What 76 WMS Buying Conversations Reveal: Mid-Market Benchmark

Most published research about warehouse and inventory software is written by the companies that sell it, and it usually says the same thing: buyers want efficiency, visibility, and scale. That is true and useless.

We had access to something more specific. Between February 2025 and May 2026 we recorded 76 sales conversations with mid-market eCommerce merchants who were actively evaluating new inventory, order, and warehouse management software. These were not surveys. They were unscripted, hour-long conversations in which an owner or operations lead explains, in their own words, what is broken, what they run today, and what they can afford. Together the transcripts run to 460,694 words, an average of 6,062 per conversation.

The headline counts, buyer speech only: buyers raised integrations or APIs in 56 of 76 operations (74%), more than price and more than any individual feature. 50 of 76 named a specific eCommerce platform, yet only 17 of 76 named any dedicated inventory or warehouse management vendor. 20 of 76 described a spreadsheet as live infrastructure, and 37 of 76 called part of their own process manual.

Methodology, up front

The sample. 76 recorded sales-demo conversations with prospective buyers of inventory, order, and warehouse management software, spanning 2025-02-17 to 2026-05-14. All 76 are non-empty and were analyzed.

The unit of measurement. Every figure is conversation-level: "X of 76" means the term appeared in X distinct conversations. An operation that says "barcode" forty times counts once.

Buyer counts versus either-speaker counts, always labeled. Each transcript is split into speaker turns, and turns belonging to SkuNexus staff are excluded from any buyer count, so a term only counts when a buyer said it, not when a salesperson pitched it. Figures that include vendor speech are labeled "either speaker" or "came up." The columns disagree in instructive ways: cycle counting comes up in 39 of 76 conversations, but buyers themselves raised it in only 14.

Literal counts versus extraction. Software can reliably count whether a buyer said "barcode." It cannot reliably count whether a buyer "expressed frustration with vendor lock-in": interpretations drifted by 25 to 30 percent when spot-checked. The spine of this page is therefore literal counts of concrete nouns, and every literal figure is a lower bound by construction. The correct reading is always "at least N of 76 said so," never "only N of 76 do this." A small set of extraction figures survives in one clearly labeled section, and nowhere else.

What this sample is not. These are merchants who had already decided to evaluate new software, so they are self-selected toward dissatisfaction with their current setup. Each conversation was with a single vendor. This is a benchmark of mid-market buyers in an active buying cycle, not a census of all merchants and not a neutral product comparison.

Part one: what mid-market operations are actually running

Integration is the most raised subject: 56 of 76 buyers

Buyers in 56 of 76 operations (74%) raised integrations or APIs, making it the single most frequently raised concrete subject in the corpus. Nothing else came close. The question rarely arrived as "do you integrate?"; it was almost always "do you integrate with this named thing that I already run and am not replacing." Buyers in 23 of 76 (30%) used the word API directly.

The storefront is the fixed point: 50 of 76 named their platform

Buyers in 50 of 76 operations (66%) named a specific eCommerce platform, and 40 of 76 (53%) named Shopify. It is named more often than any warehouse system, accounting system, or inventory vendor: operators describe their stack starting from the platform that takes the order, and work backwards.

The ledger is QuickBooks more often than it is an ERP

Buyers in 25 of 76 operations (33%) named a specific accounting or finance system, and 20 of 76 (26%) named QuickBooks. Counting either speaker, QuickBooks appears in 26 of 76 conversations (34%), usually as the system of record any new platform must integrate with, sometimes as the only inventory tool in the business. As one merchant put it about QuickBooks for inventory: "it's not very good." Buyers in 18 of 76 (24%) named an ERP of any kind, the whole NetSuite, SAP, Sage, Dynamics, Epicor, Acumatica, Infor and Odoo family combined, and the enterprise names appear mostly as the rejected "too expensive, too legacy" pole of the decision. The ledger these operations reconcile against is more often a small business accounting package than an enterprise suite.

Amazon is an operating constraint, not a channel

Buyers in 30 of 76 operations (39%) named a marketplace, and 28 of 76 (37%) named Amazon specifically, more than every dedicated inventory software vendor combined. For an operations team a marketplace is not a sales channel; it is a set of packaging rules, label rules, and cutoff times the warehouse has to satisfy.

The spreadsheet is still load-bearing: 20 of 76

Buyers in 20 of 76 operations (26%) referred to a spreadsheet, Excel, or Google Sheets while describing how their operation currently runs. Widen the pattern to include manual-work language ("manually," "by hand," "typing it in") and the literal buyer union reaches 43 of 76 (57%). Many merchants never say "spreadsheet"; they say "we do everything by memory," and the manual reality sits underneath. We wrote about the breaking point in when spreadsheets stop working for inventory.

