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FishingBooker Charters & Trips

FishingBooker Charters & Trips

FishingBooker, Inc

Travel免费v1.50.3
App Store
评分

4.9

4,675 条评分

星级

★★★★★

最近更新

2026年5月11日

发布日期

2022年3月24日

更新内容

v1.50.3

We’ve made a few small improvements to keep things running smoothly: - Resolved a few minor bugs - Made general performance and stability updates There aren’t any visible changes this time, but these updates help keep everything working smoothly behind the scenes. Thanks for keeping your app up to date.

应用信息

开发者
FishingBooker, Inc
分类
Travel
价格
免费
版本
1.50.3
App ID
1511475315

简介

FishingBooker is the world's largest online platform for booking fishing trips. Whether you're planning a local outing or an international expedition, our app connects you with thousands of verified captains and charters worldwide. Fishing Trips Worldwide Book guided fishing trips in 2,000+ destinations. Whether you're staying close to home or heading somewhere new, find a fishing experience that fits your schedule, location, and style. Verified Reviews See what 3.4 million+ anglers are saying to help you find your perfect fishing trip. Direct Communication Message your captain directly to customize your trip and get real-time answers to your questions. Seamless Booking Book your next fishing trip from start to finish, right in the app. Browse trips, message captains, and lock in your booking – it’s quick, easy, and secure. Real-Time Catches Feed Explore recent catches from the FishingBooker community to inspire your next trip. Loyalty Rewards Complete a trip and you’ll join our Loyalty Program, unlocking tiered discounts of up to 20%. The more you fish, the more you save! Why Choose FishingBooker? We make it easy to find, compare, and book fishing trips – whether you're new to fishing or a seasoned pro. Booking your trip is fast, easy, and secure, so you can focus on what it’s really about: getting out on the water.

下载量预测

专业 · 预览

预估总下载量

346K234K668K
保守估计乐观估计

5K

低 / 月

7K

预估 / 月

13K

高 / 月

基于4,675 条评分
假设评分率1.4%
应用年龄50 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。