Vendor-reported figures — source: www.logiwa.com
eShipper+, a Canadian third-party logistics provider specializing in D2C and B2B ecommerce fulfillment, hit a growth ceiling driven by fragmented warehouse infrastructure. As order volumes scaled, the absence of a unified warehouse management system created compounding inefficiencies: inventory discrepancies from disconnected data sources, manual paper-based pick-and-pack workflows, sluggish order turnaround times, and no meaningful visibility into labor performance. Outdated scanning hardware further constrained throughput. In 3PL environments these gaps carry direct financial consequences — shrinkage running at 6% and unreliable inventory accuracy eroded margins and created friction with clients who expected consistent, fast fulfillment at scale.
After evaluating more than 10 WMS platforms — including enterprise solutions from SAP and Manhattan — eShipper+ selected Logiwa IO for its ecommerce-native design, rapid implementation timeline, and intuitive UX. Robotic process automation underpins the platform's order routing and wave rule engine, replacing manual dispatch decisions with automated, rules-driven workflows. eShipper+ simultaneously partnered with Rufus WorkHero for wearable barcode scanners and granular labor analytics, creating a tightly integrated hardware-software stack. The combined deployment included real-time cycle counting, automated shrinkage controls, and pre-built integrations with Shopify, Amazon, and WooCommerce. In-app support for Locus Robotics was included to accommodate future automation expansion. Both vendors provided hands-on onboarding, compressing time to value and delivering operational clarity within the initial rollout period.
The headline result was a 73% reduction in D2C order processing time, with B2B fulfillment cycles improving by 56%. Inventory accuracy stabilized at 94–98%, up from a baseline marked by frequent discrepancies. Shrinkage dropped from 6% to under 2% — a 67% improvement — with direct margin impact.
Have a similar implementation?
Share your customer's AI results and link it to your vendor profile.
Submit a case study →