Fixes and Fails from Organizing eCommerce Automations

Fixes and Fails from Organizing eCommerce Automations

ByUS Stacked

1. Untangling sync issues between inventory tools and product feeds

One of the biggest headaches I hit was when our Shopify stock levels weren’t matching what Google Merchant Center thought we had. Turns out, the sync delay wasn’t Zapier or Make at all—it was the caching on the product feed system we were pulling from an inventory tool (in this case, connected to Airtable). What showed as updated in Airtable hadn’t pushed out to the public feed endpoint for another 8 minutes, causing occasional rejected products during feed validations.

What made it harder: I built an automation that pinged the public endpoint and updated the Shopify metafield when an item changed in Airtable, but didn’t realize I was actually hitting an older version of the feed. The feed URL didn’t change but had a weird undocumented buffer. So the sync was firing fine—but on stale data.

“Why is the webhook running if nothing changed?” turned into “the webhook WAS firing, but the input hadn’t updated yet.”

I ended up putting a 12-minute delay in Make between Airtable item updates and the webhook push, with a conditional router that checks current vs. previous inventory levels to avoid looping. Slightly messy, but we’ve stayed off the Google warning radar since.

2. Handling rate limits when looping through many Shopify orders

If you’re pulling order records for tagging, analytics, or dumping into a reporting tool, Shopify will throttle you fast. Especially if you’re using Zapier’s built-in Shopify connector and looping through more than around 250 orders in a short window. The API says it’s fine—but batch too fast and suddenly the task history fills with “Shopify: Too many requests” errors.

Make.com gives you more control here. I switched to using Webhooks to call the Shopify REST API directly, then chunked the calls using a sleep function between batches of 30 orders. The keyword is X-Shopify-Shop-Api-Call-Limit—it’s buried in the response headers and shows how close you are to getting cut off.

{
  "headers": {
    "x-shopify-shop-api-call-limit": "36/40"
  }
}

Once that number hits 39/40, wait. If not, keep calling. Super janky but oddly effective.

One weird edge case:

If you’re filtering by date range, Shopify will sometimes skip or duplicate orders if another merchant adjusts a date or metadata during your loop. Always use the order ID cursor method, not just a simple date filter.

Visual sign: your dashboard will show more orders than you have in Sheets or Airtable. That’s your clue something’s off.

3. Dealing with Zapier multi-step search failures mid-zap

Had one client’s Zap fail maybe twice a week—always after Step 3, which did a search against an Airtable base of SKUs. Console logs looked fine. The SKU existed. Path seemed fine… until I saw that sometimes the SKU had a trailing space coming in from Shopify.

None of Zapier’s native search steps trim whitespace. There’s no built-in TRIM() equivalent.

My fix:

I dropped in an intermediary Code by Zapier step at the top using JavaScript to forcibly scrub the SKU before any searches:

return { cleanSKU: inputData.sku.trim() }

This alone cut the weird failures to almost zero. Then I applied the same trim logic to the stored Airtable SKUs using a one-time script because, of course, some of those got copied in with invisible characters too. Literal copy-paste gremlins.

Nothing about this shows up in the Zapier editor. You only catch it staring at a 400 error that technically doesn’t exist. I lost two hours to this one.

4. Disabling automations during bulk product imports and why it matters

There is no built-in “pause” button on Make.com scenarios or Zapier zaps that triggers automatically during data imports. If you’re uploading 300+ products into Shopify or WooCommerce, you will accidentally fire every store sync, feed update, and labeler automation if you haven’t put gate logic around them.

Biggest rescue: I added a Google Sheet flag called Automation_Enabled with a single toggle cell for all related automations. Each zap and Make scenario checks that cell value before running anything. If it returns FALSE or OFF or whatever you want—it exits immediately without even making a Shopify call.

Zapier doesn’t have global variables. But it does let you poll a Sheet cell in under 0.3 seconds. Make does even faster by caching it to memory for 2 mins.

