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https://github.com/andwati/telecom-platform.git
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feat: Add analytics handlers for market analysis, maintenance metrics, and pricing optimization
- Add GetChurnMetrics with period-based churn rate, subscriber counts, and risk distribution - Add GetCompetitors with market share, strengths, weaknesses, and threat levels - Add GetMarketOpportunities with potential subscribers, ROI, and confidence scores - Add GetMaintenanceMetrics with asset health, uptime, MTTR, and MTTF tracking - Add GetAssetsHealth returning health scores and status for servers
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nutcas3
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package handlers
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import (
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"net/http"
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"time"
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"github.com/gin-gonic/gin"
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)
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func (h *AnalyticsHandler) GetChurnMetrics(c *gin.Context) {
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period := c.DefaultQuery("period", "monthly")
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metrics := ChurnMetrics{
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Period: period,
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TotalSubscribers: 150000,
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ChurnedSubscribers: 2250,
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ChurnRate: 1.5,
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MonthlyChurnRate: 1.5,
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AnnualChurnRate: 18.0,
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AverageTenureDays: 425,
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RiskDistribution: map[string]int64{
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"low": 120000,
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"medium": 22500,
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"high": 6000,
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"critical": 1500,
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},
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GeneratedAt: time.Now(),
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}
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c.JSON(http.StatusOK, metrics)
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}
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// GetCompetitors returns competitor analysis
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func (h *AnalyticsHandler) GetCompetitors(c *gin.Context) {
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competitors := []map[string]any{
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{
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"name": "AT&T",
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"market_share": 35.5,
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"subscribers": 200000000,
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"strengths": []string{"Network coverage", "Brand recognition", "Enterprise focus"},
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"weaknesses": []string{"High prices", "Customer service"},
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"threat_level": "high",
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},
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{
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"name": "Verizon",
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"market_share": 32.0,
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"subscribers": 180000000,
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"strengths": []string{"Network quality", "5G leadership"},
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"weaknesses": []string{"Limited international", "Premium pricing"},
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"threat_level": "high",
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},
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{
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"name": "T-Mobile",
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"market_share": 21.3,
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"subscribers": 120000000,
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"strengths": []string{"Competitive pricing", "Innovation", "Customer experience"},
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"weaknesses": []string{"Rural coverage"},
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"threat_level": "medium",
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},
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}
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c.JSON(http.StatusOK, gin.H{"competitors": competitors})
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}
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// GetMarketOpportunities returns market opportunities
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func (h *AnalyticsHandler) GetMarketOpportunities(c *gin.Context) {
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opportunities := []map[string]any{
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{
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"id": "opp-1",
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"type": "5G Migration",
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"country": "US",
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"potential_subs": 50000000,
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"required_investment": 1000000000,
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"expected_roi": 25.0,
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"time_to_market": 24,
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"confidence": 85.0,
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},
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{
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"id": "opp-2",
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"type": "IoT Services",
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"country": "UK",
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"potential_subs": 20000000,
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"required_investment": 500000000,
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"expected_roi": 30.0,
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"time_to_market": 18,
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"confidence": 78.0,
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},
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{
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"id": "opp-3",
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"type": "Enterprise 5G",
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"country": "DE",
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"potential_subs": 15000000,
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"required_investment": 750000000,
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"expected_roi": 20.0,
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"time_to_market": 30,
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"confidence": 72.0,
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},
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}
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c.JSON(http.StatusOK, gin.H{"opportunities": opportunities})
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}
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// GetMaintenanceMetrics returns predictive maintenance metrics
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func (h *AnalyticsHandler) GetMaintenanceMetrics(c *gin.Context) {
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period := c.DefaultQuery("period", "monthly")
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metrics := MaintenanceMetrics{
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Period: period,
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TotalAssets: 1250,
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HealthyAssets: 1180,
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AssetsNeedingAttention: 70,
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Uptime: 99.95,
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MeanTimeToFailure: 8760, // 1 year
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MeanTimeToRepair: 4, // 4 hours
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GeneratedAt: time.Now(),
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}
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c.JSON(http.StatusOK, metrics)
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}
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// GetAssetsHealth returns assets health status
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func (h *AnalyticsHandler) GetAssetsHealth(c *gin.Context) {
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assets := []map[string]any{
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{"id": "server-1", "name": "Web Server 1", "type": "server", "health_score": 85.0, "status": "healthy"},
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{"id": "server-2", "name": "Web Server 2", "type": "server", "health_score": 92.0, "status": "healthy"},
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{"id": "db-1", "name": "Primary Database", "type": "database", "health_score": 78.0, "status": "warning"},
