per year, as a range. Not a point estimate, because the honest evidence does not support one.
The band is the range a Harvard Business School study actually measured — five to nine percent of demand per full star, identified by comparing businesses that landed just above and just below a rounding threshold. Your 0.9★ gap is worth that much of the new patients you already see. Most vendors quote you a single dramatic number instead. There isn’t one. There is a range, and this is it.
At 3.6★, 22% of patients say your rating clears their personal minimum; at 4.5★ that becomes 92%. On the numbers you entered, that is about 27.9 people a month who say your rating would stop them.
We do not put a dollar figure on that line, because patients report far stricter standards than they act on. Taken literally, these thresholds say a practice at 2.5★ would see almost no new patients at all — which every working practice at 2.5★ disproves by continuing to exist. It shows you the mechanism. The money above comes from what was measured, not what was reported.
[+] Where these numbers come from
Why a range and not a number. The best-identified research on this question produces a range, not a point. Reporting the midpoint would imply a precision the evidence does not have, and reporting the top of it would be marketing.
The screening bar shows the mechanism: the cumulative share of patients whose self-reported minimum acceptable rating your rating clears. It is built from the RepuGen 2025 Patient Review Survey (1,212 patients), in which 78% report requiring four stars or better. We show it and deliberately do not price it, because stated thresholds are aspirational: taken literally they would predict that a practice at 2.5★ sees virtually no new patients, and practices at 2.5★ plainly do.
The dollar band comes from causal research on what rating changes actually do to demand. Luca (Harvard Business School) used the rounding thresholds on Yelp as a natural experiment and found one full star moves revenue 5–9%, with independent businesses affected more than chains. In healthcare specifically, AJMC found a single 1-star review cut new patient volume 2.3–2.6% for at least sixteen weeks. The band you see is Luca’s 5–9% range applied to the new patients you already report seeing, which is why that input matters more than any other on this page.
Both ends are valued at patient lifetime revenue (revenue per year × years retained) and scale with provider count. Luca’s estimate comes from restaurants rather than clinics, and independent businesses showed larger effects than chains — an independent practice is the closer analogue, which is one reason the true figure may sit toward the upper end. The recovery counts on the left are not estimates at all: they are exact arithmetic, assuming new reviews average five stars and your displayed badge rounds to one decimal.
See a real read of your actual practice.
This is the sketch. The real one is an on-site walkthrough, mystery-patient calls, and your own numbers — done by one person who builds it, runs it, and reads it back. M.A., Industrial & Organizational Psychology.