When we did a 500+ product import into a new eComm client’s store, this toggle saved us from 200+ unnecessary emails, 80+ product feed refreshes, and an API lockout warning.

Wish there was a native toggle interface, but this hack gets it done while you bulk-edit in another tab.

5. When metadata conflicts confuse both Zapier and Shopify

I hit a strange wall when two automations—one from Zapier, one from a native Shopify app—were both writing to metafields on the same products. Specifically, a metafield representing inventory origin (Warehouse A / B). The app was writing via GraphQL, I was writing via REST through Zapier’s connector.

No visible errors. But the values kept reverting randomly.

After three dives into Shopify’s changelog, I found buried responses like:

{
  "message": "GraphQL write did not overwrite recent REST write"
}

This doesn’t affect everything—only when updates happen within 10 seconds to the same namespace. So if your automation is auto-tagging based on URL patterns or custom logic, and another integration tries to log where the product came from, you’re stepping on your own updates.

The workaround:

  • Always namespace your metafields with unique prefixes, like auto_source vs. app_logistics
  • Use Make to delay REST metafield updates by 12 seconds if a known app is in play
  • Query the current value first, then skip the write if identical

The actual problem? Shopify’s update collision policy isn’t visible, and doesn’t throw conventional errors when it rejects a write—just makes it look like nothing happened.

6. Using webhook logs to debug client-store sync failures

One client swore “the automation just stopped working.” Their Shopify-to-Google-Sheet order export ran fine for weeks, until it didn’t. No error emails, no Zapier alerts, nothing. But the data in Sheets froze on a random Tuesday.

What fixed it wasn’t Zapier—it was me remembering that Shopify logs outgoing webhook payloads under Settings → Notifications → Webhooks. Hidden deep, but reliable.

The Make scenario tied to the webhook hadn’t changed. But the response payload had—Shopify added a new nested buyer_accepts_marketing field, and for some reason this broke the JSON parse step downstream.

The field technically wasn’t required, so the parser didn’t fail loudly. It just exited early because the custom router in Make branched based on field count (don’t do this, by the way—counting JSON fields as logic triggers is begging for breakage).

Direct quote from Make error log: Found value: null; expected type: number.

I replaced the router logic with an explicit field presence check, and hardcoded defaults for any new fields. No more silent failures since.

7. Avoiding automation loops when syncing discounts with Shopify

If a coupon or discount code is created in Shopify, and that triggers an automation to sync it into Airtable or Notion—or vice versa—you must avoid bi-directional loops. Especially when multiple staff are adding codes manually and not telling you.

I once had a loop that pinged every 3 minutes for new codes and pushed them back to Shopify if they weren’t tagged. But it didn’t check when the last update happened—so if a teammate edited a code title or usage limit, the automation thought it was “new” again and cloned it.

End result: duplicated discount codes with the same function, some labeled “copy-of-copy”.

Best practice I should’ve just done the first time:

  • Add a sync_origin field to each discount record (e.g. Airtable or Shopify UI)
  • Only sync if sync_origin !== automation
  • Store timestamps and diff against last sync time
  • Never create unless a UUID is missing, instead of just using name/slug matches

Loop detection isn’t built into any platform natively. You either build protection yourself or hit problems once live.

8. Why Make scenarios sometimes rerun after being manually stopped

This one’s subtle—and only burned me once, thankfully: I hit stop on a Make scenario halfway through a bulk update process. Nothing seemed broken at the time. Logs showed completed runs and some pending ones.

Next morning, random updates started hitting products seemingly from nowhere. Turns out if you hit “Stop” on a scheduled scenario, but the schedule queue is still processing, Make will attempt to rerun partial executions the next time the scenario switches back to active. Not exactly a retry—but more like unfinished queues coming back from the dead.

No visual indicator in the scenario window, just the faintest gray bar under history tab that says “Remaining executions.”

I now add a dummy module at the end of bulk loops—just an HTTP call to webhook.site—that I can watch. If I don’t see those firing each time, I know the loop got terminated early.