Shopify and the App Store can automate a huge amount of running an ecommerce business, but I’m guessing there are still tasks that merchants handle manually, in spreadsheets, or by moving information between different apps.
What’s one task in your Shopify business that you still manage manually and wish you didn’t have to?
It could be something you do daily, weekly or even once a month.
I’m especially interested in things where you find yourself thinking:
“Surely there should be an easier way to do this.”
If you’re comfortable sharing, I’d also love to know:
1. What are you doing manually? 2. How often do you do it? 3. What do you currently use — spreadsheet, another app, Shopify, etc.?
I’m trying to understand where the biggest operational friction still exists for Shopify merchants rather than assuming what the problems are.
Thanks — genuinely interested to see what comes up.
When store owners list their most tedious “manual spreadsheet tasks,” two specific catalog maintenance workflows consistently consume 80% of the manual labor:
Variant Image Formatting & Deduplication: For a product with 5 colors × 4 sizes = 20 SKUs, assigning the correct color photo across all size rows in CSVs takes significant spreadsheet manual labor. Leaving secondary size rows blank assuming inheritance breaks variant image mapping on import.
Supplier WebP Binary Transpilation: Supplier catalog feeds (especially from Asian manufacturers like 1688/Alibaba) frequently contain raw .webp image links or dynamic CDN parameters. Shopify’s background CSV importer quietly skips downloading WebP binaries without throwing an error log, leaving blank variant images on import.
Multi-Store Attribute Synchronization: Copying CSVs between Store A and Store B without sanitizing product Handles overwrites existing attributes or corrupts variant-image mapping when option arrays differ.
If you want to automate these spreadsheet tasks locally without relying on expensive cloud middleware, consider using EasyCatch (a client-side Chrome extension). Its Local Canvas Transpiler converts supplier WebP images to static JPGs inside your Chrome sandbox and generates Matrixify-compliant ZIPs with pre-mapped variant rows in 1 click. 100% Local-First so store catalog data stays completely private.
Thanks, this is exactly the kind of workflow I was hoping to understand.
When you say bulk updates become painful, which one causes the most trouble in practice — price changes, inventory, tags/metafields, or collections?
And is the main problem that Shopify’s bulk editor is too limited, or that merchants still have to figure out which products need changing before they can make the update?
I’m especially interested in whether the bigger pain is doing the repetitive work or deciding what needs attention in the first place.
Thanks! That’s exactly what I’m trying to do — understand the actual workflows and recurring pain points first rather than starting with a solution and looking for validation.
Hopefully the responses here surface a few problems that merchants are still solving manually despite all the apps available
Thanks for the detailed examples. The variant-image and multi-store synchronization issues are interesting.
Since you seem to work quite closely with these CSV/catalog workflows, I’m curious — are these problems you’re seeing repeatedly across different Shopify merchants, or are they more common with certain types of stores such as large catalogs, fashion/variants, dropshipping, or multi-store setups?
And when merchants run into these issues, what tends to be the bigger pain: fixing the CSV/import itself, or discovering the errors only after products have already been imported incorrectly?
I’m trying to distinguish between problems that are technically frustrating and problems that actually consume significant merchant time or cause measurable business impact.
@vedasuite — Great questions! From what we see across merchant testing:
Where it happens most: It’s heavily concentrated in Fashion/Apparel (high variant density per product, e.g. 5 colors × 4 sizes = 20 SKUs) and Dropshipping/Multi-supplier catalog sourcing (where product feeds originate from Asian platforms like 1688/Alibaba with raw WebP URLs).
What causes more headache (Pre-import vs Post-import): Post-import discovery is 10x more painful. When a merchant imports 500 variants and only discovers hours later that variant images dissociated or blanked out across live storefronts, un-linking and re-importing clean sheets requires CSV snapshot archaeology.
That’s precisely why pre-normalizing image formats and variant mapping locally before hitting the import button saves so much time!
One area that seems to create a surprising amount of manual work is keeping inventory aligned when a business operates across multiple stores, channels, or customer groups.
For example, a merchant might have a DTC store and a wholesale store using the same products. Even when both are connected to the same inventory, they may still need to export data, compare stock levels, make manual adjustments, or check whether an order from one channel has affected what can be sold through another.
It doesn’t necessarily happen every day, but when it does, it can become quite time-consuming—especially when there are a lot of SKUs involved. The bigger problem is that manual processes like these can also introduce small errors that aren’t immediately obvious until they result in an oversell or an inventory discrepancy.
I’ve come across this quite a bit through conversations with merchants while working on Easify Inventory Sync. Interestingly, many merchants don’t initially describe this as an “inventory problem.” They describe it as having to repeatedly check, copy, reconcile, and update information between different places.
I think that’s an important distinction. Sometimes the biggest opportunity for automation isn’t replacing one big task, but eliminating all those small repetitive steps that merchants have become accustomed to doing manually.
I’d be interested to hear what others are still maintaining in spreadsheets or manually moving between Shopify and other apps. Those seemingly small tasks can probably add up to a lot of time over the course of a month.
Thanks, this clarifies it really well. The distinction between the import itself and discovering errors only after hundreds of variants are already live is particularly useful.
It sounds like the real cost isn’t just the CSV work — it’s the cleanup and rework when something goes wrong at scale.
Also interesting that this seems concentrated in high-variant and multi-supplier catalogs rather than being an equally common problem for every Shopify store.
Thanks — the distinction you made between an “inventory problem” and a “repeated reconciliation problem” is really interesting.
From the merchants you’ve spoken with, when inventory gets out of sync across stores or channels, what is usually the biggest consequence?
Is it mainly:
Overselling / cancelled orders
Incorrect stock availability
Time spent manually reconciling
Purchasing or replenishment mistakes
Or something else?
And do merchants generally want the systems to stay synchronized automatically, or do they still want human approval when a discrepancy is detected?
I’m trying to understand whether the bigger opportunity is automating the repetitive work or detecting the problem early and telling the merchant what needs attention.
@vedasuite — Exactly! You hit the nail on the head: the real cost is the cleanup and rework after live storefronts break.
Pre-normalizing image formats and variant mapping locally before hitting import is what turns a massive post-import cleanup into a 1-click seamless upload. Appreciate the great discussion!
From the thread so far, the most frequent consequence seems to be what Easify-Jennifer highlighted: merchants discovering inventory drift after it’s already affected orders, then spending time unraveling what went wrong and what needs to be resynced. That’s the chronic cost eating merchant time.
The automation vs approval question is interesting because no one’s directly addressed it yet. Merchants probably split based on catalog complexity: if a single inventory error is low-cost, automatic sync works fine. But for larger catalogs where a mistake ripples across hundreds of SKUs or multiple suppliers, merchants likely want the system to surface what changed so they can verify before the sync commits, rather than discovering the problem after orders are already affected.
That might be the real bottleneck: not keeping inventory in sync, but knowing what changed and having confidence in the decision before applying it.
