Service 04 Fastest to move Weeks, not quarters

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The rating that ends the comparison.

Great customers, mediocre score, because only the angry ones post. That gap is the most fixable thing in your marketing, and the one models read as a verdict.

The fastest win we offer. Review volume moves in weeks, not quarters.

Your score is a sampling error.

It doesn't measure how good you are. It measures who felt strongly enough to type.

Recency beats volume

Buyers and models both weight recent reviews far above old ones. Two thousand from 2021 read as a company that peaked; forty from last month read as one that's alive.

→ steady flow, not a spike

Models quote the aggregate

Asked whether you're any good, an answer engine reaches for a number and a sentence about what people complain about. Both are set by who reviewed you last quarter.

→ the sentence, not just the star

The silent majority is yours

The customers who renewed without a word outnumber the angry ones many times over. Nobody has ever asked them at the right moment.

→ ask well, ask often

Ask everyone. Incentivise nobody.

Find the moment a customer is happiest, ask them then, make it take forty seconds, and never pay for, gate or filter what they say.

  • Journey mappingThe three or four moments where satisfaction peaks (a resolved ticket, a successful onboarding, a second order) with the ask built into them.
  • Multi-platform collectionTrustpilot, G2, Google, Capterra, the app stores. Whichever ones your buyers and the answer engines actually read.
  • Response managementEvery review answered, including the bad ones, in a voice that reads as a person. Models read the replies too.
  • Negative-review triageFix the underlying problem, then invite an honest update where the reviewer agrees. Never a removal request.
  • Employer reviewsOptional, and increasingly relevant. Models cite Glassdoor when asked what you're like to deal with.
  • Monthly reportingVolume, average, recency, platform mix, and the themes people keep raising. Usually the most useful page for your product team.

We don't buy reviews, reward positive ones, or gate the ask so only happy customers see it. That's illegal in the US, against every platform's terms, and Google removed 292 million reviews in a single year for it.³ A score built that way evaporates in one sweep.

Where the missing reviews are

Would review if askedActually reviewed
Delighted customers~3% posted
Satisfied, uneventful~1% posted
Had a problem, resolved~8% posted
Had a problem, unresolved~40% posted

Illustrative shape, not measured data, but the asymmetry is the point. Frustration posts itself; everything else has to be invited.

The number moves first.

Which is why we usually start here, even when Reddit is the bigger prize.

Weeks 1–2

Wire it up

Journey mapped, platforms claimed, requests built into moments that already exist. No new tooling to learn.

Weeks 3–8

Volume climbs

The backlog of happy customers gets asked for the first time. Most of the movement happens here.

Month 3 onward

It self-sustains

New customers keep recency high permanently, and the themes report starts telling your product team things it didn't know.

One site, or all of them.

Priced on platform count and the volume running through your customer journey. Two hundred invitations a month is a different job from twenty thousand.

Single platform

One site claimed and optimised, collection wired into two journey moments, every review answered, monthly report.

Request a quote3 months minimum

Multi-platform

Up to five platforms, full journey mapping, response management, negative-review triage, themes report.

Request a quote3 months minimum

Set-up only

We build the machine and your team runs it: collection, response templates, compliance guardrails, half-day handover.

Request a quoteone-off · 4 weeks

What moves the number. Platform count, customer volume, languages, and whether your journey already has touchpoints to hang an ask on.

  • Platform count
  • Customer volume
  • Languages
  • Journey complexity
Request a quote

Third-party platform fees are billed by Trustpilot, G2 and the rest, not us, and sit outside any quote. Prices exclude VAT.

We went from 3.6 to 4.5 in four months without changing a thing about the product. Turns out we just weren't asking.

Lena FischerHead of CX, Aviato Rentals

The themes report is the thing I didn't expect. Our roadmap changed twice because of what customers kept writing in reviews.

Tomasz WierzbickiHead of Product, marketplace

Another agency offered us a shortcut. These ones explained exactly how that shortcut ends and we stopped taking that call.

Isabel MárquezCOO, DTC brand

The honest version.

It depends on how good you already are. Most companies sit below their true score because only annoyed customers post; ask everyone properly and the honest majority shows up. If your service is genuinely bad, no programme fixes that, and we'll say so during the audit.

Only ones that breach platform policy: fake, defamatory, or from someone who was never a customer. Genuine negative reviews stay, and they're load-bearing. A profile with no criticism reads as manufactured, and the public reply often sells harder than the review cost you.

No. Incentivised reviews are illegal in the US under FTC rules and get whole histories wiped when detected, taking the legitimate ones with them. We also never gate the ask so only happy customers receive it. Platforms treat that the same way.

Whichever ones your buyers check and the answer engines quote, which is usually not the list marketing assumes. B2B software: G2 and Capterra. Consumer: Trustpilot and Google. Anything with an app: the stores. The audit tells you which models actually cite in your category.

Not if it's timed right and asked once. The common failure is a quarterly blast to the whole list, which reads as spam. Asking one customer once, just after something went well, has a far higher response rate and no complaints worth mentioning.

Find out what AI is telling your buyers.

It starts with a visibility audit: €1,499, delivered in a week. What the major models say about you, about your two closest competitors, and the shortest route to changing it.

Plàmenos

An AI visibility studio. We make brands legible to the models people ask first, through Reddit, Wikipedia and reviews.

© 2026 Plàmenos · Amsterdam

Figures marked 1–4 come from published research and platform reporting; studies measure different things, so read them as direction rather than a scoreboard. We work strictly within each platform's rules: we don't buy reviews, run fake accounts, or edit Wikipedia with undisclosed conflicts of interest.