Success Criteria

What the platform needed to deliver

• Data‑Driven Solutions: analytics + AI-ready foundations to improve marketplace performance
• Automated Marketplace Reporting: timely insights for faster sales and ops decisions
• Scalable SaaS Platform for Ecommerce: flexible architecture that grows with SKU volume and channels

Technical Deep Dive: Development Phases

We built the platform in three phases: first establishing the Seller UI, backend, and Amazon connectivity, then adding deeper integrations, embedded analytics, and real-time workflows, and finally delivering an Admin UI with stronger security—resulting in a scalable, enterprise-ready solution.

• Phase 1 — Foundation: Built the Seller UI and backend with secure account management, Amazon Seller Central catalog integration, and an AWS (Redshift) data foundation.
• Phase 2 — Enhanced Functionality: Embedded Tableau reporting, expanded Amazon API integrations, added real-time order notifications, and strengthened secure data persistence.
  
• Phase 3 — Admin & Advanced Features: Launched the Admin UI with role-based access, employee management, and additional user controls to improve usability and security.
  

Summary

Marketplace IQ.ai is a marketplace analytics SaaS tool built to simplify multi-channel operations through centralized data integration, automated reporting, embedded visualization, and scalable user/admin controls—helping sellers operate faster, with clearer insights and less manual work.

Success Criteria

What the platform needed to deliver

• Real-time inventory synchronization tool: automatic stock updates across Amazon and Shopify
• Shopify Amazon order management: reduce manual order handling in separate systems
• FBA, FBM order processing: support both fulfillment models cleanly
• Amazon Shopify order integration: import, process, and reconcile orders reliably
• Automation-first workflows: minimize human error and operational overhead
• Security and reliability: protect sensitive order/customer data and maintain trust
• Scalable operations: handle growth without creating new bottlenecks

Technical Deep Dive: Development Phases

Inter-soft developed ToolE Amazon Easy Sync in six structured phases to ensure fast onboarding, reliable Amazon–Shopify integrations, and strong data protection—while delivering measurable operational improvements for Shopify sellers.

• Phase 1 — Initial Research and User Engagement: identified high-impact merchant pain points across Amazon + Shopify operations
• Phase 2 — User-Friendly Interface Design: built an intuitive workflow and logic for efficient inventory and order management
  
• Phase 3 — Security and Reliability: implemented robust protections for customer and order data to preserve integrity and trust
  
• Phase 4 — Implementation and Setup Process: Implementation and Setup Process
  
• Phase 5 — Impact Measurement: validated efficiency gains (40% less time on inventory tasks; 25% higher order accuracy)
• Phase 6 — Cost Savings and Business Growth: demonstrated automation-driven savings (~USD 5,000 annually) and growth (15% sales lift over six months)
  

Key technical highlights

• Real-time sync logic to reduce inventory drift
• Automated import + processing workflows for Amazon orders in Shopify contexts
• Reliability and security controls appropriate for ecommerce data flows
• Scalable foundations for increasing SKU counts and order volume

Summary

Inter-soft delivered Amazon Shopify integration software that unifies inventory and orders across channels, supports both FBA and FBM workflows, and gives sellers a scalable foundation for automated multi-channel operations.

Success Criteria

What the platform needed to deliver

• Ecommerce analytics dashboard: clear, role-friendly views of KPIs and trends
• Marketplace profitability tool: insights tied to operational and performance levers
• API-integrated marketplace analytics: Amazon SP‑API + Ads API connectivity with secure storage
• Operations management: inventory visibility, alerts, and workflow support
• Marketing support: campaign planning and tracking with actionable reporting
• Customization: configurable dashboards and reporting to match each business model
• Security & privacy: strong controls for marketplace and customer data

Technical Deep Dive: Development Phases

Inter-soft developed DataDash in structured phases to deliver fast onboarding, reliable API integrations, and secure data handling—while creating a scalable foundation for new metrics, dashboards, and marketplace workflows.

