An ACBuy spreadsheet can save you hours of searching, but only if you know how to read it — and how to tell when its data has gone stale. This guide explains what these sheets contain, how to interpret each field, how to estimate the real cost of an item, and when a different discovery method serves you better.
Overview
An ACBuy spreadsheet is a structured list of product links from Chinese marketplaces — typically Taobao, Weidian, and 1688 — organized so shoppers can browse, compare, and prepare items before ordering through the ACBuy or AllChinaBuy agent workflow. Public descriptions of these sheets consistently mention columns for product links, prices in CNY, seller notes, and estimated shipping costs. Quality varies enormously by maintainer, so treat every sheet as a starting point for research, not a vetted catalog.
The context matters here: ACBuy operates as a shipping agent — a middleman that purchases items on your behalf rather than selling products itself, as creator tutorials such as this ACBuy walkthrough explain. The spreadsheet is a community or creator artifact layered on top of that workflow. Some are huge: one site claims a collection of over 2,000 ACBuy finds with QC photos and USD prices, and Reddit threads have circulated sheets advertising 1,500+ links across shoes, clothes, accessories, and electronics.
That scale is exactly why evaluation skills matter more than finding the “biggest” sheet. A spreadsheet is only as useful as its freshest row, and most public sheets do not tell you when each row was last checked. The rest of this article treats an ACBuy spreadsheet the way a careful user should: as a working dataset with fields to interpret, costs to model, and failure modes to watch for.
What an ACBuy spreadsheet usually contains
An ACBuy spreadsheet differs from a simple list of links, a social media post, or a Yupoo album because it carries structured fields alongside each link. A finds page or Instagram post gives you a photo and a link; a spreadsheet gives you comparable columns — price, seller, category, notes — that let you filter and sort. Maintainers describe the goal the same way: organizing products in one place so you can browse faster and build hauls more efficiently, usually grouped into categories like shoes, hoodies, jackets, and accessories.
The catch is that structure is not the same as accuracy. A sheet can have beautiful columns and dead links. Knowing which fields to expect — and which ones are missing — is the fastest way to judge whether a sheet was built for readers or just for clicks.
Core fields to look for
A usable ACBuy spreadsheet should carry most of these columns. If several are missing — especially the last-checked date — treat the sheet as a lead generator, not a reference.
- Item name — a plain description, ideally with size or colorway noted
- Category — shoes, hoodies, accessories, electronics, and so on
- Source marketplace — Taobao, Weidian, or 1688
- Product URL — the actual listing link, not just an agent redirect
- Seller — shop name or ID, so you can spot seller changes
- Price — with currency stated (sheets commonly list CNY or USD)
- Batch / version — which production run or variant the row refers to
- QC photo link — photos of an actual received item, if available
- Last checked date — when someone last confirmed the link and price
- Status — active, out of stock, dead link, replaced
- Shipping estimate — estimated weight or shipping cost, clearly labeled as an estimate
- Notes — sizing advice, risks, or caveats from the maintainer
Not every sheet will have all twelve, and that is fine. What is not fine is a sheet with no currency labels, no dates, and no way to tell whether a row was checked last week or last year.
Annotated sample row
Here is a worked example of a single row, using realistic values, so you can practice reading one before you click anything. Imagine this row in a public sheet:
Item: Running shoe, grey/white · Category: Shoes · Source: Weidian · URL: weidian.com/item/… · Seller: Shop 88 Sports · Batch: “V2, spring batch” · Price: ¥268 CNY · QC photos: link to album · Last checked: 2026-05-14 · Status: Active · Est. shipping weight: 1.2 kg · Notes: “Runs half size small”
Read it in this order. First, the last checked date: 2026-05-14 means someone confirmed this row within recent weeks — old enough that the price could have drifted, recent enough to be worth opening. Second, the price and currency: ¥268 is the item price only; it excludes domestic shipping to the agent warehouse, international shipping, and any fees, so the real cost will be meaningfully higher. Third, the batch note: “V2, spring batch” tells you which version the QC photos represent — if the seller has moved to a newer batch, those photos may no longer describe what you would receive. Fourth, the seller name: if the URL opens to a different shop than “Shop 88 Sports,” the listing has likely been repurposed and every other field in the row is suspect. The constraint to internalize: a row is a snapshot, and every field is only as reliable as the date next to it.
