package radio import ( "sundynix-go/global" "sundynix-go/model/radio/response" "time" ) type AnalyticsService struct{} // parseDateRange 解析日期范围,未传则默认最近30天 func parseDateRange(startDate, endDate string) (time.Time, time.Time) { now := time.Now() layout := "2006-01-02" end, err := time.ParseInLocation(layout, endDate, now.Location()) if err != nil { end = now } // 结束日期取当天 23:59:59 end = time.Date(end.Year(), end.Month(), end.Day(), 23, 59, 59, 0, end.Location()) start, err := time.ParseInLocation(layout, startDate, now.Location()) if err != nil { start = end.AddDate(0, 0, -29) // 默认30天 } // 开始日期取当天 00:00:00 start = time.Date(start.Year(), start.Month(), start.Day(), 0, 0, 0, 0, start.Location()) return start, end } // GetListeningTrend 获取收听趋势 (使用持久化的 ListenLog) func (s *AnalyticsService) GetListeningTrend(startDate, endDate, channelId string) (response.ListeningTrendResponse, error) { var resp response.ListeningTrendResponse start, end := parseDateRange(startDate, endDate) db := global.DB.Table("sundynix_radio_listen_log") if channelId != "" { db = db.Where("channel_id = ?", channelId) } // 按天聚合收听次数 (即便用户删除了 history,日志依然存在) err := db.Select("DATE(created_at) AS date, COUNT(*) AS count"). Where("created_at BETWEEN ? AND ?", start, end). Where("deleted_at IS NULL"). Group("DATE(created_at)"). Order("date ASC"). Scan(&resp.Trend).Error if err != nil { return resp, err } for _, p := range resp.Trend { resp.TotalCount += p.Count } return resp, nil } // GetSubscriptionTrend 获取新增订阅趋势 (使用永久 Order 记录) func (s *AnalyticsService) GetSubscriptionTrend(startDate, endDate, channelId string) (response.SubscriptionTrendResponse, error) { var resp response.SubscriptionTrendResponse start, end := parseDateRange(startDate, endDate) // 订阅趋势 = 首次购买该频道成功的订单 // 通过子查询找到每个 (user_id, channel_id) 的最小成功订单日期 subQuery := global.DB.Table("sundynix_order"). Select("MIN(updated_at) as first_pay"). Where("type = 1 AND status = 1 AND deleted_at IS NULL"). Group("user_id, channel_id") db := global.DB.Table("(?) as first_orders", subQuery). Where("first_pay BETWEEN ? AND ?", start, end) err := db.Select("DATE(first_pay) AS date, COUNT(*) AS count"). Group("DATE(first_pay)"). Order("date ASC"). Scan(&resp.Trend).Error if err != nil { return resp, err } for _, p := range resp.Trend { resp.TotalNewSubs += p.Count } return resp, nil } // GetRenewalTrend 获取续费趋势 (使用永久 Order 记录) func (s *AnalyticsService) GetRenewalTrend(startDate, endDate, channelId string) (response.RenewalTrendResponse, error) { var resp response.RenewalTrendResponse start, end := parseDateRange(startDate, endDate) // 续费 = 成功支付的订阅订单,且不是该用户对该频道的首笔订单 db := global.DB.Table("sundynix_order AS o"). Where("o.type = 1 AND o.status = 1 AND o.deleted_at IS NULL"). Where("o.updated_at BETWEEN ? AND ?", start, end). Where("EXISTS (SELECT 1 FROM sundynix_order AS o2 WHERE o2.user_id = o.user_id AND o2.channel_id = o.channel_id AND o2.updated_at < o.updated_at AND o2.status = 1)") if channelId != "" { db = db.Where("o.channel_id = ?", channelId) } err := db.Select("DATE(o.updated_at) AS date, COUNT(*) AS