wurenzhi
b31591e04c
refactor: 优化服务层代码并修复类型问题 docs: 更新开发进度文档 feat(merchant): 新增商户监控与数据统计服务 feat(dashboard): 添加商户管理前端页面与服务 fix: 修复类型转换与可选参数处理 feat: 实现商户订单、店铺与结算管理功能 refactor: 重构审计日志格式与服务调用 feat: 新增商户入驻与身份注册功能 fix(controller): 修复路由参数类型问题 feat: 添加商户排名与统计报告功能 chore: 更新模拟数据与服务配置
403 lines
12 KiB
TypeScript
403 lines
12 KiB
TypeScript
import { Injectable, Logger } from '@nestjs/common';
|
||
import { Merchant, Order, Settlement } from '@prisma/client';
|
||
import { PrismaService } from '../../config/database';
|
||
|
||
interface MerchantBehaviorData {
|
||
merchantId: string;
|
||
orderCount: number;
|
||
totalSales: number;
|
||
averageOrderValue: number;
|
||
orderFrequency: number; // 日均订单数
|
||
refundRate: number;
|
||
activeDays: number; // 活跃天数
|
||
lastOrderDate: Date;
|
||
createdAt: Date;
|
||
}
|
||
|
||
interface BehaviorPredictionResult {
|
||
merchantId: string;
|
||
predictions: {
|
||
futureSales: number; // 预测未来30天销售额
|
||
orderTrend: 'increasing' | 'stable' | 'decreasing'; // 订单趋势
|
||
churnRisk: 'low' | 'medium' | 'high'; // 流失风险
|
||
growthPotential: 'high' | 'medium' | 'low'; // 增长潜力
|
||
};
|
||
confidence: number; // 预测置信度
|
||
factors: {
|
||
historicalTrend: number;
|
||
recentActivity: number;
|
||
customerRetention: number;
|
||
marketSeasonality: number;
|
||
};
|
||
recommendations: string[];
|
||
}
|
||
|
||
@Injectable()
|
||
export class MerchantPredictionService {
|
||
private readonly logger = new Logger(MerchantPredictionService.name);
|
||
|
||
constructor(private readonly prisma: PrismaService) {}
|
||
|
||
/**
|
||
* 预测商户行为
|
||
* @param merchantId 商户ID
|
||
* @param traceId 链路追踪ID
|
||
* @returns 商户行为预测结果
|
||
*/
|
||
async predictMerchantBehavior(merchantId: string, traceId: string): Promise<BehaviorPredictionResult> {
|
||
this.logger.log(`开始预测商户行为: ${merchantId}`, { traceId, merchantId });
|
||
|
||
try {
|
||
// 获取商户历史行为数据
|
||
const behaviorData = await this.getMerchantBehaviorData(merchantId);
|
||
|
||
// 分析历史趋势
|
||
const historicalTrend = this.analyzeHistoricalTrend(merchantId);
|
||
|
||
// 分析最近活动
|
||
const recentActivity = this.analyzeRecentActivity(behaviorData);
|
||
|
||
// 分析客户留存
|
||
const customerRetention = this.analyzeCustomerRetention(merchantId);
|
||
|
||
// 分析市场季节性
|
||
const marketSeasonality = this.analyzeMarketSeasonality();
|
||
|
||
const factors = {
|
||
historicalTrend,
|
||
recentActivity,
|
||
customerRetention,
|
||
marketSeasonality,
|
||
};
|
||
|
||
// 预测未来销售额
|
||
const futureSales = this.predictFutureSales(behaviorData, factors);
|
||
|
||
// 预测订单趋势
|
||
const orderTrend = this.predictOrderTrend(historicalTrend, recentActivity);
|
||
|
||
// 预测流失风险
|
||
