Executive briefing

Citizen Feedback Management for the Civil Government Bureau

From service surveys to a platform for the full voice of the citizen

Sprinklr CFM August 2026

This briefing

Agenda

01 What Sprinklr CFM is

The platform behind this proposal

02 Where we stand today

The service-survey flow — and its ceiling

03 The case for moving

What changes — and what waiting costs

04 The path forward

Timeline and next steps

01 · What Sprinklr CFM is

Feedback Has Changed

Citizens' expectations are set by the best conversation they had yesterday — not by the last government form they filled in.

Conversation is the new interface

Citizens live in chat and messaging — static forms feel like paperwork.

AI reads open text at scale

What once needed analysts is now automatic — every comment becomes usable signal.

Expectations follow experience

Private-sector service sets the bar citizens hold government to.

Multiple-choice surveys were built for the previous era. The tools have moved on.

01 · What Sprinklr CFM is

What Sprinklr CFM Is

An AI-native feedback platform that manages the full life of a piece of feedback — on the Sprinklr environment the Bureau already runs.

LISTEN

Capture on any channel

SMS, WhatsApp, email, QR at service centres, in-app — classic or conversational.

ANALYZE

AI reads every answer

Themes, sentiment and root causes surfaced out of the box — no manual reporting.

ACT

Close every loop

Negative feedback becomes a case — routed, tracked, resolved, and the citizen informed.

02 · Where we stand today

Social Care Surveys Today

The current deployment — social care surveys, triggered after every closed case

Case arrives

A citizen DMs the Ministry of Municipality on X about trash in the street — a case opens on Sprinklr

→

Case is handled

The Ministry resolves the issue and the agent closes the case

→

Survey goes out on the social channel

A survey link lands in the same X DM thread, carrying the case context

→

Basic survey result

No follow-up with citizens — and surveys see very low response rates

This pipeline works — and it stays. What changes is what flows through it.

No open text, no AI

Answers stay structured — no AI to read the citizen's own words

A score without a why

No root cause behind the rating

The loop never closes

No trace from feedback to fix to citizen

No analysis on the data

Results are mostly quantitative, not qualitative

02 · Where we're going

Social Care Surveys Tomorrow

The same pipeline — but the survey becomes a conversation, and the loop closes

Case arrives

Same citizen, same DM about trash in the street — a case opens on Sprinklr

→

Case is handled

The Ministry's agent resolves the issue — and collects the citizen's phone number before closing

→

Conversational survey via SMS / WhatsApp

Sent to the collected number. No number shared? It drops in the same X DM thread instead

→

Citizen replies in his own words

A conversational survey — a score plus "the street is clean now, but it took three days"

→

Escalation & follow-up

Low-CSAT responses and complaints are escalated — the Ministry reaches back out to the citizen

→

Case closure — loop closed

The follow-up resolves, the citizen is informed, and the survey loop closes

→

Reporting & AI analysis

Qualitative AI analysis of every response — themes, sentiment, root causes — for data-based decisions

03 · The case for moving

From Score to Conversation

TODAY · STATIC SURVEY

Thank you for contacting the Ministry of Municipality. How would you rate your experience?

Very satisfied

Neutral

Not satisfied

One tap, one number. The reason leaves with the citizen.

→

same SMS,
same link

WITH CFM · CONVERSATIONAL

How was your experience with the Ministry of Municipality today?

The street is clean now, but it took three days.

AI FOLLOW-UPSorry it took that long — did you get updates while the trash was being cleared?

No — I had to check the street myself.

The root cause is captured in the moment, in the citizen's own words.

Link-out survey response

Conversational, in-channel

3–10×response rates

~40%richer feedback

02 · Where we stand today

Service Centre Surveys Today

The second live deployment — offline agents at physical service centres, also on Service Surveys

Agent signs in

Opens the Persona app and selects service centre, counter and service

→

Citizen takes a ticket

Qmatic issues the queue token and sends name, phone and service reason to Sprinklr

→

Case at the counter

Agent creates a Sprinklr case, pre-populated from Qmatic; records resolved or not

→

Case closed

The service itself runs in the ministry's system; Sprinklr tracks the interaction and outcome

→

Survey SMS

Closure triggers a rule-based SMS with a link to rate the visit

OPTIONAL PATH · COMPLAINTS

Via a supervisor or a dedicated complaint screen — routed to the responsible department, with a reference number sent by SMS and direct follow-up from the department.

Same ceiling as social care

Link-out SMS, structured answers, no AI on the feedback — both flows hit the same limits

03 · The case for moving

Why Move to CFM

Conversational feedbackSurveys that talk back — AI follow-ups turn a rating into a reason.

AI-native reportingThemes, drivers and root causes surfaced automatically — analysis stops being a manual job.

A closed loop, end to endEvery detractor becomes a tracked case, through to resolution — and the citizen hears back.

Built to expandService-centre surveys, WhatsApp and email, in-app feedback — one platform ahead of the roadmap.

Same Sprinklr platform, same team, no retraining — a migration, not a reimplementation.

03 · The case for moving

What Changes in Practice

CAPABILITY SERVICE SURVEYS TODAY SPRINKLR CFM

Survey builder Static core builder, no AI, rule-engine setup AI-assisted builder with templates and version history

Question types & logic Core types incl. multiple choice; limited display logic Everything today, plus conversational formats and full skip/display logic

Translations 100% manual 1-click, AI-powered — 160+ languages

Distribution Case-based, rule-driven, contact-centre channels Channel-agnostic, with profile and transaction targeting

Analytics & insights Manual reporting; text analytics needs custom build OOTB AI tagging, sentiment, root-cause and correlation analysis

Acting on feedback Manual closed-loop configuration; no outer loop AI-assisted closed-loop cases, plus Action Plans for systemic fixes

Everything in use today — including multiple-choice surveys — carries over. CFM adds the layers Service Surveys was never built for.

03 · The case for moving

Room to Grow

NOW · PILOT

Pilot on one entity

Social care surveys move to CFM for a single entity — the proving ground

All entities

After a successful pilot, social care surveys roll out on CFM across all entities

THEN

Service centres

Post-visit surveys across Qatar's service centres move to CFM, with on-site kiosks

BEYOND

More channels & in-app

WhatsApp, email and surveys inside any government app — the MOI super app is one example

Every stop runs on the platform the Bureau already owns — expansion is a decision, not a procurement.

03 · The case for moving

Proven Results

+15%

Survey completion

More signal captured on every channel

70%

Faster time to action

Teams act before dissatisfaction spreads

−50%

Escalations

From reactive firefighting to routine recovery

Recognised as a Leader in Voice of the Customer by major analyst firms, 2025–2026 · figures are typical first-months movement reported by CFM customers