count"). Group("DATE(o.updated_at)"). Order("date ASC"). Scan(&resp.Trend).Error if err != nil { return resp, err } for _, p := range resp.Trend { resp.TotalRenewals += p.Count } return resp, nil } // GetSubscriberStats 获取订阅用户统计 (混合实时 Subscription 与历史 Order) func (s *AnalyticsService) GetSubscriberStats(startDate, endDate, channelId string) (response.SubscriberStatsResponse, error) { var resp response.SubscriberStatsResponse start, end := parseDateRange(startDate, endDate) now := time.Now() // 1. 当前有效订阅用户数 (实时表) activeQuery := global.DB.Table("sundynix_radio_subscription"). Where("deleted_at IS NULL AND status = 1 AND expired_at > ?", now) if channelId != "" { activeQuery = activeQuery.Where("channel_id = ?", channelId) } activeQuery.Select("COUNT(DISTINCT user_id)").Scan(&resp.ActiveSubscribers) // 2. 累积总订阅人数 (从历史 Order 表统计全量真实去重用户) totalUserQuery := global.DB.Table("sundynix_order"). Where("type = 1 AND status = 1 AND deleted_at IS NULL") if channelId != "" { totalUserQuery = totalUserQuery.Where("channel_id = ?", channelId) } totalUserQuery.Select("COUNT(DISTINCT user_id)").Scan(&resp.TotalSubscribers) // 3. 已流失/过期用户 = 历史总计 - 当前有效 resp.ExpiredSubscribers = resp.TotalSubscribers - resp.ActiveSubscribers if resp.ExpiredSubscribers < 0 { resp.ExpiredSubscribers = 0 } // 4. 每日新增转化用户趋势 (从 Order 表提取) trendQuery := global.DB.Table("sundynix_order"). Where("type = 1 AND status = 1 AND updated_at BETWEEN ? AND ? AND deleted_at IS NULL", start, end) if channelId != "" { trendQuery = trendQuery.Where("channel_id = ?", channelId) } err := trendQuery.Select("DATE(updated_at) AS date, COUNT(DISTINCT user_id) AS count"). Group("DATE(updated_at)"). Order("date ASC"). Scan(&resp.ActiveTrend).Error return resp, err } // GetContentQuality 内容质量分析:完播率 func (s *AnalyticsService) GetContentQuality(channelId string) ([]response.CompletionRateResponse, error) { var results []response.CompletionRateResponse // 使用更具韧性的 SQL 计算完播率: // 1. 优先使用 program 表中的 duration (得益于“贪婪学习”,它会越来越准) // 2. 如果 program.duration 为 0,则动态使用该节目在日志中的 MAX(progress) 作为推定时长 // 3. 过滤掉完全没有任何播放深度记录的异常数据 baseQuery := global.DB.Table("sundynix_radio_program AS p"). Select("p.id as program_id, p.title, " + "AVG(CAST(h.progress AS DECIMAL) / " + "NULLIF(COALESCE(NULLIF(p.duration, 0), (SELECT MAX(progress) FROM sundynix_radio_listen_log WHERE program_id = p.id)), 0)) as avg_completion, " + "COUNT(DISTINCT h.user_id) as play_count"). Joins("INNER JOIN sundynix_radio_history AS h ON h.program_id = p.id") if channelId != "" { baseQuery = baseQuery.Where("p.channel_id = ?", channelId) } err := baseQuery.Group("p.id, p.title"). Having("avg_completion >= 0"). Order("avg_completion DESC"). Limit(20). Scan(&results).Error return results, err } // GetUserStickiness 用户黏性分析:留存分析 (Cohort Analysis) func (s *AnalyticsService) GetUserStickiness(startDate, endDate string) ([]response.RetentionResponse, error) { var list []response.RetentionResponse start, end := parseDateRange(startDate, endDate) // 获取时间范围内的每日新增活跃用户 var dailyNewUsers []struct { Date string Count int64 } global.DB.Table("sundynix_radio_listen_log"). Select("DATE(created_at) as