When Google retired manual Local Services Ads (LSA) disputes around mid-2024, it did not leave advertisers entirely voiceless. In place of the old dispute button sits the Rate this lead survey — a lightweight way to tell Google what you thought of each lead. The mistake many owners make is treating this survey as a re-skinned dispute form: fill it out, get your money back. It does not work that way. Used correctly, though, the survey is a genuine tool for protecting spend over time. This article explains what it actually is and how to get value from it.
A signal, not a lever
The single most important thing to understand is the difference between a lever and a signal. The old dispute was a lever: you pulled it, and a human-or-rules review decided your refund on that specific lead. The Rate this lead survey is a signal: your input becomes one input among many that the machine-learning credit model weighs. You are informing a system, not commanding it.
That means two things. First, rating a lead as bad does not guarantee a credit — the model still makes its own assessment during its roughly 72-hour window. Second, your ratings compound. Consistent, honest feedback helps the model understand the quality patterns on your account, which can improve how it assesses future leads. The payoff is cumulative, not transactional.
What the survey influences
- Per-lead assessment. Your rating is evidence the model can factor into whether that lead is deemed invalid and creditable.
- Account-level pattern learning. Over many leads, your feedback contributes to how the system understands your typical lead mix.
- Your own visibility. Even setting aside the model, rating leads forces you to categorize them, which is the raw material for measuring lead quality.
What it will not do
Set expectations honestly, especially with clients:
- It will not credit a job-type mismatch. A caller who wanted a service adjacent to yours is a valid lead no matter how you rate it.
- It will not credit an in-area geographic mismatch. You defined the service area.
- It will not credit ordinary lost sales — price objections, tire-kickers, prospects who chose a competitor.
- It does not change how credits work in excluded verticals like healthcare and tax.
How to rate leads well
Because the survey is a signal, its quality depends on your discipline. Sloppy or self-serving ratings feed the model noise.
Rate promptly and consistently
Build rating into your daily lead review while the interaction is fresh. A consistent hand across all leads is more useful to the model than sporadic, mood-driven ratings.
Rate honestly, not optimistically
Do not mark valid-but-unconverted leads as junk to fish for credits. It will not fool the assessment, and it degrades the signal you are trying to build. Reserve negative ratings for genuinely invalid contacts — spam, wrong numbers, no-intent calls.
Attach evidence where you can
For call-based leads, the recording or transcript is your best documentation. Knowing why a lead was junk — a robocall, a solicitation, a person looking for a different business — makes your internal categorization defensible and your ratings accurate.
Keep your own ledger
The survey lives inside Google. Keep a parallel record of what you rated and why, so you can reconcile against the credits that actually appear within about 30 days and measure your true net spend.
| Do | Do not |
|---|---|
| Rate every lead consistently | Rate only when hoping for a credit |
| Mark genuine junk as invalid | Mark lost sales as junk |
| Use call recordings as evidence | Guess from memory days later |
| Track ratings vs. actual credits | Assume a rating equals a refund |
The realistic payoff
Even used perfectly, the survey operates inside a system where third-party estimates put recoverable spend around 6 to 7 percent. So the honest goal is not to squeeze dramatic refunds out of the survey — it cannot deliver them. The goal is to give the model the cleanest possible signal so that the credits you are entitled to actually materialize, and to build the internal habit of categorizing leads that powers every other quality improvement you make. The survey rewards discipline, not wishful thinking.
Frequently asked questions
Is the Rate this lead survey the same as the old dispute button?
No. The old dispute was a lever that decided a refund on a specific lead, while the Rate this lead survey is a signal, one input among many that the machine-learning credit model weighs, so a bad rating does not guarantee a credit.
Does rating a lead as bad guarantee a credit?
No. The model still makes its own assessment during its roughly 72-hour window, and it will not credit job-type or geo mismatches, ordinary lost sales, or excluded verticals like healthcare and tax; ratings help most cumulatively by teaching the model your account's quality patterns.
How should I rate LSA leads to protect spend?
Rate every lead promptly and honestly, reserving invalid ratings for genuine junk like spam and wrong numbers, use call recordings as evidence, and keep your own ledger to reconcile against credits that appear within about 30 days.