const churnRisk = this.predictChurnRisk(behaviorData, recentActivity);
|
||
|
||
// 评估增长潜力
|
||
const growthPotential = this.assessGrowthPotential(factors);
|
||
|
||
// 计算预测置信度
|
||
const confidence = this.calculateConfidence(factors);
|
||
|
||
// 生成建议
|
||
const recommendations = this.generateRecommendations({
|
||
...behaviorData,
|
||
...factors,
|
||
predictions: {
|
||
futureSales,
|
||
orderTrend,
|
||
churnRisk,
|
||
growthPotential,
|
||
},
|
||
});
|
||
|
||
const result: BehaviorPredictionResult = {
|
||
merchantId,
|
||
predictions: {
|
||
futureSales,
|
||
orderTrend,
|
||
churnRisk,
|
||
growthPotential,
|
||
},
|
||
confidence,
|
||
factors,
|
||
recommendations,
|
||
};
|
||
|
||
this.logger.log(`商户行为预测完成: ${merchantId}`, { traceId, result });
|
||
|
||
return result;
|
||
} catch (error) {
|
||
this.logger.error(`商户行为预测失败: ${error.message}`, { traceId, merchantId, error });
|
||
throw error;
|
||
}
|
||
}
|
||
|
||
/**
|
||
* 批量预测商户行为
|
||
* @param merchantIds 商户ID列表
|
||
* @param traceId 链路追踪ID
|
||
* @returns 商户行为预测结果列表
|
||
*/
|
||
async batchPredictMerchantBehavior(merchantIds: string[], traceId: string): Promise<BehaviorPredictionResult[]> {
|
||
this.logger.log(`开始批量预测商户行为, 数量: ${merchantIds.length}`, { traceId });
|
||
|
||
const results: BehaviorPredictionResult[] = [];
|
||
|
||
for (const merchantId of merchantIds) {
|
||
try {
|
||
const result = await this.predictMerchantBehavior(merchantId, traceId);
|
||
results.push(result);
|
||
} catch (error) {
|
||
this.logger.error(`批量预测商户行为失败: ${merchantId}, 错误: ${error.message}`, { traceId, merchantId });
|
||
}
|
||
}
|
||
|
||
this.logger.log(`批量预测商户行为完成, 成功: ${results.length}/${merchantIds.length}`, { traceId });
|
||
|
||
return results;
|
||
}
|
||
|
||
/**
|
||
* 获取商户行为数据
|
||
*/
|
||
private async getMerchantBehaviorData(merchantId: string): Promise<MerchantBehaviorData> {
|
||
// 获取商户基本信息
|
||
const merchant = await this.prisma.merchant.findUnique({
|
||
where: { id: merchantId },
|
||
});
|
||
|
||
if (!merchant) {
|
||
throw new Error(`商户不存在: ${merchantId}`);
|
||
}
|
||
|
||
// 获取商户订单数据
|
||
const orders = await this.prisma.order.findMany({
|
||
where: { merchantId },
|
||
select: {
|
||
id: true,
|
||
totalAmount: true,
|
||
status: true,
|
||
createdAt: true,
|
||
},
|
||
});
|
||
|
||
// 计算基本统计数据
|
||
const orderCount = orders.length;
|
||
const totalSales = orders.reduce((sum, order) => sum + order.totalAmount, 0);
|
||
const averageOrderValue = orderCount > 0 ? totalSales / orderCount : 0;
|
||
|
||
// 计算活跃天数
|
||
const activeDays = new Set(orders.map(order => order.createdAt.toISOString().split('T')[0])).size;
|
||
|
||
// 计算日均订单数
|
||
const daysSinceCreation = merchant.createdAt ?
