SKU.io research · Q4 2026
The Ecommerce Ops Pain Index
What 135 ecommerce operators told us was broken, counted from 146 recorded
evaluation calls between April 2021 and September 2026. Updated every quarter.
Data as of October 7, 2026 · next update January 2027
135ecommerce operators, one vote each
45%described hours of manual data entry
31%ran core operations on fragile spreadsheets
30%started looking because their current tool was failing them
The short version
The most common problem was the least glamorous one. 45% of operators described people spending real time re-keying orders, purchase orders, tracking numbers and invoices from one system into another. 31% said their stock, purchasing or reporting lived in spreadsheets that break, go stale or depend on one person.
Overselling across channels came up as a current problem for 6.7% of operators, the joint lowest share in the index. Even among the 57 operators selling on three or more channels it was 8.8%.
The most common reason to start looking was that the current tool was failing them (30%), slightly ahead of growth into a new channel, warehouse or volume (27%). Moving off spreadsheets for the first time was the trigger for 11%.
Most operators had more than one problem. The median operator described 2 of the 13 as current. 19% described none of them, and their needs were elsewhere, for example dropshipping workflows or tracking stock by warehouse bin.
What operators said was broken
Share of the 135 operators who described each problem, in their own words, as a current
problem in their business. One company counts once per problem, however many times it came up. Most raised more than one, so
the bars add up to more than 100%.
Share of operators describing each operations problem as current, Q4 2026, n=135 | Problem | Share of operators | Operators |
|---|
| Hours of manual data entry People spend significant time re-keying orders, POs, tracking numbers, invoices or data between systems by hand. | 45.2% | 61 |
| Running on fragile spreadsheets Core operations (stock, purchasing, reporting) live in spreadsheets, macros or manual reports that break, go stale or depend on one person. | 31.1% | 42 |
| Purchasing by gut feel Reordering and purchasing decisions lack a trustworthy forecast or reorder signal, causing stockouts, overstock or cash tied up in inventory. | 15.6% | 21 |
| 3PL and warehouse integration friction The relationship with a 3PL or WMS is held together by CSVs, a flaky API, missing or duplicated orders, or poor visibility into stock at the 3PL. | 14.8% | 20 |
| No true profit per order or SKU They cannot see true profit or COGS per order, SKU or channel (landed cost, fees, 3PL costs not attached), so they run on a margin number they do not believe. | 14.1% | 19 |
| Too many disconnected tools Running the operation means bouncing between many separate apps/portals that do not talk to each other; they want one place to run operations. | 14.1% | 19 |
| Inventory numbers they no longer trust The operator does not trust the stock counts their current system shows, often because a sync or tool overwrote, drifted or mis-synced inventory, so they check by hand. | 13.3% | 18 |
| Inventory that won't reconcile with the books Inventory value, COGS or transactions in the ops system do not reconcile with QuickBooks/Xero/accounting, requiring manual journal work or causing misstatements. | 12.6% | 17 |
| Bundles, kits and multipacks Bundles, kits, multipacks or bills of materials are not handled properly: component stock, fulfillment instructions or demand for components are wrong or invisible. | 10.4% | 14 |
| Priced out by enterprise software They were quoted or burned by expensive, long, heavy ERP implementations (large onboarding fees, months-long rollouts) that did not fit their size. | 8.9% | 12 |
| Amazon FBA/AWD as its own universe Amazon FBA/AWD inventory, inbound shipments, fees, reimbursements or valuation are hard to track or reconcile alongside the rest of the business. | 8.1% | 11 |
| Overselling across channels Inventory is not unified across sales channels or stores, causing oversells, cancellations, or no way to allocate or reserve stock per channel. | 6.7% | 9 |
| Losing track of supplier money Supplier deposits, payment terms, purchase-order balances or vendor bills are not tracked in a system, so they are surprised by what they owe. | 6.7% | 9 |
Wanting one system is not the same as suffering from many
41% of operators said they wanted one place to run everything. Only 14% described what juggling their current tools actually cost them. The same gap shows up for profit per order (28% raised it, 14% described it as a current problem) and for purchasing (29% against 16%). The table below shows both measures for every problem.
