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BoxHero: Inventory Management

BoxHero: Inventory Management

BGPworks

Business免费v3.47.0
App Store
评分

4.5

154 条评分

星级

★★★★☆

最近更新

2026年5月11日

发布日期

2019年5月23日

更新内容

v3.47.0

• You can now select a currency for each order. • Change your team's default currency and decimal places anytime from Settings. • Bug fixes and stability improvements.

应用信息

开发者
BGPworks
分类
Business
价格
免费
版本
3.47.0
App ID
1325512157

简介

BoxHero makes inventory management simple.
 Track stock, scan barcodes, and keep everything organized from your iPhone or iPad. Update inventory in real time, reduce errors, and manage multiple locations with ease. Whether you're running a retail shop, warehouse, or online store, BoxHero helps you stay on top of your inventory so you can focus on growing your business. BoxHero Features: * Real-time inventory tracking for instant updates * Custom attributes and photos for each item * Barcode scanning with your phone's camera for quick item lookup and stock adjustments * Custom barcode label printing, compatible with any printer * Multi-device access with cloud sync across mobile, tablet, and desktop * Low stock alerts to notify you when items need restocking * Team collaboration with role-based access controls * Easy Excel import and export for data transitions * Multiple location management for warehouses, retail stores, and office branches Get started in minutes. 1. Download BoxHero and create an account. 2. Add your inventory manually or upload an Excel file. 3. Start tracking stock with barcode scanning and real-time updates. Join thousands of businesses worldwide using BoxHero to simplify inventory management. Download now! Need help or have questions? * Support: support@boxhero.io * BoxHero Official: https://www.boxhero.io * BoxHero User Guide: https://docs-en.boxhero.io * Terms of Service: https://www.boxhero.io/en/tos * Privacy: https://www.boxhero.io/en/privacy

下载量预测

专业 · 预览

预估总下载量

21K15K31K
保守估计乐观估计

181

低 / 月

242

预估 / 月

362

高 / 月

基于154 条评分
假设评分率0.8%
应用年龄85 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。