Customer Sentiment
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Customer Sentiment Backend

Customer Sentiment App Backend Template
NPS Tracking and Feedback Aggregation

A production-ready customer sentiment backend on Back4app with users, surveys, responses, and feedback. Includes ER diagram, data dictionary, JSON schema, API playground, and an AI Agent prompt for rapid bootstrap.

Key Takeaways

This template gives you a customer sentiment backend with users, surveys, responses, and feedback so your team can focus on gathering and analyzing customer insights.

  1. User-centric schema designModel users with profiles and survey responses in clear, queryable structures.
  2. Real-time feedback collectionUse Back4app's real-time capabilities for survey responses and feedback updates.
  3. NPS trackingTrack Net Promoter Scores with aggregated survey responses.
  4. Survey and response featuresAllow users to participate in surveys and provide feedback seamlessly.
  5. Cross-platform sentiment backendServe mobile and web clients through a single REST and GraphQL API for users, surveys, responses, and feedback.

What Is the Customer Sentiment App Backend Template?

Back4app is a backend-as-a-service (BaaS) for fast product delivery. The Customer Sentiment App Backend Template is a pre-built schema for users, surveys, responses, and feedback. Connect your preferred frontend (React, Flutter, Next.js, and more) and ship faster.

Best for:

Customer feedback applicationsNPS tracking platformsSurvey and response appsMobile-first feedback appsMVP launchesTeams selecting BaaS for sentiment analysis

Overview

A customer sentiment product needs user profiles, surveys, responses, and feedback.

This template defines User, Survey, Response, and Feedback with real-time features and ownership rules so teams can implement sentiment analysis quickly.

Core Customer Sentiment Features

Every technology card in this hub uses the same customer sentiment backend schema with User, Survey, Response, and Feedback.

User profiles and surveys

User class stores username, email, password, and survey participation.

Survey creation and management

Survey class links title, description, and timestamps.

Responding to surveys

Response class stores survey reference, user, score, and feedback.

Feedback management

Feedback class tracks user comments and suggestions.

Why Build Your Customer Sentiment Backend with Back4app?

Back4app gives you user, survey, response, and feedback primitives so your team can focus on gathering insights and improving customer satisfaction instead of infrastructure.

  • User and survey management: User class with profile fields and survey class for feedback management supports sentiment analysis.
  • Response and feedback features: Manage responses with scores and allow users to provide detailed feedback easily.
  • Realtime + API flexibility: Use Live Queries for feedback updates while keeping REST and GraphQL available for every client.

Build and iterate on customer sentiment features quickly with one backend contract across all platforms.

Core Benefits

A customer sentiment backend that helps you iterate quickly without sacrificing structure.

Rapid feedback launch

Start from a complete user, survey, and response schema rather than designing backend from zero.

Real-time feedback support

Leverage real-time feedback and updates for enhanced customer insights.

Clear feedback flow

Manage user feedback with detailed comments and suggestions for improvement.

Scalable permission model

Use ACL/CLP so only users can edit their profiles and responses, and manage feedback submissions.

Survey and response data

Store and aggregate survey responses and feedback for display and analysis without schema resets.

AI bootstrap workflow

Generate backend scaffolding and integration guidance fast with one structured prompt.

Ready to launch your customer sentiment app?

Let the Back4app AI Agent scaffold your customer sentiment backend and generate users, surveys, responses, and feedback from one prompt.

Free to start — 50 AI Agent prompts/month, no credit card required

Technical Stack

Everything included in this customer sentiment backend template.

Frontend
13+ technologies
Backend
Back4app
Database
MongoDB
Auth
Built-in auth + sessions
API
REST and GraphQL
Realtime
Live Queries

ER Diagram

Entity relationship model for the customer sentiment backend schema.