The category incumbent is missing from the buyer's own story: 17 of 76

Buyers in 17 of 76 operations (22%) named any dedicated inventory or warehouse management vendor, against 50 of 76 who named an eCommerce platform. It is the most structurally interesting number in the study, and it is not a market-share statement: the platform is named, the ledger is named, the marketplace is named, and the inventory system, more often than not, is a set of manual habits stitched between them.

Counting either speaker against a broader tracked list that adds shipping tools, a third-party tool is named in 40 of 76 conversations (53%). The most-referenced point solution is ShipStation, named in 15 of 76, identical in both columns, and in several conversations it appears as an incumbent pushed past its intended purpose, used as an order-management hub rather than a shipping tool.

Part two: what the work looks like on the floor

Scanning is the most discussed floor practice: 49 of 76

Buyers in 49 of 76 operations (64%) used barcode or scanning language, with 39 of 76 using the noun barcode itself and 17 of 76 referring to scanner hardware directly; either speaker, the topic comes up in 63 of 76. It runs in two registers: operations asking whether the software can generate barcodes for items that never had them, and operations that already scan asking about harder cases, like barcoding a location rather than a product. Our guide to barcode software for inventory management starts there.

Nearly half describe their own process as manual: 37 of 76

Buyers in 37 of 76 operations (49%) described part of their process as manual, done by hand, or typed in. That this coexists with the platform finding is the core tension of mid-market fulfillment: the front end is current, the back end is a person retyping.

Inbound is not a footnote: purchase orders 28, receiving 26

Buyers in 28 of 76 operations (37%) discussed purchase orders and 26 of 76 (34%) discussed receiving or putaway, frequently wanting the receiving scan and the purchase order to be the same event rather than two records reconciled later.

Bins, kits, and the shape of the exceptions

Buyers in 23 of 76 operations (30%) discussed bins, bin locations, aisles, or slotting, and the recurring request underneath is permission to break the assumption that one SKU lives in one place.

Buyers in 20 of 76 operations (26%) discussed kitting, kits, bundles, or bundling, across unrelated verticals. One protein producer described virtual kitting: the sale can be composed any number of ways, but the pick is against the true underlying items. That distinction, between how something is sold and how it is picked, is the practical definition of the problem.

Multi-warehouse: 19 of 76 buyers describe it, in a corpus where 66 say "warehouse"

Buyers in 19 of 76 operations (25%) described operating more than one warehouse or location, in a corpus where 66 of 76 buyers used the word warehouse at all; either speaker, multi-warehouse phrasing comes up in 50 of 76. The descriptions were rarely tidy: one contractor runs four warehouses plus a corporate office; another splits inventory across two buildings by channel and wanted routing to respect the split. Raised by vendors far more often than volunteered by buyers, multi-warehouse reads as a near-future requirement more often than a present fire.

Cycle counting: the clearest vendor-led topic in the corpus

Buyers in 14 of 76 operations (18%) raised cycle counting or physical inventory. The same language appears in 39 of 76 conversations once SkuNexus staff turns are included. That gap is why this page counts buyer speech separately: it is the difference between what vendors like to discuss and what buyers arrive wanting to discuss.

Every topic, buyer column versus room column

Where the room column towers over the buyer column (customization, dropshipping, purchase orders, cycle counting), the topic is substantially vendor-led. Where the columns sit close (spreadsheets, ShipStation), the buyer owns it. Overselling was raised by buyers in only 8 of 76, but when it is a pain, it is visceral:

"Main challenges are overselling... We think that we have three items of a specific SKU... when we actually go to that unit to pick up the stock... we find only two, we find only one."

- furniture retailer

One more pattern worth isolating: vendor neglect of a critical integration is a churn signal, not just a pain. As one hardware merchant put it about an incumbent: "their integration exists, but when things break, they break hard."

Part three: what buyers ask the software to do

Buyers in 31 of 76 operations (41%) used customization language, asking whether something could be customized, configured to their process, or built to their specification. (Either speaker, the language appears in 70 of 76, which mostly measures how often vendors say it.)

Buyers in 20 of 76 operations (26%) described wholesale, B2B, or distribution activity, and 11 of 76 (14%) used direct-to-consumer language. The mixed-model operation is normal here: the same building ships a pallet to a retail account and a single unit to a consumer, and the two flows want different paperwork, packing, and carriers.

Buyers in 20 of 76 operations (26%) discussed dropshipping or supplier direct shipment, and 14 of 76 (18%) referred to their own developers, engineers, or programmers, in at least one case because the person on the call had personally written the warehouse software the company was running.

