Plugged In: How Spreetail Embedded SPS Commerce Into Its Own Tech Stack to Win the Real-Time Inventory Game
Spreetail solves a problem most e-commerce companies avoid: how do you sell a sauna online and deliver it tomorrow? As the leading e-commerce marketplace accelerator for big-and-bulky products, it helps brands and manufacturers grow on Amazon, Walmart, Target, and other major channels, handling the full lifecycle from listing and advertising to logistics and fulfillment for categories most platforms were never designed to carry.
What makes the model distinctive is also what makes it hard. Oversized, hazmat, and heavy products follow a different fulfillment logic than standard parcel. Warehouse and order systems are built around boxes that fit neatly in trucks, and a 400-pound sauna is not that. So Spreetail does something most companies its size do not: it builds much of its own technology, deciding deliberately where to build, where to buy, and where to plug into something it could not recreate.
The challenge:
Spreetail’s big-and-bulky model needs real-time inventory decisions across a decentralized network, and off-the-shelf tools were not built for it.
The solution:
Spreetail embedded the SPS Commerce network inside its own technology as a native capability, gaining inbound supply chain visibility it could not build alone.
The result:
Two use cases running on SPS data are projected to deliver $2M to $6M in bottom-line impact through lower freight costs and smarter inventory positioning.
The Challenge
Winning on a marketplace like Amazon is not only about having the right product. It is about having it in the right place before the customer orders. Rankings are sensitive to availability: a product that sells out while ranked in the top ten can drop below position ninety overnight, and climbing back is hard. Holding position means throttling inventory across a decentralized fulfillment network in near real time, based on what is inbound, where it is, and when it will arrive. For big-and-bulky, that is a different problem than small parcel. Oversized items move, stage, and cost differently once they are in motion, and a playbook built for boxes does not map onto freight.
Spreetail’s answer has always been to build its own tools, because the off-the-shelf options were not designed for its product mix. But one capability cannot be engineered from scratch: years of multi-enterprise transaction data across thousands of supplier and channel relationships. That is the network effect SPS Commerce has spent more than two decades accumulating. No amount of in-house talent produces it quickly, because it only forms through real transactions across real trading relationships over time.
The Solution
Rather than treat SPS as a vendor relationship, Spreetail treats it as infrastructure. The SPS network is embedded inside Spreetail’s custom technology, surfaced through its own internal tooling so that employees and brand partners interact with SPS data as if it were native. Spreetail’s engineers did the work to wrap around and customize the connection, producing a supply chain intelligence layer the company could never have built as cheaply or as fast on its own.
That layer powers two inbound use cases. The first is overseas consolidation. Spreetail often has products arriving from different manufacturers on cycles that do not align, and SPS data shows where each one sits in the manufacturing and shipping process, surfacing windows to consolidate ocean shipments before they leave the country of origin and cutting freight costs on international moves. The second is a stateside distribution decision. Once consolidated product lands, Spreetail uses SPS data to judge whether to break it apart and inject it into multiple distribution nodes or forward it whole into a single facility, a call that directly affects whether product arrives fast enough for next-day or same-day delivery, the competitive bar in these categories. The value is not only data: when an unexpected weather event spikes demand for something like ice melt, Spreetail can work directly with SPS and its suppliers to force an exception and execute a non-standard solve faster than a feed alone could.
“We’ve plugged SPS into our custom-built ecosystem as if it were part of our own technology, and wrapped around it to make it feel like our own tooling.”
— Josh Smith, CTO, Spreetail
The Results
The two use cases carry a combined projected bottom-line impact of $2M to $6M. Both derive from the same underlying capability: real-time visibility into inbound supply chain data Spreetail could not previously reach at the depth or speed the business demands. The overseas consolidation case is the more concrete of the two, since the freight savings on consolidated ocean shipments are directly measurable, and it may be the stronger standalone number once realized.
That impact sits inside a business operating at scale. Spreetail reported 34% GMV growth in a record year, a 74% reduction in stockouts, and a 95%-plus on-time delivery rate for oversized items, while expanding into more than 10 countries in Europe with a first-mover position in big-and-bulky. These are company-level figures rather than SPS-attributed results, but they describe the environment the integration runs in: one where inventory positioning and delivery speed are the whole game.
The larger point is a proof Spreetail makes simply by how it operates. A technology-first company with the engineers and the inclination to build its own systems chose to plug into the SPS network instead of replicating it, not for lack of capability, but because the network’s value comes from data that can only accumulate through real transactions over years. That is not a build problem. It is a network problem, and it is the one thing Spreetail decided not to build.
It would be too costly and take too long to build ourselves. So we plugged SPS in and treated it like part of our own capabilities.
— Josh Smith, CTO, Spreetail