AI-Driven E-commerce App Blueprint Rahul John
Budget: $250 – $750 USD
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.