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AI-Driven E-commerce App Blueprint Rahul John
예산
$250~$750 USD
예상 기간
3~4주
난이도
전문가
기술 스택
Mobile App Development
iOS Development
Android Development
AI/ML
Machine Learning
Deep Learning
Cloud Computing (AWS/GCP/Azure)
Backend Development
Database Design
System Architecture
UI/UX Design
Wireframing
Project Management
E-commerce Strategy
Payment Gateway Integration
Mobile Analytics Tools
Figma
Miro
AI 분석 요약
이 프로젝트는 iOS 및 Android용 AI 기반 전자상거래 모바일 앱 구축을 위한 상세한 설계도(블루프린트)를 개발하는 것입니다. 핵심 기능 정의, AI 통합 방안, 기술 스택 추천, 와이어프레임, 개발 타임라인 및 KPI를 포함해야 하며, 전자상거래 전략, 모바일 앱 아키텍처, AI/ML 통합 및 프로젝트 관리 역량이 필요합니다.
프로젝트 원문 설명
I need a clear, actionable blueprint for building a sales-focused e-commerce mobile app that will launch on both iOS and Android. The document should guide my in-house team from concept to store release, showing exactly how we can weave AI into the user journey to boost conversions and lifetime value.
Scope
• Define the core feature set: catalogue, smart search, personalised product feeds, in-app marketing tools, cart, checkout, order tracking and an admin dashboard.
• Map AI touchpoints such as image-based product recognition, dynamic pricing, recommendation engines and automated customer-service chat.
• Recommend the full tech stack: mobile frameworks (e.g. Flutter, React Native or native), backend, database, AI/ML services (TensorFlow Lite, Core ML, Amazon Personalize, etc.) and third-party APIs for payments, shipping and analytics.
• Lay out an annotated wireframe or low-fidelity screen flow that illustrates how users move from discovery to purchase.
• Provide a phased development timeline broken into logical sprints with expected deliverables, QA tasks and app-store submission steps.
• Include KPIs tied to sales and marketing goals—conversion rate, average order value, retention—and explain how in-app data will feed the AI models.
Acceptance criteria
1. A single PDF and editable source file (Figma, Miro or similar) containing all diagrams, timelines and references.
2. Architecture and AI recommendations must align with current App Store & Google Play guidelines.
3. Each sprint plan clearly lists objectives, success metrics and required resources.
If you have sample roadmaps or live apps that showcase similar AI-enabled e-commerce flows, feel free to reference them so I can gauge fit.
Scope
• Define the core feature set: catalogue, smart search, personalised product feeds, in-app marketing tools, cart, checkout, order tracking and an admin dashboard.
• Map AI touchpoints such as image-based product recognition, dynamic pricing, recommendation engines and automated customer-service chat.
• Recommend the full tech stack: mobile frameworks (e.g. Flutter, React Native or native), backend, database, AI/ML services (TensorFlow Lite, Core ML, Amazon Personalize, etc.) and third-party APIs for payments, shipping and analytics.
• Lay out an annotated wireframe or low-fidelity screen flow that illustrates how users move from discovery to purchase.
• Provide a phased development timeline broken into logical sprints with expected deliverables, QA tasks and app-store submission steps.
• Include KPIs tied to sales and marketing goals—conversion rate, average order value, retention—and explain how in-app data will feed the AI models.
Acceptance criteria
1. A single PDF and editable source file (Figma, Miro or similar) containing all diagrams, timelines and references.
2. Architecture and AI recommendations must align with current App Store & Google Play guidelines.
3. Each sprint plan clearly lists objectives, success metrics and required resources.
If you have sample roadmaps or live apps that showcase similar AI-enabled e-commerce flows, feel free to reference them so I can gauge fit.
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