One neutral request rule for every eligible customer, sensitive cases kept with people, and recurring themes routed to the teams that can fix the underlying experience.

Review operations damage trust when teams ask only happy customers, use incentives to influence participation, automate sensitive replies, or dismiss recurring complaints as a reputation issue instead of treating them as an operational signal.

We create a neutral request process, a responsibly managed response queue, and a clear path from supported review themes to the teams that can improve the underlying customer experience.

A customer-feedback team sorts review cards into response, escalation, and service-improvement paths beside a visible neutral-request rule.

Some of the 500+ brands we've worked with

See all references
  • Domino’s
  • Joker
  • Wall Street English
  • Jack Martin Menswear
  • Yatsan

We begin with the customer journey and current platform rules, then design request and response processes that stay fair even when the queue gets busy.

  1. Define the policy, audience, and owners

    We review current solicitation and response policies, consent and contact basis, eligible customer events, exclusions, frequency limits, opt-outs, location and service ownership, response voice, and the conditions that pause requests or public replies.

    A review playbook with one neutral eligibility rule, named owners, channel limits, suppression behavior, escalation contacts, and stop conditions.

    AI assist
    AI summarizes current platform policies and previous request patterns into one draft set of rules, giving the team a starting point for review instead of a blank page.
    Human gate
    Before the playbook is finalized, named owners decide the eligibility rule, frequency limit, and conditions that pause requests or public replies. One eligibility rule is approved.
  2. Identify honest moments to request a review

    We identify genuine completion points in the customer journey and apply the same request logic to every eligible customer. We test timing, channel, language, frequency, delivery tracking, and opt-out handling without filtering people by expected satisfaction or rating.

    A request plan showing who may be contacted, which real event makes them eligible, which approved channel may be used, and why someone may be excluded.

    AI assist
    AI tests possible timing and channel combinations against delivery and opt-out data to show which moments reach customers without contacting them too often.
    Human gate
    Before the logic is used with actual customers, a specialist confirms that predicted satisfaction or rating never determines eligibility. The request logic is verified as sentiment-blind.
  3. Organize response and escalation work

    We group existing reviews by verified location, service, theme, urgency, response status, and available factual context. Personal data, threats, legal claims, fraud, safety issues, and other sensitive cases go to the appropriate human owner before anyone drafts a public response.

    A response and escalation matrix that separates routine factual replies from cases requiring service, legal, privacy, safety, or leadership review.

    AI assist
    AI classifies incoming reviews by theme and urgency, and flags personal data, threats, or legal claims as soon as they appear in the text.
    Human gate
    A named human owner decides how to handle every sensitive case before a public reply is drafted, and no flagged review is automatically routed for publication. Every sensitive case is routed to a named owner.
  4. Respond responsibly and assign recurring themes

    Specialists prepare factual, empathetic drafts using approved information. Location or service owners verify the underlying event and handle recovery away from public disclosure. Supported recurring themes go to operational owners with a corrective action and a later check.

    A theme insight board and response record showing what was said, what was escalated, which service issue was assigned, and what evidence is still missing.

    AI assist
    A factual, empathetic reply gets drafted from verified context, and recurring complaint themes get grouped so a pattern is not lost among individual responses.
    Human gate
    The location or service owner verifies the underlying event and decides the corrective action before a recurring theme is assigned and marked as resolved. The theme has a verified corrective action and an owner.

AI drafts, classifies, and flags; a named person decides every sensitive reply.

AI summarizes current platform policies and previous request patterns into one draft rule set, tests timing and channel combinations against delivery and opt-out data, classifies incoming reviews by theme and urgency and flags personal data, threats, or legal claims as soon as they appear, drafts a factual, empathetic reply from verified context, and groups recurring complaint themes so a pattern is not lost among individual responses. No flagged review is automatically routed for publication. We do not write, buy, trade, incentivize, gate, suppress, impersonate, or selectively request reviews, we do not disclose personal data, argue with reviewers, or expose private service recovery in a public reply, and we do not promise ratings, review counts, or local-pack positions.

A feedback loop somebody is accountable for, which improves the service without turning your customers into rating targets.

  • Playbook

    Review request playbook

    Accepted when

    Eligibility, completion events, channels, frequency caps, consent, suppression, opt-outs, localization, ownership, and pause conditions are explicit and independent of expected ratings.

  • Decision matrix

    Response and escalation matrix

    Accepted when

    Routine, factual, sensitive, legal, privacy, safety, fraud, and crisis cases each have an owner, an approved route, and a limit on public disclosure.

  • Dashboard

    Customer theme insight board

    Accepted when

    Themes remain linked to source reviews, verified service context, confidence, accountable teams, corrective actions, and unresolved evidence.

  • Audit report

    Compliance & outcome log

    Accepted when

    Requests, responses, opt-outs, complaints, policy events, escalations, and operational follow-up remain reviewable by location, service, and channel.

We call it done when: The request playbook, escalation matrix, theme board, and outcome log are done when eligibility, completion events, channels, frequency caps, consent, suppression, opt-outs, localization, ownership, and pause conditions are explicit and independent of expected ratings, every case type has an owner, an approved route, and a public-disclosure limit, every theme stays linked to its source reviews, verified service context, confidence, accountable team, corrective action, and unresolved evidence, and requests, responses, opt-outs, complaints, policy events, and follow-up remain reviewable by location, service, and channel.

Reviews span locations and services, and yet request timing, response ownership, and escalation usually still come down to whoever happens to be looking.

A good fit when

  • Different teams request reviews at different points and through different channels, without a shared neutral eligibility rule, frequency limit, suppression process, or opt-out path.
  • Reviews remain unanswered or receive inconsistent replies because no one owns factual checks, brand voice, privacy decisions, sensitive cases, or service recovery.
  • Recurring customer themes are visible but never linked to verified service incidents, an operations owner, corrective work, and a later check.

Better handled as other work when

  • The aim is to buy, trade, write, impersonate, incentivize, gate, suppress, or selectively request reviews according to the rating or sentiment you expect.
  • There is no lawful basis for contacting customers, no current platform policy, no consent or suppression checks, no approved response language, and no escalation route for legal, safety, fraud, privacy, or crisis cases.

If one of these is closer to your situation, start here instead: Local SEO

We call it done when: Eligible customers all fall under the same neutral request rule. Response and escalation ownership is clear, and sensitive cases stay with people. Supported recurring themes reach the service owners, and a policy or consent risk can pause the whole process.

  • GatherUp

    review request automation, feedback capture, and response monitoring

  • Podium

    request delivery, reply handling, and conversation history

  • Chatmeter

    multi-location review themes and location-level escalation queues

  • Google Business Profile

    source review context and authorized public response checks

  • Yext

    cross-platform review inbox, assignments, and response audit trail

  • BrightLocal

    review source coverage and unanswered queue monitoring

Your current request messages, the review queues, the platform worries, and wherever escalation currently falls through. A neutral, accountable first version comes out of that.
Plan review operations with Zeo

Eligibility comes from a genuine customer event and the same approved rule for everyone in that eligible group. Predicted rating, sentiment, staff judgment, complaint status, and incentives do not affect the decision. Consent, contact basis, frequency caps, suppression, channel limits, and opt-outs still apply.