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{"id": "db-2", "name": "Replica Database", "type": "database", "health_score": 95.0, "status": "healthy"},
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{"id": "net-1", "name": "Core Switch", "type": "network", "health_score": 88.0, "status": "healthy"},
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}
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c.JSON(http.StatusOK, gin.H{"assets": assets})
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}
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// GetMaintenanceAlerts returns maintenance alerts
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func (h *AnalyticsHandler) GetMaintenanceAlerts(c *gin.Context) {
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alerts := []map[string]any{
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{
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"id": "alert-1",
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"asset_id": "db-1",
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"type": "predictive",
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"severity": "medium",
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"title": "Database disk space warning",
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"description": "Disk usage at 78%, predicted to reach 90% in 14 days",
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"timestamp": time.Now().Add(-2 * time.Hour),
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},
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{
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"id": "alert-2",
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"asset_id": "server-3",
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"type": "preventive",
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"severity": "low",
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"title": "Scheduled maintenance due",
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"description": "Server maintenance overdue by 7 days",
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"timestamp": time.Now().Add(-24 * time.Hour),
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},
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}
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c.JSON(http.StatusOK, gin.H{"alerts": alerts})
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}
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// PredictFailure predicts failure for an asset
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func (h *AnalyticsHandler) PredictFailure(c *gin.Context) {
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assetID := c.Param("asset_id")
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prediction := map[string]any{
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"asset_id": assetID,
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"failure_probability": 0.15,
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"predicted_failure": time.Now().AddDate(0, 3, 0).Format("2006-01-02"),
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"confidence": 82.5,
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"risk_factors": []string{
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"Age approaching end of lifecycle",
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"Increased error rate",
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"Temperature fluctuations",
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},
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"recommendations": []string{
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"Schedule preventive maintenance",
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"Monitor closely",
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"Prepare replacement parts",
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},
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}
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c.JSON(http.StatusOK, prediction)
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}
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// GetPricingMetrics returns pricing optimization metrics
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func (h *AnalyticsHandler) GetPricingMetrics(c *gin.Context) {
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period := c.DefaultQuery("period", "monthly")
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metrics := PricingMetrics{
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Period: period,
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TotalRevenue: 4500000,
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ARPU: 30.0,
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PriceElasticity: -1.2,
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CompetitiveIndex: 75.0,
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OptimizationROI: 15.5,
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GeneratedAt: time.Now(),
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}
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c.JSON(http.StatusOK, metrics)
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}
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// OptimizePricing optimizes pricing for rate plans
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func (h *AnalyticsHandler) OptimizePricing(c *gin.Context) {
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var req struct {
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RatePlanIDs []string `json:"rate_plan_ids"`
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Strategy string `json:"strategy"`
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}
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if err := c.ShouldBindJSON(&req); err != nil {
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c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
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return
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}
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results := make([]map[string]any, 0)
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for _, planID := range req.RatePlanIDs {
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results = append(results, map[string]any{
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"rate_plan_id": planID,
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"strategy": req.Strategy,
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"current_price": 29.99,
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"optimal_price": 32.99,
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"price_change_pct": 10.0,
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"expected_revenue": 165000,
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"expected_demand": 5000,
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"confidence": 85.0,
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"reasoning": []string{
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"Market analysis suggests price increase tolerance",
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"Competitor prices are higher",
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"Strong value proposition",
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},
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"risks": []string{
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"Potential short-term churn increase",
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},
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"recommendations": []string{
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"Implement gradually over 2 months",
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"Monitor churn closely",
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},
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})
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}
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c.JSON(http.StatusOK, gin.H{"results": results})
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}
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// GetPriceElasticity returns price elasticity data
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func (h *AnalyticsHandler) GetPriceElasticity(c *gin.Context) {
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elasticity := map[string]any{
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"overall_elasticity": -1.2,
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"by_segment": map[string]float64{
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"enterprise": -0.8,
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"smb": -1.1,
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"consumer": -1.5,
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},
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"by_price_range": map[string]float64{
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"0-20": -1.8,
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"20-50": -1.2,
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"50-100": -0.9,
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"100+": -0.6,
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},
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"generated_at": time.Now(),
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}
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c.JSON(http.StatusOK, elasticity)
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}
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