How to use an ACBuy spreadsheet without treating it as proof
The practical mistake most new users make is treating spreadsheet data as verification. A row is a claim made by a maintainer at some point in the past; your job is to re-check the parts that matter before money moves. The sequence below keeps that discipline without turning every purchase into a research project.
A reasonable mini-workflow looks like this:
- Filter or scan by category and price to shortlist candidate rows.
- Open the source link and confirm the listing matches the row’s item, seller, and price.
- Read batch/version notes and any linked QC photos.
- Estimate the full landed cost (covered in the next section).
- Order through the agent, then review warehouse QC photos before approving shipment.
Each step deserves a little unpacking.
Start with category, price, and source link
Filtering is where a spreadsheet genuinely beats scrolling social feeds: you can sort a thousand rows by category and price in seconds. Shortlist a few rows, then open each source link and compare what you see against what the sheet claims. If the listed price was ¥268 but the live listing shows ¥329, the row is stale — note it and re-evaluate rather than assuming the old price will be honored. The rule is simple: the spreadsheet gets you to the listing quickly, but the listing is the source of truth.
Check batch, version, seller, and QC photos
Batch and version notes describe which production run a row refers to, and QC photos show what one buyer actually received from that run. Both are useful evidence, but neither guarantees the item currently sold is identical: sellers change suppliers, batches rotate, and visually similar items from different factories can vary in quality. Check that the seller name in the sheet matches the live listing, and treat QC photos as describing a past order, not a promise about yours. If the batch note is vague or absent, price in that uncertainty rather than ignoring it.
Decide what to do after warehouse QC
Ordering through an agent gives you one real checkpoint: when the item arrives at the warehouse and QC photos are taken, you decide what happens next before international shipping. Compare those photos against the spreadsheet’s QC link and the original listing — check the model, colorway, size tag, stitching, and any flaw the maintainer’s notes warned about. If something does not match, use whatever options the platform offers — asking questions, requesting an exchange or return where supported — instead of shipping an item you already doubt. This decision point is the single biggest advantage of the agent workflow, and a spreadsheet is only useful if it helps you use it well.
A simple landed-cost model for spreadsheet items
The listed item price is not the total cost. A ¥268 pair of shoes can easily double in real terms once domestic shipping, international shipping, and potential customs charges are added, which is why sheets that show only item prices systematically understate what you will pay. Building a small cost model in your own sheet takes five minutes and prevents the most common budgeting mistake in haul planning.
Fields for estimating total cost
Add these columns next to any row you are seriously considering:
- Item price — in the listing currency, converted at the current rate
- Domestic shipping — seller to agent warehouse
- Agent / service costs — where applicable on your platform and order type
- International shipping estimate — from the platform’s shipping estimator, by weight and line
- Packaging / insurance — optional extras if you select them
- Exchange-rate buffer — a small margin for rate movement between quote and payment
- Estimated customs / tax — an allowance for your destination, which you cannot fully predict
- Coupons / credits — subtract only ones you have actually confirmed
Every one of these should be re-checked at order time. Estimators, fees, and promotions change, and a spreadsheet estimate is a planning number, not a quote.
Example formulas
If your columns are laid out as Item price (B), Domestic shipping (C), Agent/service costs (D), International shipping (E), Packaging/insurance (F), Customs/tax estimate (G), and Coupons (H), the core formula is:
Estimated total = B + C + D + E + F + G − H
In spreadsheet syntax: =B2+C2+D2+E2+F2+G2-H2. Two supporting formulas make comparisons easier. Cost per kilogram — =E2/W2, where W is chargeable weight — helps you compare shipping lines and decide whether consolidating items into one parcel improves the rate. And a share-of-total check — =E2/(B2+C2+D2+E2+F2+G2-H2) — shows what fraction of your spend is shipping; for light, cheap items it is often the dominant cost, which changes what is actually “a good deal.” Treat all outputs as estimates until the platform shows you real numbers at checkout.
How to judge whether an ACBuy spreadsheet is reliable
A good ACBuy spreadsheet is useful only if you can tell when the data was checked and by whom. Popular sheets advertise scale — 2,000+ finds on one aggregator site, 1,500+ links in Reddit-shared sheets — but scale says nothing about freshness or honesty. Before relying on any sheet, run through a short checklist:
- Update date — does the sheet state when it was last updated, and do individual rows carry last-checked dates?
