project-89067 System Requirements Document

Introduction

This document outlines the system requirements for project-89067, a micro SaaS tool designed to recover failed payments for e-commerce platforms like Shopify and Stripe. The tool leverages personalized SMS and AI-driven discount incentives to enhance the recovery of declined transactions.

System Overview

The project-89067 tool aims to address the issue of failed payment recovery in e-commerce, particularly for subscription boxes and Shopify stores. By implementing smarter retry sequences through personalized communication and dynamic discount offers, the tool seeks to improve the recovery rate of declined transactions, which typically fail around 60% of the time with standard retry logic.

Functional Requirements as Story Points

• As a Shopify store owner, I should be able to integrate the tool to recover failed payments using personalized SMS.
• As a Stripe user, I should be able to utilize AI-driven discount incentives to encourage customers to retry payments.
• As a user, I should be able to configure dynamic discount offers based on customer behavior and transaction history.
• As an admin, I should be able to view analytics on recovered payments and the effectiveness of retry sequences.
• As a user, I should be able to customize SMS and email templates for retry sequences.
• As an admin, I should be able to set up automated retry schedules for failed payments.

User Personas

• Shopify Store Owner: A business owner using Shopify to manage their online store, interested in maximizing revenue by recovering failed payments.
• Stripe User: An individual or business using Stripe for payment processing, looking to improve transaction success rates.
• Admin: A user responsible for configuring and monitoring the tool's performance and effectiveness.

Core User Flows

• Shopify store owner integrates the tool -> configures SMS templates -> sets up retry schedules -> monitors recovery analytics.
• Stripe user activates AI-driven discounts -> customizes email templates -> reviews transaction recovery reports.
• Admin configures retry logic -> sets dynamic discount parameters -> analyzes performance metrics.

Visuals Colors and Theme

• primary: #1A73E8 (a deep blue for brand identity)
• primary_light: #4D90FE (a lighter blue for hover states)
• secondary: #FF6F61 (a coral hue for emphasis and links)
• accent: #FFD700 (a vibrant gold for CTAs and active states)
• highlight: #FFA500 (an orange for notifications and active indicators)
• bg: #F5F5F5 (a light grey for the page background)
• surface: rgba(255, 255, 255, 0.9) (a white card/panel background)
• text: #333333 (a dark grey for primary text)
• text_muted: #777777 (a softer grey for secondary text)
• border: rgba(0, 0, 0, 0.1) (a subtle border color)

Signature Design Concept

The landing page for project-89067 will feature an interactive galaxy map where each star represents a feature or section of the tool. Users can click on a star to open a detailed view of that feature, drag to rotate the galaxy, and hover to highlight connections between features. This concept will be implemented using @react-three/fiber and @react-three/drei for a 3D interactive experience.

Landing Hero Motion Brief

The hero section will depict a dynamic illustration of a payment journey. As users scroll, they will see a failed payment attempt transform through personalized SMS and AI-driven incentives, culminating in a successful transaction. This animation will be created using motion/react for smooth transitions and interactions, ensuring a compelling narrative that highlights the tool's value proposition.

Interaction Model & Motion Direction

The intended interaction model for the landing page is "parallax," with layered depth via scroll. Decorative elements will translate at different speeds to create a visually rich first impression, while real content scrolls naturally. This approach is ideal for storytelling and engaging users with the tool's features.

Non-Functional Requirements

• The system must ensure data security and privacy for all user transactions.
• The tool should be scalable to accommodate growing user bases and transaction volumes.
• The system must provide high availability and reliability to ensure continuous operation.

Tech Stack

• Frontend: React for Web
• Backend: Python, FastAPI
• Database: MySQL or MariaDB, using Alembic for migrations
• AI Models: GPT 5.4 for user-friendly responses
• AI Tools: Litellm for LLM Routing, Langchain
• Local Orchestration: Docker, docker-compose
• Server-side Orchestration: Kubernetes

Assumptions and Constraints

• The tool will primarily target Shopify and Stripe users.
• The system assumes users have basic technical knowledge for integration.
• Constraints include compliance with data protection regulations and API limitations of Shopify and Stripe.

Glossary

• Dunning: The process of communicating with customers to recover failed payments.
• Retry Logic: Automated attempts to process a payment after an initial failure.
• AI-driven Incentives: Personalized offers generated by artificial intelligence to encourage payment retries.