CS Customer Service System

Based on the latest RuoyiPlus backend architecture, 6 DOs / 5 Controllers, menu ID starting at 8500, building an omnichannel intelligent customer service and ticket management system


1. Enhancement Positioning and Architecture

1.1 Product Positioning

RuoYiPlus CS Customer Service System centers around three core pillars—Omnichannel Access, Intelligent Ticket Routing, and Service Quality Control—to deliver enterprise-level enhancement, achieving full-process digital management from customer touchpoints to problem resolution.

1.2 Module Scale

MetricValue
Data Objects (DO)6
Controllers5
Menu ID Start8500
Maven Moduleyudao-module-cs

1.3 Core Data Tables

Table NameDescription
cs_conversationConversation Management
cs_ticketTicket Management
cs_contactContact Management
cs_inboxInbox Management
cs_canned_responseCanned Responses
graph TB subgraph "RuoYiPlus CS Enhanced Architecture" subgraph "Channel Access Layer" A1[WeChat Channel] A2[APP Channel] A3[Phone Channel] A4[Email Channel] A5[Social Media Channel] end subgraph "Business Processing Layer" B1[Conversation Management] B2[Ticket Management] B3[Intelligent Bot] B4[Knowledge Base] end subgraph "Control Layer" C1[SLA Management] C2[Quality Scoring] C3[Permission Control] C4[Audit Tracking] end end A1 --> B1 A2 --> B1 A3 --> B1 A4 --> B1 A5 --> B1 B1 --> B2 B1 --> B3 B3 --> B4 B2 --> C1 B2 --> C2 B1 --> C3 B2 --> C4

1.4 Capability Comparison

DimensionTraditional CSRuoYiPlus CS Enhanced
Channel AccessSingle channelUnified omnichannel access
Ticket ManagementSimple ticketsFull-process ticket management
Intelligent CSNoneAI intelligent Q&A + bot
Knowledge BaseNoneKnowledge base + intelligent search
Service QualityNoneSLA management + quality scoring
Permission ControlNoneCS tiered permissions + data isolation
Audit ComplianceNoneConversation audit + quality traceability

2. Omnichannel Access

2.1 Channel Architecture

graph TB subgraph "Omnichannel Access" subgraph "Instant Messaging" A1[WeChat Official Account] A2[WeChat Mini Program] A3[WeCom] A4[DingTalk] A5[Feishu] end subgraph "Traditional Channels" B1[Phone Support] B2[Email Support] B3[SMS Support] end subgraph "Social Media Channels" C1[Weibo] C2[TikTok] C3[Xiaohongshu] end subgraph "Unified Access" D1[Message Aggregation] D2[Conversation Management] D3[Customer Identification] D4[Context Persistence] end end A1 --> D1 A2 --> D1 A3 --> D1 A4 --> D1 A5 --> D1 B1 --> D1 B2 --> D1 B3 --> D1 C1 --> D1 C2 --> D1 C3 --> D1 D1 --> D2 D2 --> D3 D3 --> D4
Channel TypeDescription
WeChat ChannelsOfficial account, mini program, WeCom
APP ChannelsIn-app embedded, H5 pages
Phone ChannelsInbound/outbound, IVR navigation
Email ChannelsEmail tickets, auto-reply
Social Media ChannelsWeibo, TikTok and other social platforms

3. Full-Process Ticket Management

3.1 Ticket Workflow

graph TB A[Ticket Creation] --> B[Auto Classification] B --> C[Auto Assignment] C --> D[Ticket Processing] D --> E{Resolved?} E -->|Yes| F[Customer Confirmation] E -->|No| G[Ticket Escalation] G --> D F --> H[Satisfaction Rating] H --> I[Ticket Archiving] A --> A1[Multi-Channel Creation] A --> A2[Template-Based Creation] C --> C1[Assignment by Type] C --> C2[Assignment by Skill] C --> C3[Assignment by Region] D --> D1[Accept and Process] D --> D2[Collaborative Processing] D --> D3[Progress Update]

3.2 Ticket Permission Control

The ticket system implements role-based data permission control, ensuring agents can only access tickets within their permission scope.