|
||
Math.max(1, Math.floor((new Date().getTime() - merchant.createdAt.getTime()) / (1000 * 60 * 60 * 24))) : 1;
|
||
const orderFrequency = orderCount / daysSinceCreation;
|
||
|
||
// 计算退款率
|
||
const refundedOrders = orders.filter(order => order.status === 'REFUNDED').length;
|
||
const refundRate = orderCount > 0 ? refundedOrders / orderCount : 0;
|
||
|
||
// 获取最后订单日期
|
||
const lastOrder = orders.sort((a, b) => b.createdAt.getTime() - a.createdAt.getTime())[0];
|
||
const lastOrderDate = lastOrder ? lastOrder.createdAt : merchant.createdAt;
|
||
|
||
return {
|
||
merchantId,
|
||
orderCount,
|
||
totalSales,
|
||
averageOrderValue,
|
||
orderFrequency,
|
||
refundRate,
|
||
activeDays,
|
||
lastOrderDate,
|
||
createdAt: merchant.createdAt,
|
||
};
|
||
}
|
||
|
||
/**
|
||
* 分析历史趋势
|
||
*/
|
||
private async analyzeHistoricalTrend(merchantId: string): Promise<number> {
|
||
// 这里可以实现更复杂的趋势分析逻辑
|
||
// 例如：分析过去3个月的订单增长趋势
|
||
return Math.random() * 0.5 + 0.5; // 模拟趋势值 (0.5-1.0)
|
||
}
|
||
|
||
/**
|
||
* 分析最近活动
|
||
*/
|
||
private analyzeRecentActivity(behaviorData: MerchantBehaviorData): number {
|
||
// 计算最近30天的活跃程度
|
||
const thirtyDaysAgo = new Date();
|
||
thirtyDaysAgo.setDate(thirtyDaysAgo.getDate() - 30);
|
||
|
||
const daysSinceLastOrder = Math.floor((new Date().getTime() - behaviorData.lastOrderDate.getTime()) / (1000 * 60 * 60 * 24));
|
||
const recentActivity = Math.max(0, 1 - (daysSinceLastOrder / 30));
|
||
|
||
return recentActivity;
|
||
}
|
||
|
||
/**
|
||
* 分析客户留存
|
||
*/
|
||
private async analyzeCustomerRetention(merchantId: string): Promise<number> {
|
||
// 这里可以实现更复杂的客户留存分析逻辑
|
||
// 例如：分析重复购买率
|
||
return Math.random() * 0.3 + 0.7; // 模拟留存率 (0.7-1.0)
|
||
}
|
||
|
||
/**
|
||
* 分析市场季节性
|
||
*/
|
||
private analyzeMarketSeasonality(): number {
|
||
// 这里可以实现更复杂的季节性分析逻辑
|
||
// 例如：根据当前月份分析季节性因素
|
||
const month = new Date().getMonth() + 1;
|
||
// 假设Q4是销售旺季
|
||
if (month >= 10 || month <= 2) {
|
||
return 1.2; // 旺季
|
||
} else if (month >= 3 && month <= 5) {
|
||
return 0.9; // 淡季
|
||
} else {
|
||
return 1.0; // 正常
|
||
}
|
||
}
|
||
|
||
/**
|
||
* 预测未来销售额
|
||
*/
|
||
private predictFutureSales(behaviorData: MerchantBehaviorData, factors: any): number {
|
||
// 基于历史数据和因素预测未来30天销售额
|
||
const dailySales = behaviorData.totalSales / Math.max(1, behaviorData.activeDays);
|
||
const basePrediction = dailySales * 30;
|
||
|
||
// 应用各种因素的影响
|
||
const adjustedPrediction = basePrediction *
|
||
(1 + (factors.historicalTrend - 0.5) * 0.3) *
|
||
(1 + (factors.recentActivity - 0.5) * 0.2) *
|
||
factors.marketSeasonality;
|
||
|
||
return Math.max(0, Math.round(adjustedPrediction));
|
||
}
|
||
|
||
/**
|
||
* 预测订单趋势
|
||
*/
|
||
private predictOrderTrend(historicalTrend: number, recentActivity: number): 'increasing' | 'stable' | 'decreasing' {
|
||
const combinedScore = (historicalTrend + recentActivity) / 2;
|
||
|
||
if (combinedScore > 0.7) {
|
||
return 'increasing';
|
||
} else if (combinedScore > 0.4) {
|
||
return 'stable';
|
||
} else {
|
||
return 'decreasing';
|
||
}
|
||
}
|
||
|
||
/**
|
||
* 预测流失风险
|
||
*/
|
||
private predictChurnRisk(behaviorData: MerchantBehaviorData, recentActivity: number): 'low' | 'medium' | 'high' {
|
||
const daysSinceLastOrder = Math.floor((new Date().getTime() - behaviorData.lastOrderDate.getTime()) / (1000 * 60 * 60 * 24));
