Fulfillment | eCommerce Automation

Back to Case Studies

eCommerce

Automated Shopify → 3PL Fulfillment Pipeline

Zero-touch fulfillment automation for a growing D2C brand fulfilling 300–1,500 orders/day.

eCommerce automation case study featuring integration and workflow automation.

Overselling

-70%

Ship Time

Eliminated

Manual Work

Overview

A D2C eCommerce brand fulfilling 300–1,500 orders/day needed zero-touch fulfillment automation. Inventory mismatches were causing overselling, and manual CSV exports to their 3PL were delaying shipments.

Business Context

The brand had grown rapidly through successful social media marketing, but their fulfillment operations hadn't scaled with their order volume. Customer complaints about delayed shipments and canceled orders due to overselling were damaging reviews and repeat purchase rates, with a measurable impact on customer lifetime value. The operations team was working overtime just to keep up with manual order exports, and every human touchpoint introduced potential for error that could result in a poor customer experience. The CEO recognized that fulfillment complexity was becoming the primary constraint on growth, as marketing could drive orders faster than operations could ship them reliably.

How We Built It

We built a comprehensive fulfillment automation system connecting Shopify directly to their 3PL partners via API, creating a zero-touch order flow from purchase to shipment. The core architecture uses Make.com for orchestration with a PostgreSQL database maintaining real-time inventory state across all sales channels and warehouse locations, synchronized every five minutes with warehouse management system data. The SKU normalization engine handles the complexity of product variants, bundles, and kits, ensuring the 3PL receives correctly formatted orders regardless of how products are structured in Shopify — this was critical as the brand had over 400 SKUs with complex variant relationships. Webhook listeners capture new orders instantly and validate them against current inventory before submission to the 3PL, preventing overselling at the source through optimistic locking mechanisms. The system includes an intelligent error recovery layer that handles common fulfillment exceptions — missing customer details, unrecognized SKUs, address validation failures, split shipments, and international customs requirements — with automated remediation flows rather than requiring manual intervention. Tracking number synchronization runs continuously, pulling shipment updates from the 3PL and pushing them back to Shopify and transactional email systems within minutes of scan. Returns and exchanges flow through a dedicated workflow that automatically generates return labels, updates inventory upon receipt, and triggers replacement shipments or refunds based on customer preference. A Retool dashboard provides the operations team with complete visibility into the fulfillment pipeline, including exception queues, SLA monitoring, carrier performance tracking, and historical performance metrics with drill-down capabilities.

Challenges

Inventory mismatches causing overselling

Manual CSV exports for 3PL

Delayed order fulfillment

No unified visibility of shipments

Customer complaints increasing

What We Delivered

Automated Shopify → 3PL order sync

SKU normalization engine

Automatic tracking number updates back to customers

Returns + exchange workflow

Real-time order status dashboard

Error recovery system (e.g., SKU not found, missing customer details)

Tech Stack

Shopify API, 3PL APIs (ShipBob, ShipStation), Make.com, Retool, PostgreSQL

Results

Overselling

-70%

Ship Time

Eliminated

Manual Work

Strategic Impact

The elimination of overselling incidents immediately improved customer satisfaction scores and reduced support ticket volume by over 60%, freeing support agents to focus on higher-value customer interactions. Ship time reduction of 70% means customers now receive orders 1-2 days faster on average, directly contributing to improved reviews and repeat purchase rates that compound over time. The operations team that previously spent entire days on fulfillment tasks has been redeployed to higher-value work including customer experience improvements, new product launches, and supplier relationship management. The automated error recovery system catches and resolves issues that previously would have resulted in delayed or failed shipments, maintaining fulfillment SLAs even during peak sales periods like Black Friday and flash sales when order volume increases 10x. The brand has been able to scale from 500 to 1,500 orders per day without adding operations headcount, fundamentally improving unit economics and contribution margin. The real-time inventory accuracy has enabled the marketing team to run promotions with confidence, knowing the system will automatically prevent overselling and manage inventory allocation across marketing channels. Perhaps most importantly, the brand now has the operational foundation to expand to new sales channels like Amazon and wholesale, as the fulfillment infrastructure can handle multi-channel complexity without additional manual work. The system has also improved vendor relationships as purchase order automation ensures timely restock orders based on velocity data and lead time calculations.