Reputation Math

Review Rating Ledger

Work out exactly how many new top-rated reviews you need, how many low-rated ones would need to come off the books, or the blend of both.

Enter your numbers
Pull these straight from Google Business Profile (or any platform with a 1–5 star scale).
reviews
max ★
on file

Two straight paths
Assuming you only work one lever at a time.
Add only
new top-rated reviews needed, with nothing removed
Remove only
low-rated reviews taken down, with none added
Trade ratio
1 removal does the work of this many additions

Find your blend
Drag to see how many additions you'd still need for a given number of removals.
Low-star reviews removed 0
Remove (debit)
Low-star reviews taken down0
Subtotal0
Add (credit)
Top-star reviews still needed
Subtotal
CurrentTarget
This blend lands you at across reviews.

Estimated revenue impact
Modeled from published research on star ratings and revenue — a directional estimate, not a guarantee.
$
sales / mo
Where this comes from: Harvard Business School research (Luca, 2011) found a one-star Yelp increase corresponded with a 5–9% revenue increase for independent restaurants, using a causal regression-discontinuity design. This tool prorates that rate linearly for partial-star moves and applies it to your numbers as an industry benchmark, not a guarantee — actual results vary by industry, market, and review volume. A separate cross-industry study of 200,000+ small businesses (Womply, 2019) found revenue tends to peak around 4–4.5 stars and plateau or dip at a perfect 5.0, likely due to lower review volume or perceived authenticity at the extreme.
Reality check: platforms only remove reviews for policy violations — no verifiable transaction, fake engagement, harassment, off-topic content, or conflict of interest. A review can't come down just for being negative but legitimate. Audit low-star reviews individually before counting on the "remove" side of this ledger.