|
||
const activityScore = recentActivity;
|
||
|
||
if (daysSinceLastOrder > 60 || activityScore < 0.3) {
|
||
return 'high';
|
||
} else if (daysSinceLastOrder > 30 || activityScore < 0.6) {
|
||
return 'medium';
|
||
} else {
|
||
return 'low';
|
||
}
|
||
}
|
||
|
||
/**
|
||
* 评估增长潜力
|
||
*/
|
||
private assessGrowthPotential(factors: any): 'high' | 'medium' | 'low' {
|
||
const combinedScore = (factors.historicalTrend + factors.customerRetention) / 2;
|
||
|
||
if (combinedScore > 0.8) {
|
||
return 'high';
|
||
} else if (combinedScore > 0.6) {
|
||
return 'medium';
|
||
} else {
|
||
return 'low';
|
||
}
|
||
}
|
||
|
||
/**
|
||
* 计算预测置信度
|
||
*/
|
||
private calculateConfidence(factors: any): number {
|
||
// 基于数据完整性和因素稳定性计算置信度
|
||
const dataCompleteness = 0.9; // 假设数据完整性较好
|
||
const factorConsistency = (factors.historicalTrend + factors.recentActivity + factors.customerRetention) / 3;
|
||
|
||
const confidence = dataCompleteness * factorConsistency;
|
||
return Math.round(confidence * 100);
|
||
}
|
||
|
||
/**
|
||
* 生成建议
|
||
*/
|
||
private generateRecommendations(data: any): string[] {
|
||
const recommendations: string[] = [];
|
||
|
||
if (data.predictions.churnRisk === 'high') {
|
||
recommendations.push('建议主动联系商户，了解经营情况并提供支持');
|
||
}
|
||
|
||
if (data.predictions.orderTrend === 'decreasing') {
|
||
recommendations.push('建议优化产品展示和营销策略，提升订单量');
|
||
}
|
||
|
||
if (data.predictions.growthPotential === 'high') {
|
||
recommendations.push('建议为商户提供高级功能和增值服务，支持其业务增长');
|
||
}
|
||
|
||
if (data.refundRate > 0.1) {
|
||
recommendations.push('建议帮助商户优化产品质量和客户服务，降低退款率');
|
||
}
|
||
|
||
if (data.averageOrderValue < 100) {
|
||
recommendations.push('建议引导商户增加高价值产品或实施捆绑销售策略');
|
||
}
|
||
|
||
return recommendations.length > 0 ? recommendations : ['商户经营状况稳定，继续保持'];
|
||
}
|
||
|
||
/**
|
||
* 获取高风险商户列表
|
||
* @param limit 返回数量
|
||
* @param traceId 链路追踪ID
|
||
* @returns 高风险商户列表
|
||
*/
|
||
async getHighRiskMerchants(limit: number = 10, traceId: string): Promise<Array<{ merchantId: string; companyName: string; riskLevel: string; reason: string }>> {
|
||
this.logger.log(`获取高风险商户列表, 限制: ${limit}`, { traceId });
|
||
|
||
try {
|
||
// 获取所有活跃商户
|
||
const merchants = await this.prisma.merchant.findMany({
|
||
where: { status: 'ACTIVE' },
|
||
select: {
|
||
id: true,
|
||
companyName: true,
|
||
},
|
||
});
|
||
|
||
const merchantIds = merchants.map(m => m.id);
|
||
const predictions = await this.batchPredictMerchantBehavior(merchantIds, traceId);
|
||
|
||
// 筛选高风险商户
|
||
const highRiskMerchants = predictions
|
||
.filter(p => p.predictions.churnRisk === 'high')
|
||
.map(prediction => {
|
||
const merchant = merchants.find(m => m.id === prediction.merchantId);
|
||
return {
|
||
merchantId: prediction.merchantId,
|
||
companyName: merchant?.companyName || '未知商户',
|
||
riskLevel: prediction.predictions.churnRisk,
|
||
reason: prediction.recommendations[0] || '商户活动度低，存在流失风险',
|
||
};
|
||
})
|
||
.slice(0, limit);
|
||
|
||
this.logger.log(`获取高风险商户列表完成, 数量: ${highRiskMerchants.length}`, { traceId });
|
||
|
||
return highRiskMerchants;
|
||
} catch (error) {
|
||
this.logger.error(`获取高风险商户列表失败: ${error.message}`, { traceId, error });
|
||
throw error;
|
||
}
|
||
}
|
||
}
|