Permission LevelScopeDescription
AgentOwn ticketsCan only view and process tickets assigned to them
Team LeadTeam ticketsCan view and assign all team tickets
CS ManagerAll ticketsCan view all tickets and perform statistical analysis
QA PersonnelSampled ticketsCan randomly sample tickets for quality scoring

3.3 Ticket Audit

All ticket operations record complete audit logs, supporting ticket processing traceability.

graph LR A[Ticket Creation] --> B[Ticket Assignment] B --> C[Ticket Processing] C --> D[Ticket Escalation] D --> E[Ticket Resolution] E --> F[Ticket Archiving] A -.-> G[Audit Log] B -.-> G C -.-> G D -.-> G E -.-> G F -.-> G

4. Intelligent Customer Service Bot

4.1 Bot Architecture

graph TB subgraph "Intelligent Bot" subgraph "Q&A Engine" A1[Knowledge Base Search] A2[Semantic Understanding] A3[Intelligent Matching] end subgraph "Business Processing" B1[Business Query] B2[Business Processing] B3[Ticket Creation] end subgraph "Human-Bot Collaboration" C1[Bot Reception] C2[Intelligent Handoff to Human] C3[Human Assistance] end end A1 --> A2 A2 --> A3 A3 --> B1 B1 --> B2 B2 --> B3 B3 --> C1 C1 --> C2 C2 --> C3

4.2 Core Capabilities

CapabilityDescription
Intelligent Q&AKnowledge base search, semantic matching
Multi-Turn DialogueContext understanding, intent recognition
Business ProcessingSelf-service query, self-service processing
Intelligent HandoffAutomatic handoff to human for complex issues
Human AssistanceKnowledge recommendations, script suggestions

5. Knowledge Base Management

5.1 Knowledge Base System

graph TB subgraph "Knowledge Management" subgraph "Knowledge Collection" A1[FAQ Entry] A2[Document Import] A3[Knowledge Extraction] end subgraph "Knowledge Organization" B1[Knowledge Classification] B2[Knowledge Tags] B3[Knowledge Association] end subgraph "Knowledge Application" C1[Intelligent Search] C2[Knowledge Recommendation] C3[Knowledge Push] end subgraph "Knowledge Maintenance" D1[Knowledge Update] D2[Knowledge Expiration] D3[Knowledge Archiving] end end A1 --> B1 A2 --> B1 A3 --> B1 B1 --> B2 B2 --> B3 B3 --> C1 C1 --> C2 C2 --> C3 C3 --> D1 D1 --> D2 D2 --> D3
CapabilityDescription
Knowledge EntryFAQ, documents, Q&A pairs
Intelligent SearchSemantic search, keyword search
Knowledge RecommendationRelated knowledge recommendations
Knowledge StatisticsUsage statistics, effectiveness evaluation

6. Service Quality Management

6.1 SLA Service Levels

graph LR A[Ticket Creation] --> B{Priority} B -->|Critical| C[5-Min Response] B -->|Important| D[15-Min Response] B -->|Normal| E[30-Min Response] C --> F[30-Min Resolution] D --> G[2-Hour Resolution] E --> H[24-Hour Resolution]
cs:
  sla:
    levels:
      - name: "Critical"
        response-time: 5m
        resolve-time: 30m
      - name: "Important"
        response-time: 15m
        resolve-time: 2h
      - name: "Normal"
        response-time: 30m
        resolve-time: 24h
    monitoring:
      alert-threshold: 80%  # Alert if compliance rate falls below 80%

6.2 Quality Scoring

QA DimensionMetrics
Response SpeedResponse time compliance rate
Resolution QualityProblem resolution rate, first-contact resolution rate
Service AttitudePolite language, service standards
Professional CompetenceKnowledge accuracy, processing capability
Customer SatisfactionSatisfaction score, positive rating rate

7. Technical Architecture

graph TB subgraph "yudao-module-cs-plus" subgraph "cs-biz" A1[channel - Channel Access] A2[session - Conversation Management] A3[ticket - Ticket Management] A4[robot - Intelligent Bot] A5[knowledge - Knowledge Base] A6[sla - SLA Management] A7[quality - Quality Management] A8[agent - Agent Management] A9[workspace - Workspace] A10[analytics - Data Analysis] end subgraph "Permissions and Audit" B1[permission - Permission Control] B2[audit - Audit Logs] end end A1 --> B1 A2 --> B2 A3 --> B2 A4 --> B1 A5 --> B1

8. Business Value

Value PointDescription
Efficiency ImprovementIntelligent bot, quick tools
Cost ReductionBot diversion, self-service
Satisfaction ImprovementQuick response, professional service
Service Quality ControlSLA management, quality scoring
Data-Driven OptimizationPerformance analysis, issue analysis
Compliance and TraceabilityTicket audit, conversation traceability
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