- Link health — spot-check five random links; if two or more are dead, assume widespread rot.
- QC photo availability — are QC links present and do they open, or are they placeholders?
- Price currency — is every price labeled CNY or USD, and do labels match the live listings?
- Batch clarity — are versions and batches named, or does everything just say “best batch”?
- Seller consistency — do seller names in the sheet match the shops the links open to?
- Duplicate control — are the same items listed multiple times at different prices?
- Transparent notes — does the maintainer disclose affiliate links, referral coupons, or selection criteria?
That last point matters more than it looks. Many sheets and finds sites are monetized — the aggregator above, for instance, advertises ¥1,000 in coupons for signing up through its link, and creator tutorials commonly bundle referral signup offers. Monetization does not make a sheet useless, but it means “best finds” may reflect what pays the curator, not what serves you.
Be careful with “verified” claims
Words like verified, hand-picked, and QC’d carry no fixed meaning in a spreadsheet. They are only useful if the sheet answers four questions: who checked the item, what exactly was checked (the link, the seller, a received product?), when the check happened, and whether the current listing still matches what was reviewed. A row marked “verified” with no date and no named checker is a marketing label, not evidence. When those four answers are missing, downgrade the claim mentally to “someone liked this at some point” and do your own listing check.
Watch for stale links and seller changes
Spreadsheet rows decay in predictable ways. Links die when listings are removed; sellers repurpose old listings for entirely different products, so a link that once pointed to one shoe can silently start selling another; prices drift; batches change while old QC photos keep circulating; and duplicate rows accumulate as maintainers paste without pruning. The worst failure mode is the static export: sheets saved as PDFs or copied snapshots keep circulating on Reddit and Discord long after the original stopped being updated, feeding new users outdated prices and dead sellers. If a sheet has no visible update mechanism, assume it is already partly a static export.
ACBuy spreadsheets vs other ways to find products
A spreadsheet is one discovery method among several, and it is not always the best one. Spreadsheets excel at fast, structured browsing; communities excel at recent feedback; direct marketplace search excels at freshness. The matrix below summarizes the trade-offs so you can pick deliberately rather than defaulting to whichever link you saw first.
| Method | Browsing speed | Freshness | Trust signals | Effort required | Best for |
|---|---|---|---|---|---|
| ACBuy spreadsheet | Fast — sortable columns | Varies; depends on maintainer | Weak unless dates and criteria are shown | Low | Quickly shortlisting candidates by category and price |
| Reddit finds threads | Medium | Good — dated posts and comments | Comment feedback and vote counts | Medium | Recent community reactions to specific items |
| Discord communities | Medium | Good — live discussion | Direct answers, but hype-prone | Medium | Asking questions about a specific item or seller |
| Direct Weidian/Taobao/1688 search | Slow | Best — live listings | Marketplace reviews and seller history | High | Verifying anything before purchase |
| Yupoo albums | Medium | Varies | Photos only, minimal structure | Medium | Visual browsing of a single seller’s range |
| Agent find directories | Fast | Varies; check update claims | Often affiliate-driven | Low | Broad category browsing with QC photos |
The practical pattern most experienced users settle on is hybrid: use a spreadsheet or directory to shortlist, a Reddit or Discord thread to sanity-check recent experiences, and direct marketplace search to verify the live listing before paying. No single source needs to be perfect if each covers the others’ weaknesses.
When a personal spreadsheet is better than a huge public sheet
A 1,500- or 2,000-link public directory is built for browsing, not for deciding. Once you have shortlisted a handful of items, a small personal sheet does the jobs a mega-sheet cannot: tracking your budget against estimated landed costs, ranking items by priority, recording QC status per order, and — crucially — creating a waiting period between wanting something and buying it. Staging a haul in your own sheet is a natural anti-impulse mechanism: items sit in rows until you have compared total costs and, ideally, seen QC results.
A personal sheet also holds data no public sheet ever will: your own refund history, seller responsiveness, actual shipping weights and transit times, and which past purchases you regretted. Over a few hauls, that private record becomes more valuable than any public directory, because it is verified by the only checker who matters for your money — you.
