Star rating recovery calculator

Each new review's impact on your average is diluted by every review that came before. A 1-star at 10 reviews drops you 0.4 stars; a 1-star at 1,000 reviews drops you 0.004 stars. The fix isn't to chase recovery after the bad one lands — it's to keep collecting steadily so a single bad review barely moves the needle.

If your average is A across N reviews and you get a new review at rating B, the new average becomes (A·N + B) / (N+1). To recover to A by adding k five-star reviews: k ≥ (A − B) / (5 − A). Always rounds up. At A = 5.0, the denominator is zero and recovery is mathematically impossible — any review below 5 permanently lowers a perfect average.

4.5–4.9 is the sweet spot. Below 4.0 and customers filter you out of search results; above 4.9 looks suspicious (consumers assume curated reviews). The Harvard Business Review found a half-star bump can add 5–9% in revenue for restaurants — the leverage on rating is huge.

Yes. The number you see on your Google Business Profile is the live arithmetic mean of every review on the listing. There's no smoothing or weighting. New reviews are counted from the moment they pass moderation (usually minutes).

Route customers based on how they feel before they leave a public review. SignalRoute asks the customer how their experience went; happy customers go to Google in one tap, unhappy ones get a private feedback channel where you can fix the issue before it becomes a public 1-star. The math above is why prevention is so much cheaper than recovery — every point of average rating you protect is worth dozens of 5-star reviews you'd otherwise need to chase.