Under Google's current Local Services Ads (LSA) credit model, the feedback you give on a lead and the credit you may receive are separated by time and process. Owners who do not understand the sequence misread the signals constantly — expecting instant refunds, panicking when a credit does not appear the next day, or assuming a rating did nothing because they did not see an immediate result. This article walks through the lead-feedback lifecycle so you can read it accurately and act on the right cadence.
The two windows that govern everything
Two timeframes define the entire experience, and confusing them is the source of most misunderstanding:
- Assessment — roughly 72 hours. After a lead arrives, Google's machine-learning system takes a few days to assess whether it qualifies as invalid. During this window the outcome is being determined; it is not visible or final.
- Credit — within about 30 days. If a lead is deemed creditable, the actual credit posts within roughly a monthly billing cycle. The money returns well after the assessment concludes.
So the natural rhythm is: lead today, assessment over the next few days, credit sometime within the next month. Judging outcomes faster than that guarantees false conclusions.
What your feedback is and is not
The Rate this lead survey is how you weigh in, and it replaced the old manual dispute. Critically, a rating is a signal to the model, not a command that forces a credit. A thumbs-down or a low rating is evidence the system can consider during assessment — alongside its own signals about the lead. This is why a rated-bad lead does not always convert into a credit: your input is one factor, and for job-type or in-area geo mismatches it will not move the outcome at all because those are valid charges by definition.
Reading the signals correctly
| What you observe | What it usually means |
|---|---|
| No credit within a day of rating | Normal — assessment takes ~72h, credit up to ~30 days |
| Rated bad, no credit ever came | Model judged it valid, or it was a non-creditable mismatch |
| Credit appeared without you rating | Model assessed it invalid on its own signals |
| Credit posts weeks after the lead | Expected — the ~30-day credit lag |
The most important row is the third: credits can appear whether or not you rated the lead, because the model assesses independently. Your rating improves the signal, but it is not the sole trigger.
Timing your feedback
Because assessment runs over roughly three days, the practical advice is to rate leads promptly — ideally the same day — so your signal is available while the model is still forming its judgment. Waiting a week to rate a lead is likely too late to influence its assessment, though consistent late ratings still help the model learn your account patterns over time. The habit to build is a daily lead review where you rate each new lead while the interaction is fresh and the details are documented.
Keep your own ledger
Because the credit lands weeks later and often without a prominent notice, you need a record outside Google to connect cause and effect. For each lead, log the date, your rating, and the reason. Then, as credits post over the following weeks, mark which leads they correspond to where you can. This ledger is what lets you:
- Confirm that credits you expected actually arrived.
- Compute true net cost per lead once the credit lag has closed.
- Sanity-check your recovery rate against the realistic 6 to 7 percent ceiling from third-party estimates.
- Spot patterns — for instance, recurring junk from a particular time of day or a rise in mismatch leads pointing at targeting to fix.
Common misreads to avoid
- Expecting same-day credits. The system does not work that way; the two windows guarantee a lag.
- Assuming a rating equals a refund. It is a signal, and mismatches and lost sales are never creditable regardless of rating.
- Concluding feedback does nothing. The effect is cumulative and partly invisible; you are training assessment on your account over time.
- Ignoring credits you did not rate. The model credits independently, so reconcile all credits, not only ones you flagged.
The disciplined rhythm
Put together, the healthy cadence is simple: review and rate leads every day, document why, wait out the assessment and credit windows, and reconcile credits against your ledger on a trailing basis. That rhythm keeps your expectations calibrated to how the system actually behaves — slow, probabilistic, and modest — and it ensures the credits you are genuinely owed do not slip by unnoticed while you avoid chasing refunds that were never coming.
Frequently asked questions
How long does it take to get an LSA lead credit after I rate a lead?
Under Google's current machine-learning auto-credit model, a lead is typically assessed within about 72 hours, and if it is deemed creditable the credit generally posts within roughly 30 days. A same-day credit is not how the system works, so expect a lag of a few days to a month.
Does rating a lead thumbs-down guarantee a credit?
No. The Rate this lead survey is a signal the machine-learning model can weigh, not a command that forces a credit. Job-type and in-area geo mismatches are valid charges and will not be credited regardless of how you rate them.
Will I still get credits on leads I never rated?
Yes. Google's model assesses leads on its own signals and can credit an invalid lead even if you did not rate it, so reconcile every credit against your records, not only the ones you flagged.