View diagram source
Mermaid
erDiagram
    User ||--o{ Survey : "creator"
    User ||--o{ Feedback : "user"
    User ||--o{ Response : "user"
    Survey ||--o{ Feedback : "survey"
    Survey ||--o{ NPS : "survey"
    Survey ||--o{ Response : "survey"

    User {
        String objectId PK
        String username
        String email
        String password
        String profilePicture
        Date createdAt
        Date updatedAt
    }

    Survey {
        String objectId PK
        String title
        String description
        Date createdAt
        Date updatedAt
    }

    Feedback {
        String objectId PK
        Pointer survey FK
        Pointer user FK
        String content
        Date createdAt
        Date updatedAt
    }

    NPS {
        String objectId PK
        Pointer survey FK
        Number score
        Date createdAt
        Date updatedAt
    }

    Response {
        String objectId PK
        Pointer survey FK
        Pointer user FK
        Array answers
        Date createdAt
        Date updatedAt
    }

Integration Flow

Typical runtime flow for auth, user profiles, surveys, responses, and feedback.

View diagram source
Mermaid
sequenceDiagram
  participant User
  participant App as Customer Sentiment App
  participant Back4app as Back4app Cloud

  User->>App: Login
  App->>Back4app: POST /login
  Back4app-->>App: Session token

  User->>App: View available surveys
  App->>Back4app: GET /classes/Survey
  Back4app-->>App: List of surveys

  User->>App: Submit feedback
  App->>Back4app: POST /classes/Feedback
  Back4app-->>App: Feedback objectId

  User->>App: Submit NPS score
  App->>Back4app: POST /classes/NPS
  Back4app-->>App: NPS objectId

Data Dictionary

Full field-level reference for every class in the customer sentiment schema.

FieldTypeDescriptionRequired
objectIdStringAuto-generated unique identifierAuto
usernameStringUser login name
emailStringUser email address
passwordStringHashed password (write-only)
profilePictureStringURL of the user's profile picture
createdAtDateAuto-generated creation timestampAuto
updatedAtDateAuto-generated last-update timestampAuto

7 fields in User

Security and Permissions

How ACL and CLP strategy secures users, surveys, responses, and feedback.

User-owned profile controls

Only the user can update or delete their profile; others cannot modify user content.

Survey and response integrity

Only the author can create or delete their surveys and responses. Use Cloud Code for validation.

Scoped read access

Restrict survey and response reads to relevant parties (e.g. users see their own surveys and public feedback).

Schema (JSON)

Raw JSON schema definition ready to copy into Back4app or use as implementation reference.

JSON
{
  "classes": [
    {
      "className": "User",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "username": {
          "type": "String",
          "required": true
        },
        "email": {
          "type": "String",
          "required": true
        },
        "password": {
          "type": "String",
          "required": true
        },
        "profilePicture": {
          "type": "String",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "Survey",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "title": {
          "type": "String",
          "required": true
        },
        "description": {
          "type": "String",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "Feedback",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "survey": {
          "type": "Pointer",
          "required": true,
          "targetClass": "Survey"
        },
        "user": {
          "type": "Pointer",
          "required": true,
          "targetClass": "User"
        },
        "content": {
          "type": "String",
          "required": true
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "NPS",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "survey": {
          "type": "Pointer",
          "required": true,
          "targetClass": "Survey"
        },
        "score": {
          "type": "Number",
          "required": true
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "Response",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "survey": {
          "type": "Pointer",
          "required": true,
          "targetClass": "Survey"
        },
        "user": {
          "type": "Pointer",
          "required": true,
          "targetClass": "User"
        },
        "answers": {
          "type": "Array",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    }
  ]
}

Build with AI Agent

Use the Back4app AI Agent to generate a real customer sentiment app from this template, including frontend, backend, auth, and user, survey, response, and feedback flows.

Back4app AI Agent
Ready to build
Create a customer sentiment app backend on Back4app with this exact schema and behavior.

