Case Study: AI Max Scales Local Conversions Without Sacrificing Efficiency

A controlled AI Max test across local franchise markets

Between December 1, 2025 and January 31, 2026, our paid search strategy team ran a controlled AI Max test across five locations for one of our home services franchise brand partners, designed specifically to measure how Google’s AI-driven Search enhancements perform against traditional keyword-centric campaign structures. This was not a partial-week test or a quick performance snapshot. We gave the test a full learning runway, with the following parameters in place:

• Test type: Location-level control vs. AI Max test in Google Ads
• Measurement window: Full-flight, two months (learning stabilized)
• Primary KPIs: Conversions, cost per conversion (CPA), conversion rate, and scale (impressions and clicks)
• Methodology: Each location ran parallel control and AI Max campaigns as Google Experiments, allowing us to isolate performance impact without seasonal distortion

The core question we wanted to answer: Will AI Max unlock incremental demand while maintaining the efficiency local home services franchises require to scale? In our test, the answer was yes, with guardrails.

The results: conversion growth showed up everywhere

Across the five locations, conversions increased in every test market, and four of the five locations saw materially stronger performance with AI Max.
One location underperformed on cost-per-acquisition (CPA), which is not a reason to dismiss AI Max, just another example of why testing in a controlled environment produces a wealth of new insights. Here is what we saw in terms of conversion lift and CPA impact, by location:

• Location 1: +97% conversion lift, CPA slightly up
• Location 2: +720% conversion lift, CPA improved 63%
• Location 3: +318% conversion lift, CPA flat
• Location 4: +410% conversion lift, CPA improved 30%
• Location 5: +350% conversion lift, CPA improved 50%

Our biggest takeaway from the data? AI Max consistently delivered outsized conversion growth, and in most cases, it did so more efficiently than legacy keyword structures. In other words, this was not incremental lift. In several markets, AI Max fundamentally changed what “scale” looked like.

Why AI Max performed: Three lessons franchise marketers should internalize

1. AI Max captured demand keyword lists will never fully reach

In this test, AI Max consistently surfaced conversions from queries traditional keyword lists never see, particularly longer, more conversational, problem-based searches. This is especially important in home services, where consumers often search for symptoms and urgency first, not service categories. Keyword coverage breaks down at scale when the real-world language of customers changes by season, local market, specific needs and timing.

2. Efficiency came from signals, not from keyword precision

The markets that produced the largest AI Max gains shared a common thread: strong fundamentals.

• Clean conversion tracking
• Clear primary conversion goals
• Strong landing page relevance

AI Max does not fix weak inputs. It amplifies whatever you feed it.

3. The “losing” market was the most valuable insight

One location did not outperform control on CPA, and that is the point. Local markets vary by competitive density, service mix, conversion signal quality, and budget thresholds. AI Max is not a switch you simply flip. It is a system you validate. Our operating principle is that AI adoption without testing can create additional risk. AI adoption with testing creates better leverage and better insight.

Guardrails that matter for franchises (and why we use them)

For franchise and multi-location brands, brand governance and local relevance are not optional. That is why our recommendation is not “turn on everything” and expect immediate improvement to your ROAS. Pairing AI Max with the right controls is what ultimately creates the best environment for success. Here are three recommendations you should consider in establishing a baseline for future optimization.

Recommendation 1: Start with controlled tests, market by market

It’s important that you roll out AI Max in a measured way:

• Market by market
• With clear control benchmarks
• Over full learning windows, not partial weeks

This is how you earn the right to scale budgets in the markets where AI Max proves it can deliver.

Recommendation 2: Disable final URL expansion for local franchise campaigns

In local franchise campaigns, routing traffic to the wrong location page can create downstream issues: wrong service area, wrong phone number, wrong offer, wrong experience. That is why we recommend disabling Final URL Expansion in many franchise contexts. When Final URL Expansion is on, AI Max can override the final URL you set and route users to a different landing page on the same domain that Google believes is more relevant. If you want to lock traffic to a specific landing page, you need this setting off.

Recommendation 3: Optimize conversion signals before you scale, then keep watching efficiency

Before enabling AI Max, it’s important to evaluate current campaigns and consider:

• Removing low-value conversions
• Prioritizing booked leads, qualified calls, or estimates
• Aligning KPIs to real business outcomes

AI Max needs clean, high-quality signals to learn what matters. From there, AI Max creates more campaign performance wins when you:

• Reallocate incremental budget
• Expand impression share in high-return markets
• Monitor CPA stability as scale increases

In Summary: AI Max is just getting started

AI Max is arriving at the same moment search itself is being reshaped by AI-driven experiences. The results page is no longer a list of links. It’s increasingly an interactive destination, and visibility is increasingly earned within AI surfaces, not only through traditional rankings.  From our perspective at Location3, that means two things are happening at once:

1. Paid search is becoming more intent-native. AI Max pushes campaigns beyond rigid keyword constraints and closer to matching what people mean, not just what they type.
2. Franchise brands need stronger systems, not more complexity. As the search ecosystem shifts toward AI answers and zero-click behaviors, the brands that win will be the ones that connect structured local signals, creative assets, and conversion measurement into a unified identity that machines can recognize and recommend.

This is exactly why we view the case study above as a model. It is not a hype story. It’s a disciplined proof point: AI Max can drive meaningful incremental demand in local franchise markets while holding efficiency, but only when you apply the right governance. The bottom line for franchise marketers is that AI Max is not a shortcut. It is an accelerator. When paired with strong fundamentals, disciplined testing, and location-level accountability, it becomes a powerful lever for sustainable local growth. If your franchise brand is still relying on keyword coverage as the primary lever for scale, this is your sign to evolve the playbook. Start with controlled tests. Protect local landing page integrity. Strengthen conversion signals. Then scale further. That is how franchise brands can create a recipe for success and create more wins in the AI era of search.

Interested in learning more about how we can help your franchise brand deliver better results in paid search? Get in touch with our team and let’s start the conversation.