Split shipment management: how Shipsy splits orders across carriers and consolidates back
A “single order” in modern retail is often three shipments from two warehouses via two carriers arriving on two different days — and the customer still expects one tracking link, one delivery window, and one invoice. Shipsy’s split shipment management is the mechanism that makes that work: an order splits at the right boundary, each leg ships on the best lane, and the customer-facing experience stays unified.
This post is for retail, omnichannel, and quick-commerce operators whose order volume is outrunning their ability to fulfill it from a single node.
Why we built this
Three forces broke the old “one order, one shipment” model simultaneously. Inventory moved closer to customers (dark stores, micro-fulfilment, decentralized warehouses). Assortment widened (a furniture order includes the sofa, the cushion set, and the accessory lamp — each from a different node). Delivery promises tightened (10-minute grocery, same-day retail, next-day big-bulky).
The result: a single customer order routinely requires splitting by inventory availability, by SKU characteristics, by delivery timeline, and sometimes by regulatory constraints. Every split is a potential failure point — wrong carrier for a cold item, slower node for a time-sensitive SKU, conflicting tracking links, misaligned invoicing. Shipsy’s split shipment module was built to make splitting a first-class operation, not a workaround.
How it works
The mechanism runs across three stages — split, allocate, consolidate — with Astra making the decisions and Clara handling the customer-facing surface.
1. Split at the right boundary
An incoming order goes through a splitting policy that considers inventory location (what’s in stock at which node), SKU characteristics (fragile, perishable, big-bulky, regulated), delivery promise (same-day, next-day, scheduled), and cost-to-serve per leg. The policy is configurable per shipper — a quick-commerce retailer splits aggressively by SKU temperature and node distance; a furniture retailer splits by big-bulky vs. standard; a marketplace splits by seller and SLA. The output is a set of shipment legs, each with its own fulfilment plan.
2. Allocate each leg independently
Each leg enters Shipsy’s multi-carrier allocation engine as an independent shipment decision. A leg carrying a fragile SKU scores carriers differently than a leg carrying a same-day grocery batch. Legs can move on different carriers, different service levels, and different timelines — each optimized for its content and its promise.
3. Consolidate the customer-facing surface
This is the part most systems miss. Clara maintains a unified order view for the customer — one tracking page showing all legs, one set of notifications that rolls up leg-level events into order-level status, and one customer-service surface that knows about all legs simultaneously. “Where is my order?” returns a consolidated answer. Proactive notifications batch where possible (“two of your three items are out for delivery”) and break out where they must (“your sofa arrives tomorrow, your accessories have arrived”).
Billing, returns, and reverse logistics follow the same unify-then-disambiguate pattern. The customer sees one relationship; the operator sees three shipments.
Here’s the flow at a glance:
Early scenarios
Quick commerce
A single 10-minute order often contains items from two dark stores. Shipsy splits by node, dispatches parallel riders, and Clara surfaces a single countdown timer to the customer. The customer does not know — or care — that two riders ran two routes.
Retail omnichannel
A retail order with apparel, beauty, and electronics may ship from three different nodes on three timelines. Shipsy’s splitting policy accounts for customer-preferred window, and Clara consolidates notifications so the customer gets one update, not three.
Big-bulky multi-SKU
A furniture order with a sofa, cushion, and lamp splits: sofa on a two-person crew with installation, cushion via standard parcel, lamp from a closer node for next-day. Each leg ships on a different carrier with different SLAs. The customer sees one order with three leg-level statuses.
Early results
Retail customers deploying Shipsy’s split shipment module consistently see meaningful reductions in “where is my order?” ticket volume once unified tracking replaces fragmented carrier tracking pages — the same pattern that drives MOVIN’s 85%+ autonomous CX resolution. Quick-commerce operators — including Flipkart Minutes, which cut COD loss 82% and RTO 30% with Shipsy — see measurable reductions in promise-to-dispatch time because the splitting decision runs in real time, not in a human decision loop. Big-bulky retailers like IKEA (95% FADR on Shipsy) see fewer customer-reported “partial delivery” complaints because expectations are set at order-placement, not at delivery attempt.
What’s next
The next step is predictive splitting — pre-computing likely split policies for SKU combinations based on inventory heatmaps, so the order-acceptance experience at checkout already knows the likely fulfilment geometry. Design partners are already on the rollout.