets
Filtering out irrelevant searches helps ensure ads reach the right audience.
Strategic expansion improves reach
Combining search campaigns with Performance Max and Local Services Ads can increase total lead volume.
Data-driven scaling produces predictable growth
Budget increases should always be based on performance metrics rather than assumptions.
Edellin Home Services now generates 100+ appliance repair leads every month after restructuring its Google Ads campaigns with proper tracking, segmentation, and optimization.
If your ads are active but results are inconsistent, the issue is often campaign structure, not budget. We help appliance repair companies turn inconsistent campaigns into reliable lead generation systems. Start with a professional review of your account.



