If you’re a DTC operator running a small Shopify store and your inventory situation is “I have a spreadsheet and I cross my fingers,” this post is for you. The good news: most of the painful inventory problems small DTC brands have are solvable by connecting Shopify to an agent that can ask the right questions and watch the right signals. No new ERP. No $400/month inventory SaaS.
This is the playbook we’ve watched real operators build using Tablize. Steal it.
The three problems
Almost every DTC inventory mistake we’ve seen falls into one of three buckets:
1. Stockouts on top-sellers. You sell out of your best SKU and lose 2 weeks of revenue waiting on a reorder. Often the cause is “I forgot to look at velocity changes.”
2. Dead stock. You ordered 500 units of a SKU that’s selling 5/week. You’ll be unwinding that order for 100 weeks. Often the cause is “the launch numbers looked great so we kept ordering.”
3. Replenishment math is wrong. You order based on last month’s sales, but lead time is 6 weeks. By the time the new stock arrives, demand has already shifted. Often the cause is “I haven’t built the model for it.”
A good inventory monitoring setup catches all three before they hit you. Here’s how to wire each one in Tablize.
Setup: connect Shopify (and ideally Amazon SP)
If you’re not already connected, Shopify → Tablize takes 2 minutes via OAuth. The agent reads your orders, order_line_items, products, and customers tables. Historical backfill happens once, then incremental sync from there.
If you sell on Amazon too, connect Amazon Selling Partner the same way. Now the agent can compute combined sell-through across both channels — which is what you actually need for forecasting, since pulling stock for one channel affects the other.
You’ll also want one upload: your COGS sheet. Whatever you have. A Google Sheet, an Excel file, a CSV. Drag it in. The agent uses it to compute true margin per SKU later.
Problem 1: stockout prevention
The version of this most people do: open a dashboard once a week, eyeball inventory levels, mentally guess what’s running low. This works for ~5 SKUs and breaks at 20.
The Tablize version: a Watch.
"Watch my Shopify inventory. For each SKU in my top 50 by
trailing-30-day revenue, calculate days-of-inventory based
on the last 30 days of velocity. If any of them drops below
14 days of supply, ping me on Slack with the SKU name,
current stock, daily velocity, projected stock-out date,
and recommended reorder quantity assuming a 30-day cover."What this does:
- Computes velocity dynamically. Top-50 changes as your sales mix changes; a SKU that just blew up is included automatically.
- Calculates real days-of-inventory. Not just “below 100 units” — for this SKU at its current sell-rate, when does it stock out.
- Pings you with everything you need. SKU name, current stock, projected stock-out date, recommended reorder. You don’t have to open Tablize to act — you can decide and act from the Slack DM.
- Skips noise. A SKU selling 1/month doesn’t need a 14-day alert. The “top 50 by revenue” filter keeps the signal-to-noise high.
This Watch fires every few hours on average for a busy store. After a week, you have a feel for which SKUs are running hot and which are stable. Stockouts stop happening to top-sellers.
The starter pack for this exact pattern: /templates/inventory-below-threshold-alert.
Problem 2: dead stock detection
This is the opposite problem. You have units sitting in the warehouse not moving.
The Tablize version: a weekly report.
"Every Monday, find SKUs where:
- I have more than 60 days of inventory at current velocity
- I've been reordering them on a regular cadence
- Velocity has dropped more than 30% from its peak
List them with current stock, peak velocity, current velocity,
days-of-inventory, and a recommendation: stop reordering,
promote with discount, or write off."The Monday brief lands in your inbox. You scan it in 90 seconds. Most weeks, the list is empty or has 1-2 SKUs to act on. Once a quarter, you discover an inventory drift that would’ve cost you another quarter of dead capital.
The Tablize-specific thing here: the agent looks at peak velocity vs current velocity. It catches SKUs that used to sell well but have slowed down — the most common dead-stock pattern. Just looking at current velocity misses it because the SKU still moves some.
Problem 3: replenishment math that accounts for lead time
The naive replenishment formula is:
reorder quantity = expected sales × cover period
But this ignores lead time. By the time your reorder arrives, demand has shifted, you have new sales to account for, and your assumption about “expected sales” is stale.
The right formula is closer to:
reorder quantity = (forecasted sales over lead time + cover period) − (current stock + in-transit stock) + safety stock
Doing this in a spreadsheet is painful. Doing it in Tablize is one prompt:
"Build me an inventory replenishment app. For each of my top 100 SKUs,
forecast daily sales for the next 90 days using last 90 days' data
with day-of-week and trend components. Show me:
- Current stock
- In-transit (assume from my Shopify metadata.in_transit field if present, else 0)
- Lead time (assume 30 days unless I tell you otherwise per SKU)
- Forecasted demand over the lead-time + 30 days cover
- Recommended reorder quantity (accounting for safety stock of 14 days)
- Suggested reorder date (when current + in-transit hits 14 days of cover)
Give me checkboxes to approve / skip each reorder, and log my decisions."The agent builds a small app. You open it once a week, scan the table, check boxes for the SKUs to reorder, send the decisions to your supplier (Tablize can email or generate a PO PDF). Your decision log makes it easy to look back next quarter at “did my reorder calls turn out right” — which feeds back into improving the model.
The starter pack: /templates/inventory-replenishment-app.
What this replaces
If you’re currently using:
- Just a spreadsheet: you’ll catch more, faster, and with less effort.
- Shopify’s built-in inventory reports: Shopify’s reports tell you what is — Tablize tells you what’s about to happen.
- A $100-200/month inventory SaaS (Cogsy, Inventory Planner, Brightpearl): the dedicated SaaS has fancier UI and more features. Tablize gives you 80% of the value at $60/month, with the upside that you can ask any question you want, not just the ones the SaaS author thought of.
For DTC brands above ~$5M/year with complex multi-warehouse + B2B operations, you’ll probably want the dedicated SaaS or a real ERP. For everyone below that — which is most DTC brands by count — Tablize is the right cost/value point.
What it doesn’t do
To be clear about gaps:
- No PO generation to vendor systems. Tablize can draft the PO content, but you’ll send it via your email or vendor portal.
- No barcode scanning for receiving. You’ll still need your existing warehouse process for that.
- No multi-warehouse stock allocation logic. If you have 3 warehouses and need to optimize where to ship reorder receipts, that’s a different problem.
- No demand forecasting from external signals. The forecast uses your own sales history. If you want to incorporate Google Trends or paid traffic projections, that’s possible but you’d build it yourself.
What to do this week
If you’re a DTC operator and you got this far, here’s the 30-minute setup:
- Connect Shopify to Tablize (2 min).
- Drop in your COGS spreadsheet (1 min).
- Set up the stockout watch (2 min).
- Set up the Monday morning sales brief (2 min).
- Run profit by SKU after all costs once to see what’s actually making money (5 min).
- The replenishment app: leave it for next week. Get the watches running first, then build the app once you have a few days of data on what fires.
That’s the order. Watches catch the urgent stuff (stockouts). Weekly briefs catch the patterns (dead stock). The replenishment app is the deeper investment but only useful once the other two are in place.
Try Tablize free with your Shopify store →
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