Zeo delivery method
Review Strategy & Reputation Signals
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.


Some of the 500+ brands we've worked with
See all referencesStages and gates
How we do it
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.
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.


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.


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.


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.
Deliverables and acceptance
What you get
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.
Fit and readiness
When you need this
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.
The specialists behind this SEO work
Zeo's SEO work goes back to 2006, when we started what we call the first SEO blog in the MENA region. The consultants shown here are doing that work today, matched to what this page covers.

Hande Parmaksız
SEO Manager

Sinem Bakır Yavaş
Senior SEO Executive

Ali Özgün Öz
SEO Executive

Gülşah Şahin Özkan
Senior SEO Analyst

Sena Önder
Senior SEO Executive

Aybüke Göktuna
Senior SEO Analyst

Ruhan Tiryaki
Senior SEO Analyst

Yağmur Bayram
Sr. SEO Analyst

Zafer Yıldız
Web Analytics Manager

İlker Emir
Senior Performance Marketing Executive

İpek Ezer
Performance Marketing Executive

Onur Durdağı
Performance Marketing Executive

Sevda Yurtvermez
Performance Marketing Team Lead

Serap Yurtvermez
Performance Marketing Team Lead

Abdullah Tanıdır
Performance Marketing Team Lead
Tools we use
Tools behind this work
GatherUpreview request automation, feedback capture, and response monitoring
Podiumrequest delivery, reply handling, and conversation history
Chatmetermulti-location review themes and location-level escalation queues
Google Business Profilesource review context and authorized public response checks
Yextcross-platform review inbox, assignments, and response audit trail
BrightLocalreview source coverage and unanswered queue monitoring
Next step
Build a fairer customer feedback loop


Before we start

