A haul-planning layout you can copy
A compact personal layout needs only eight columns:
- Priority — 1–3, forcing you to rank instead of accumulating
- Item URL — the live listing link
- Price — converted to your currency, with the date of conversion
- Estimated weight — for shipping math
- QC status — not ordered / awaiting QC / QC approved / rejected
- Decision — buy, wait, drop
- Total cost estimate — using the landed-cost formula from earlier
- Notes — sizing, batch, and anything a future you should remember
If you want to share a curated version of your sheet — say, a cleaned-up list of items you have personally received and QC’d — you can publish the file itself rather than passing around edit links. TablePage, for example, lets you drag and drop CSV, TSV, XLSX, or XLS files and instantly generates a public dataset page, where anyone can explore charts, insights, and a filterable table with no signup needed. Publishing a snapshot this way keeps your working sheet private while giving others a filterable, read-only view — which also sidesteps the open-edit-link chaos that has degraded more than one community sheet. For a sense of what a published sheet looks like, TablePage’s example dataset pages show the interactive table-plus-charts format.
Risk checks before you order
Spreadsheet links carry risks that no column can fully capture, so run a short mental audit before paying. First, link safety: confirm the URL actually points to the marketplace it claims — impersonation pages mimicking Weidian or Taobao listings exist, and a spreadsheet row is only as safe as the link behind it. Second, seller reliability: a sheet can tell you a seller was good months ago; it cannot tell you they still are, so check live marketplace reviews and recent community feedback.
Third, photo honesty: both listing photos and old QC photos can misrepresent what ships today, especially when batches change. Fourth, payment caution: use the payment methods your platform officially supports, and be skeptical of any spreadsheet note steering you to off-platform payment. Fifth, customs and tax: import charges depend on your country, the declared value, and the category, and no spreadsheet can promise a customs outcome — budget for the possibility rather than assuming zero.
Finally, be honest about the legal dimension. Some items circulating in finds sheets raise brand and intellectual-property concerns, and some categories draw more customs scrutiny than others. This article cannot tell you what is lawful to import where you live, and neither can a spreadsheet; if a row’s notes wave away those questions, that is a reason for more caution, not less.
Frequently asked questions
The questions below cover the loose ends most readers still have after learning the core workflow. Each answer stays within what public sources actually support.
Is ACBuy the same as AllChinaBuy?
The two names are frequently discussed together — spreadsheets and guides often carry titles like “AllChinaBuy (ACBuy) Spreadsheet,” and community pages treat the terms as closely linked. Rather than relying on a spreadsheet’s naming, check the actual platform you are creating an account on: confirm its official domain, its fee structure, and its QC and shipping options directly. Whatever the branding relationship, your obligations and protections come from the platform you transact with, not from how a third-party sheet labels it.
How often should an ACBuy spreadsheet be updated?
There is no universal rule, but data-quality logic gives a practical answer: update frequency should match how fast the underlying data changes. Marketplace listings, prices, and stock change weekly or faster, so a sheet that has not been touched in months is likely carrying a meaningful fraction of dead or drifted rows. For maintainers, the highest-value habit is a per-row last-checked date plus periodic pruning of stale entries; for readers, the highest-value habit is checking that date before trusting anything else in the row. One large aggregator signals this by displaying a page-level update date — its page shows a “last updated” stamp — though a page-level date is weaker evidence than row-level dates.
What should I do if a product link is dead?
Mark the row as stale first, so you do not re-click it later — and so others do not, if the sheet is shared. Then try to relocate the item: search the same marketplace by the seller’s shop name, or use image search with the row’s product photo if you have one. If you find a candidate replacement, treat it as a new, unverified listing — the old price, batch notes, and QC photos belong to the dead link, not the new one. Never carry old data forward to a new URL without re-checking it.
Do QC photos make a spreadsheet item safe to buy?
No — they reduce uncertainty, but only about one specific item at one point in time. QC photos in a spreadsheet show what a previous buyer received from a previous order; they do not guarantee the seller’s current stock matches, that the batch has not changed, that your customs outcome will be smooth, or that the item is legally unproblematic to import where you live. Use them as one input alongside a live listing check, recent community feedback, and your own warehouse QC photos — the only photos that actually depict your item before you commit to shipping it.