| Problem | Raised it at all | Described it as a current problem |
| Hours of manual data entry | 55.6% | 45.2% |
| Running on fragile spreadsheets | 35.6% | 31.1% |
| Purchasing by gut feel | 28.9% | 15.6% |
| 3PL and warehouse integration friction | 17% | 14.8% |
| No true profit per order or SKU | 28.1% | 14.1% |
| Too many disconnected tools | 41.5% | 14.1% |
| Inventory numbers they no longer trust | 16.3% | 13.3% |
| Inventory that won't reconcile with the books | 19.3% | 12.6% |
| Bundles, kits and multipacks | 23.7% | 10.4% |
| Priced out by enterprise software | 14.8% | 8.9% |
| Amazon FBA/AWD as its own universe | 14.1% | 8.1% |
| Overselling across channels | 14.1% | 6.7% |
| Losing track of supplier money | 11.1% | 6.7% |
"Raised it at all" counts an operator who brought the problem up in their own words, as a problem or as
something they wanted. "Described it as a current problem" is the stricter count used in the chart above.
Why they were looking
The reason each operator gave for evaluating new software at that point, one per company.
| Trigger | Operators | Share |
|---|
| The current tool was failing them | 40 | 29.6% |
| Growth: a new channel, warehouse, 3PL or more volume | 36 | 26.7% |
| No clear trigger stated | 31 | 23% |
| Moving off spreadsheets for the first time | 15 | 11.1% |
| The current tool was ending, changing or repricing | 6 | 4.4% |
| Pressure from finance, accounting or investors | 5 | 3.7% |
| A person leaving, joining, or the team not keeping up | 2 | 1.5% |
What they were running on
What each operator used to track inventory when we first spoke.
| Inventory system at the time | Operators | Share |
|---|
| Not stated | 33 | 24.4% |
| Another inventory app | 33 | 24.4% |
| Spreadsheets | 28 | 20.7% |
| The store platform itself (e.g. Shopify) | 12 | 8.9% |
| Cin7 | 11 | 8.1% |
| A custom-built system | 8 | 5.9% |
| An ERP (NetSuite and similar) | 6 | 4.4% |
| The accounting system only | 4 | 3% |
How we counted
- Source. Recorded video calls between SKU.io and ecommerce operators (brands, retailers
and wholesalers selling online) who were evaluating inventory software. We screened 742
recorded external calls and kept the 135 companies whose first recorded conversation with
us was an evaluation. Calls with partners, vendors, accountants and existing customers were left out.
- One company, one vote. Each company contributes its first one or two recorded
conversations (146 calls in total). A company we spoke to twenty times counts the same as one we
spoke to once.
- The operator has to say it. A problem counts only when someone from the operator's side
raised it or described it in their own business. Agreeing with something we described does not count.
Each count is backed by a line from that operator's own words, and we check that the line appears
word for word in the transcript (3 candidate lines failed and were dropped).
A second, separate review then reads each line and keeps it only if it describes that problem in the
operator's business today, not a wish or a hypothetical.
- Coding. A language model codes each conversation against fixed definitions (shown under
each problem above). It is the same model and the same definitions every quarter, so a change in a
share means the conversations changed, not the method.
- What this sample is. These are operators who booked a call with an inventory software
company, so they already had a problem worth a meeting. Read the shares as "how often this comes up
when an operator goes looking for help", not as a rate for all online sellers. The numbers describe
what was said. They do not show what causes what.
- Privacy. The page reports counts only. It quotes no one and names no company, and
we keep the underlying data de-identified. Nobody is identifiable from it.
Using these numbers
The figures are free to cite under CC BY 4.0.
Please link to this page and include the edition and n:
SKU.io Ops Pain Index, Q4 2026 (n=135 ecommerce operators), https://www.sku.io/research/ecommerce-ops-pain-index/
Download the table as CSV. Journalists and analysts who
want more context can reach Kalvin Mizzi, SKU.io's founder, who runs these calls, through the
contact page.
Editions
- Q4 2026 (October 7, 2026): First edition. 135 operators, evaluation calls from April 2021 to September 2026.
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