Schema:
1. User (use Back4app built-in): username, email, password; objectId, createdAt, updatedAt (system).
2. Survey: title (String, required), description (String); objectId, createdAt, updatedAt (system).
3. Response: survey (Pointer to Survey, required), user (Pointer to User, required), score (Number, required), feedback (String); objectId, createdAt, updatedAt (system).
4. Feedback: user (Pointer to User, required), content (String, required); objectId, createdAt, updatedAt (system).

Security:
- Only the user can update/delete their profile. Only the author can create/delete their surveys and responses. Use Cloud Code for validation.

Auth:
- Sign-up, login, logout.

Behavior:
- List users, create surveys, respond to surveys, provide feedback, and manage responses.

Deliver:
- Back4app app with schema, ACLs, CLPs; frontend for user profiles, surveys, responses, and feedback.

Press the button below to open the Agent with this template prompt pre-filled.

This is the base prompt without a technology suffix. You can adapt the generated frontend stack afterward.

Deploy in minutes50 free prompts / monthNo credit card required

API Playground

Try REST and GraphQL endpoints against the customer sentiment schema. Responses use mock data and do not require a Back4app account.

Loading playground…

Uses the same schema as this template.

Choose Your Technology

Expand each card for integration steps, state patterns, data model examples, and offline notes.

Flutter Customer Sentiment Backend

React Customer Sentiment Backend

React Native Customer Sentiment Backend

Next.js Customer Sentiment Backend

JavaScript Customer Sentiment Backend

Android Customer Sentiment Backend

iOS Customer Sentiment Backend

Vue Customer Sentiment Backend

Angular Customer Sentiment Backend

GraphQL Customer Sentiment Backend

REST API Customer Sentiment Backend

PHP Customer Sentiment Backend

.NET Customer Sentiment Backend

What You Get with Every Technology

Every stack uses the same customer sentiment backend schema and API contracts.

Unified customer sentiment data structure

A pre-built database schema for managing users and feedback.

Real-time feedback collection for customer sentiment

Instantly gather and analyze customer sentiments through surveys.

Secure sharing for customer sentiment

Safeguard sensitive user data with robust access controls.

REST/GraphQL APIs for customer sentiment

Flexible APIs to fetch and manipulate data seamlessly.

Customizable survey templates for customer sentiment

Easily create and modify surveys to suit your needs.

Analytics dashboard for customer sentiment

Visualize customer feedback trends and insights in real-time.

Customer Sentiment Framework Comparison

Compare setup speed, SDK style, and AI support across all supported technologies.

FrameworkSetup TimeCustomer Sentiment BenefitSDK TypeAI Support
Rapid (5 min) setupSingle codebase for customer sentiment on mobile and web.Typed SDKFull
~5 minFast web dashboard for customer sentiment.Typed SDKFull
About 5 minCross-platform mobile app for customer sentiment.Typed SDKFull
Under 5 minutesServer-rendered web app for customer sentiment.Typed SDKFull
~3 minLightweight web integration for customer sentiment.Typed SDKFull
Rapid (5 min) setupNative Android app for customer sentiment.Typed SDKFull
~5 minNative iOS app for customer sentiment.Typed SDKFull
About 5 minReactive web UI for customer sentiment.Typed SDKFull
Under 5 minutesEnterprise web app for customer sentiment.Typed SDKFull
Quick (2 min) setupFlexible GraphQL API for customer sentiment.GraphQL APIFull
~2 minREST API integration for customer sentiment.REST APIFull
Under 5 minServer-side PHP backend for customer sentiment.REST APIFull
About 5 min.NET backend for customer sentiment.Typed SDKFull

Setup time reflects expected duration from project bootstrap to first survey query using this template schema.

Frequently Asked Questions

Common questions about building a customer sentiment backend with this template.

What is a customer sentiment backend?
What does the Customer Sentiment template include?
Why use Back4app for a sentiment analysis app?
How do I run queries for users and surveys with Flutter?
How do I create a response with Next.js server actions?
Can React Native cache users and surveys offline?
How do I prevent duplicate responses?
What is the best way to show user profiles and surveys on Android?
How does the feedback flow work end-to-end?

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