date, COUNT(DISTINCT user_id) as count"). Where("created_at BETWEEN ? AND ?", start, end). Group("DATE(created_at)"). Scan(&dailyNewUsers) for _, day := range dailyNewUsers { dayTime, _ := time.Parse("2006-01-02", day.Date) res := response.RetentionResponse{ Date: day.Date, NewUsers: day.Count, } // 计算 1, 3, 7, 30 天后的留存率 intervals := []int{1, 3, 7, 30} for _, dayDelta := range intervals { checkDayStart := dayTime.AddDate(0, 0, dayDelta) checkDayEnd := checkDayStart.AddDate(0, 0, 1) var retainedCount int64 // 统计在 day.Date 活跃过的用户中,有多少在 checkDay 再次出现了 global.DB.Table("sundynix_radio_listen_log"). Where("user_id IN (SELECT DISTINCT user_id FROM sundynix_radio_listen_log WHERE DATE(created_at) = ?)", day.Date). Where("created_at BETWEEN ? AND ?", checkDayStart, checkDayEnd). Distinct("user_id"). Count(&retainedCount) rate := 0.0 if day.Count > 0 { rate = float64(retainedCount) / float64(day.Count) } res.Retention = append(res.Retention, rate) } list = append(list, res) } return list, nil } // GetBusinessConversion 商业转化分析:漏斗与 LTV func (s *AnalyticsService) GetBusinessConversion(startDate, endDate string) (response.FunnelResponse, error) { var resp response.FunnelResponse start, end := parseDateRange(startDate, endDate) // 1. 活跃收听用户数 (Top of Funnel) global.DB.Table("sundynix_radio_listen_log"). Where("created_at BETWEEN ? AND ?", start, end). Distinct("user_id").Count(&resp.ListenUsers) // 2. 尝试下单用户数 (Middle of Funnel) - 只要创建过订单就算 global.DB.Table("sundynix_order"). Where("created_at BETWEEN ? AND ?", start, end). Distinct("user_id").Count(&resp.OrderUsers) // 3. 支付成功用户数 (Bottom of Funnel) global.DB.Table("sundynix_order"). Where("updated_at BETWEEN ? AND ? AND status = 1", start, end). Distinct("user_id").Count(&resp.PayUsers) // 4. LTV 计算 (活跃期内总营收 / 总活跃用户数) var totalRevenue int64 global.DB.Table("sundynix_order"). Where("updated_at BETWEEN ? AND ? AND status = 1", start, end). Select("SUM(amount)").Scan(&totalRevenue) if resp.ListenUsers > 0 { resp.LTV = float64(totalRevenue) / float64(resp.ListenUsers) } return resp, nil } // GetPreferenceAnalysis 品类偏好分析 func (s *AnalyticsService) GetPreferenceAnalysis() (response.PreferenceAnalysisResponse, error) { var resp response.PreferenceAnalysisResponse var totalRevenue int64 // 获取总营收用于计算占比 global.DB.Table("sundynix_order").Where("status = 1").Select("SUM(amount)").Scan(&totalRevenue) // 按分类聚合播放量与营收 err := global.DB.Table("sundynix_radio_category AS cat"). Select("cat.id as category_id, cat.name as category_name, " + "COUNT(DISTINCT l.id) as listen_count, " + "COALESCE(SUM(DISTINCT o.amount), 0) as revenue"). Joins("LEFT JOIN sundynix_radio_channel AS ch ON ch.category_id = cat.id"). Joins("LEFT JOIN sundynix_radio_listen_log AS l ON l.channel_id = ch.id"). Joins("LEFT JOIN sundynix_order AS o ON o.channel_id = ch.id AND o.status = 1"). Group("cat.id, cat.name"). Order("revenue DESC"). Scan(&resp.List).Error if totalRevenue > 0 { for i := range resp.List { resp.List[i].Share = float64(resp.List[i].Revenue) / float64(totalRevenue) } } return resp, err }