Review Velocity Safety

Velocity in context

Filters do not judge speed alone; they judge speed against your baseline. A profile that has averaged four reviews a month for two years and suddenly gains forty triggers scrutiny regardless of how real those forty reviews are — a burst after a news story or a community event can flag an honest business.

If you expect a legitimate surge — a viral post, a news mention — document it. Screenshots and dates make appeals fast when the filter misreads the spike.

Healthy ranges

Most local businesses thrive at five to twenty new reviews a month. High-volume businesses — busy restaurants, retail — can sustain fifty or more naturally. The safe rule is proportion: your review graph should resemble your customer graph. If one runs far ahead of the other, expect questions.

Recovering from a false flag

When real reviews disappear after a spike, check for a policy email, verify the reviews came from actual customers, and appeal with your documentation. Do not respond by buying replacements — that converts a false positive into a true one.

Keep reading

• delivery timelines
• retention
• drip feeding decoded

Where the details come from: Online reputation overview and Word of mouth.