How buyers talk about budget

Budget was raised in most conversations, and the reference point was almost always what the buyer already pays for a starter tool or a stack of apps, not a category benchmark. Two patterns held. First, buyers compare a quote to their current spend, so a platform is judged against a spreadsheet plus a few subscriptions rather than against other platforms. Second, pricing that scales with order volume reads as a penalty for growing, and buyers said so in their own words. This page does not publish price figures, ours or anyone else's. To put your own numbers against your current process, use the WMS ROI calculator, which shows every formula.

Volume and seasonality

Buyers in 32 of 76 operations (42%) stated a concrete order or shipment volume (strict pattern in the appendix; looser grammar reaches 38). Stated figures ranged from about 10 to 15 orders per day to a typical 5,000 per day, with the median in the low hundreds. Seasonality is a quantified, recurring stressor: one merchant does roughly 90% of a quarter-million annual orders in one quarter, and another goes from about 800 orders a month to 5,000 in November and December. The volume that matters to this buyer is often not today's, but December's.

Model-extracted themes, kept but labeled

Earlier versions of this page reported figures produced by structured extraction, a normalized model read of what the prospect stated. Extraction corrects speech-to-text garbles (raw transcripts render Cin7 as "sin 7" and never captured Linnworks cleanly), but it is an interpretation, not a literal count, and cannot be reproduced by string matching. These figures stay published because other pages cite them. If you quote one, carry the label with it.

• Spreadsheets or manual workflows described as a core problem: 47 of 76 (62%). The literal buyer-language union is 43 of 76.
• An explicit price, cost, or budget objection: 49 of 76. Literal objection language matches 17 of 76 buyer-only, 28 either speaker.
• A substantive budget or pricing signal: 66 of 76. Broad literal pricing language: 63 of 76 buyer-only, 71 either speaker.
• At least one existing or alternative solution on record, including ERPs and in-house builds: 71 of 76.
• At least one extracted pain point: 75 of 76.
• Integration or sync problems as a stated pain: 27 of 76. (Buyers raised integration as a subject in 56 of 76.)
• Vendor neglect or poor support: 17 of 76.
• Implementation time raised as a fear: 13 of 76.
• Overselling or stockouts as an active pain: 12 of 76.
• Outgrown, too rigid, or cannot customize: 12 of 76.
• Multi-warehouse as an active pain: 11 of 76.

Takeaways

If you are a merchant evaluating software

1. Your integration list is your requirements document. Integration was raised by buyers in 56 of 76 operations, more than any feature. The storefront and the accounting package are the systems nobody plans to replace; everything else has to fit around them.
2. The spreadsheet is not a beginner tool. It is usually there because it is the only layer flexible enough to hold the part of the process the real systems refused to model.
3. Scanning is the highest-leverage physical change available. It converts a manual step into a recorded event, and it is the prerequisite for reliable counts and location accuracy.
4. Buy for the exceptions, and price the December problem. Kitting, multi-location, dropshipping, and mixed B2B and DTC all describe the same situation: the exceptions are the business. Ask how the software, and its pricing, behaves at 3 to 4 times your current volume before you sign.

If you are a vendor or an analyst

• The buyer's baseline competitor is a spreadsheet, not another platform. Only 17 of 76 buyers named a dedicated inventory or WMS vendor at all. The incumbent is manual process, and the real switching cost is behavioral.
• Buyers judge a quote against their current spend, not against other platforms. Volume-independent pricing consistently reduces that friction; pricing that grows with order count reads as a penalty for growing.
• Count buyer speech, not room speech. Cycle counting looks like a 39-of-76 topic until vendor turns are excluded, and then it becomes 14. Sales-call mining that does not separate speakers will mistake its own pitch for demand.

Limits, stated plainly

This is a sample of operations that agreed to a vendor conversation, not a random market sample, and it skews toward operations where something was already broken. Literal counts undercount every behavior they measure. Percentages are for readability only; with n=76, a difference of two or three conversations is not meaningful, and no claim here depends on one.

Cite this study

If you reference these figures, please use this form, so the numbers stay attached to their method:

SkuNexus Mid-Market WMS Buying Benchmark (2026). A review of 76 recorded buying conversations with mid-market eCommerce and distribution operations, February 2025 to May 2026. Figures are literal buyer-language counts at the conversation level and are lower bounds, except where labeled either-speaker or extraction. https://www.skunexus.com/blog/mid-market-wms-buying-benchmark

Methodology appendix: every number and the pattern that produced it

All patterns are case-insensitive regular expressions applied at the conversation level, n=76; the buyer column counts buyer turns only. Word boundaries are enforced, so "Excel" does not match "excellent." Reproduce any row with node scripts/corpus-verify.mjs "<pattern>".

Families deliberately not published as counts. Vendor abandonment, inability to see inventory, and fear of implementation risk are real themes in these transcripts that cannot be counted from literal language. They appear only in the labeled extraction section, or not at all. Excluded rather than estimated.