Primary Use Case: Customer Profile & Behavioral Insights

Background Overview

360° profiles of social customers require integrating data from community interactions, content clicks, transactions, services, and feedback. Without unified insights, it's impossible to identify high-value customers, churn risks, or product opportunities. This primary use case describes how to build customer profiling systems, behavioral analysis, insight reports, and strategy integration, letting data drive customer operations.

Goals & Value

• Complete Profiling: Aggregate social channel data with CRM master data.
• Behavioral Analysis: Identify trends, preferences, paths, problems.
• Insight Reports: Provide actionable conclusions and suggestions.
• Strategy Integration: Insights drive operations, product, sales actions.

Participating Roles

• Data Analysis & BI Teams: Build profiling models, analysis tools.
• Customer Success/Operations: View customer insights, develop strategies.
• Marketing: Target audience positioning, campaign planning.
• Product Team: Optimize products based on feedback.
• Management: Assess customer structure and health.

Primary Scenario User Story

As a data analyst, I want to consolidate customer profiles and generate insight reports, so that I can help business develop precise strategies.

Sub-scenario Details

Sub-scenario A: Customer Profile Synthesis

• Roles & Triggers: Need to build 360° customer view.
• Main Process:
  1. Integrate social data, CRM data, orders, service, feedback.
  2. Perform identity resolution and master data merging to generate unique customer profiles.
  3. Calculate key metrics (value, activity, satisfaction, channel preference).
  4. Publish profiles to SCRM, CRM, BI.
• Success Criteria: Complete, accurate profiles; real-time updatable; secure permissions.
• Exceptions & Risk Control: Matching conflicts require manual confirmation; sensitive fields redacted; sync failure alerts.
• Metric Suggestions: Profile coverage, accuracy, update latency.

Sub-scenario B: Behavioral Path & Preference Analysis

• Roles & Triggers: Analyze customer behaviors in social contexts.
• Main Process:
  1. Construct behavior paths (join community → interact with content → place order).
  2. Analyze preferences (content types, time slots, channels).
  3. Identify conversion bottlenecks and opportunity points.
  4. Output suggestions (optimize content, adjust timing, improve products).
• Success Criteria: Accurate insights; business guidance value; timely updates.
• Exceptions & Risk Control: Complete missing data; avoid discriminatory labels in preference analysis; retain model versions.
• Metric Suggestions: Insight adoption rate, strategy conversion improvement, update frequency.

Sub-scenario C: High-value & Risk Customer Identification

• Roles & Triggers: Identify VIPs and churn risks.
• Main Process:
  1. Build scoring based on RFM, lifecycle, feedback.
  2. Output VIP, potential, and risk customer lists.
  3. Push to CS and sales for corresponding strategy execution.
  4. Track strategy effectiveness and update scoring thresholds.
• Success Criteria: Accurate lists; timely responses; value improvement.
• Exceptions & Risk Control: Prompt calibration when scoring deviates; list usage requires compliance; retain historical versions.
• Metric Suggestions: Identification accuracy, strategy response rate, value contribution.

Sub-scenario D: Insight Reports & Knowledge Retention

• Roles & Triggers: Regularly output insight reports.
• Main Process:
  1. Auto-generate thematic reports (new customer insights, activity trends, risk alerts).
  2. Update models and suggestions based on business feedback.
  3. Publish to knowledge base and communication groups.
  4. Record suggestion adoption and effects.
• Success Criteria: Actionable reports; effective dissemination; continuous optimization.
• Exceptions & Risk Control: Sensitive content requires de-identification; report permission control; retain versions.
• Metric Suggestions: Report read rate, suggestion adoption rate, effect improvement.

Scenario-level Test Case Examples

Test Preparation: Build profile datasets, behavior log warehouses, scoring models, report templates, permission systems.

Test Case A-1: Profile Synthesis Accuracy (Positive)

• Prerequisites: Same customer has records in multiple systems.
• Steps:
  1. Run profile synthesis process.
  2. Check customer profiles.
• Expected Results:
  • Data sources successfully merged into unified profiles.
  • Key metrics displayed correctly with drill-down support.
  • Synced to SCRM and CRM.

Test Case B-1: Risk Customer Alert Verification (Negative)

• Prerequisites: Simulate customer with no interaction for 30 days and low NPS.
• Steps:
  1. Run scoring model.
  2. View risk lists and notifications.
• Expected Results:
  • Customer marked as "high-risk," pushed to CS.
  • Report explains reasons and provides suggestions.
  • If CS provides no feedback, system escalates after 48 hours.

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