• Phase 1 — Discovery & KPI Definition: aligned goals, required metrics, and reporting outputs for sellers, agencies, and aggregators
• Phase 2 — Data Architecture & Modeling: designed a scalable analytics foundation to support multiple accounts and evolving datasets
  
• Phase 3 — API Integration Buildout: integrated Amazon SP‑API and Ads API for consistent data ingestion and normalization
  
• Phase 4 — Dashboard UX & Reporting: delivered a user-friendly ecommerce analytics dashboard with configurable views and insights
  
• Phase 5 — Automation, Alerts & QA: implemented event/threshold alerts, validated data accuracy, and refined workflows through testing
  
• Phase 6 — Deployment & Support: enabled onboarding, documentation, and ongoing maintenance for upgrades and new integrations
  

Key technical highlights

• Centralized data ingestion with scalable reporting structures
• API-driven data imports (SP‑API + Ads API) with secure storage practices
• Dashboard customization to match business-specific KPIs and workflows
• Automation and alerting to reduce manual monitoring effort

Summary

DataDash is an AI-powered marketplace analytics tool that brings marketplace analytics, operations visibility, and API-integrated reporting into one customizable dashboard—helping sellers and operators improve profitability through faster, clearer decisions.

Success Criteria

What the platform needed to deliver

• API-based advertising data solutions: integrate Amazon APIs for reliable data ingestion
• Ad campaign data management: consolidate and normalize metrics for analysis
• Advertising data reporting tools: automated reporting with flexible time ranges
• User-centric experience: intuitive navigation for creators and collaborators
• Scalable architecture: support multiple customer accounts and user roles
• Security + control: maintain IKON ownership of data and hosting environment

Technical Deep Dive: Development Phases

We delivered the IKON Dashboard through a structured six-phase build, moving from discovery and architecture to implementation, testing, rollout, and long-term support. This approach ensured we shipped quickly without compromising scalability—while validating user roles, integrating Amazon APIs for real-time data, and keeping IKON in full control of its data on its own servers.

• Phase 1 — Initial Requirement Gathering: aligned stakeholders on goals, metrics, and reporting needs for marketing data management
• Phase 2 — Architecture Design: designed a scalable, multi-account framework supporting multiple customers and integrations
  
• Phase 3 — Implementation: rebuilt the DataDash interface for usability; integrated Amazon APIs (SP‑API + Ads API) for real-time data import
  
• Phase 4 — Testing: validated role permissions (Admin, Customer, Collaborator) and refined features through feedback loops
  
• Phase 5 — Deployment: phased rollout starting with a pilot group, then expanded after iteration
• Phase 6 — Post‑Deployment Support: maintenance and updates framework; ensured IKON retains data ownership on its own servers
  

Summary

IKON replaced fragmented reporting tools with advertising data management software built around Amazon API integrations, Creator Connections tracking, and automated performance reporting—giving teams a centralized, scalable dashboard for better advertising decisions.

Success Criteria

What the platform needed to deliver

• Automation for Ecommerce: reduce manual intervention and repetitive work
• Order Management Software: handle complex scenarios like split orders reliably
• Inventory + Pricing Management Solutions: real-time synchronization across channels
• Ecommerce Data Security Solutions: secure processing and strong data ownership controls
• Ecommerce Analytics Software: scalable reporting foundation for ongoing optimization

Technical Deep Dive: Robust SP‑API and Automated Workflows for Multichannel E‑Commerce Integration

A modular architecture was implemented so Etermart can scale volume and evolve channel coverage without breaking core operations.

Key technical highlights:

• Custom SP‑API Engine: optimized communication with Amazon’s SP‑API for performance and data integrity
• Real‑Time Data Mapping: harmonized product structures and inventory logic across Shopify/Magento/Amazon
  
• Microservices Architecture: scalable, fault-tolerant foundation for future expansion (analytics, pricing optimization, additional channels)
  

Summary

Etermart modernized its multichannel e-commerce operations with a centralized middleware platform that delivers real-time inventory/pricing synchronization, automated workflows, and a custom Amazon SP‑API integration—improving reliability, reducing errors, and enabling scalable growth across channels.