Abe Lamoreaux (https://www.linkedin.com/in/abelamo/)
Compliance Playbook: Collect More Reviews Without Getting Flagged
Everyone wants more reviews, but paying customers to leave reviews is certainly not the way to get them. Here are some do's and do not's for getting more reviews without getting in trouble.
Published November 6th, 2025
Everyone wants more reviews, but paying customers to leave reviews is certainly not the way to get them. Here are some do's and do not's for getting more reviews without getting in trouble.
Has your favorite influencer ever received a free product and been asked to review the product? Did you ever stop to consider, perhaps, that review will certainly be biased towards the company that gave it for free and potentially paid them?
More than ever, companies understand how to source highly visible reviews that land them in front of potential customers. The question, more than ever, is how do I get reviews and stay safe from losing them due to a lack of fair play?
Goal: help your team earn more reviews while staying on the right side of the FTC and platform rules. No loopholes. No stress. Just clean, repeatable habits that scale.
TL;DR (what’s safe vs. risky)

Safe, scalable
Ask every eligible customer the same way (no cherry-picking).
Reward the action (the ask, the workflow), not the star rating.
Never script positive sentiment; never pressure edits.
Disclose any material connection (e.g., “thanks gift”) clearly and up front
Keep your facts consistent (name, phone, hours) across profiles.
Likely to get you flagged
Review gating (“only ask happy customers”).
Incentives contingent on positive reviews or star minimums.
Asking on platforms that prohibit asks (e.g., Yelp says “don’t ask”).
Editing/suppressing negative reviews or nudging customers to change them.
Fake or paid-for reviews, employees reviewing you without disclosure.
Quick disclaimer: This is practical guidance, not legal advice. When in doubt, have counsel review your policy.
The rules in plain English
FTC (Endorsement Guides; 2023 updates)
Reviews must be real and reflect honest opinions.
If there’s anything of value offered (gift card, discount, sweepstakes entry), that’s a material connection → disclose it clearly in or near the review request and (ideally) in the review itself.
No review gating or hiding negatives; your collection flow can’t prefer positives.
Google / Apple / Others
Google: You can ask for reviews. Don’t offer incentives tied to sentiment; don’t post from your own location’s device (avoid IP weirdness).
Apple / Apple Maps / Apple Business Connect: Ask is fine; keep it authentic and avoid mass, duplicate, or templated content.
Yelp: Do not ask. Yelp can penalize for solicitation (downranking, badges). Let Yelp reviews happen organically; you may link to your Yelp page passively (e.g., on your website) but avoid direct asks or QR codes.
Industry platforms (Angi, BBB, etc.): Generally okay to ask; follow their specific incentive/disclosure rules.

Field mechanics: how to collect more (compliantly)
1) Universal ask (for platforms that allow it)
Script (15 seconds):
“Before I head out, would you mind sharing a quick review about your experience today? It helps my manager see I took good care of you. Here’s my badge—scan and it’ll take you to our page.”
Ask every job (success or service recovery).
Timing: right after the work is done, while you’re still on site.
Make it frictionless: NFC badge or QR that opens your review hub (lets the customer choose their platform).
No steering (“5-star,” “positive”). Keep it neutral.
2) Yelp-safe flow (no direct ask)
Do not ask. Instead:
Include Yelp logo/link on your site’s Reviews page (passive).
Add “Find us on Yelp” to email signatures and receipts (no call-to-action to review).
Focus on great service + visibility; Yelp’s algorithm will surface organic reviews over time.
3) Post-visit follow-up (for allowed platforms)
Text/email (neutral language):
“Thanks for choosing us today. If you’re willing to share feedback about your visit, here’s the link: <review hub>. Positive or negative, we read every note to improve.”
Send within 24–48 hours.
Include opt-out.
Keep it single click to the review hub.
Incentives that won’t burn you
Principle: Reward behavior under your control (attempts, verified review links sent), not the customer’s sentiment.
Compliant SPIFs (examples)
Per verified ask
Per published review (any rating) mentioning the tech’s name
Milestones (# of reviews, length of reviews)
Do not
Pay more for higher star ratings.
Run raffles that only include positive reviewers.
Offer discounts/gifts only if the review is changed or removed.

If you ever run a public “thank-you” gift:
Keep it platform-agnostic (not Yelp).
Disclose: “We offer a small thank-you for any honest review, positive or negative.”
Aim to tag disclosure in the ask and on the landing page. (Some platforms also allow “I received a thank-you” tick boxes.)
Review gating vs. service recovery (the safe line)
Review gating (not allowed): Asking “Are you happy?” and only sending the review link to “Yes” customers.
Service recovery (allowed, smart): If a job goes sideways, fix it first—then send the same neutral review link you send to everyone. Your flow never withholds the link based on sentiment.
Incident response (if something trips a wire)
If something happens, the key is to respond promptly, and to reach out to the review system itself. A common problem is unsolicited reviews coming from people that never used your service. If this is an issue, reach out to providers like Google and Yelp as well as reporting them for never having used the service.
Copy-and-paste assets
Neutral review CTA (on-site / text):
“Mind leaving a quick review about your experience today? Good or bad, it helps us improve.”
Disclosure (if you ever do a universal thank-you):
“We sometimes offer a small thank-you for any honest review—positive or negative. No purchase or rating required.”
Tech talk-track (Yelp-safe day):
“Thanks again—I’m leaving my card with all our links if you ever need us. Have a great day.” (No request to review.)

Abe Lamoreaux (https://www.linkedin.com/in/abelamo/)
AI Consultant
