How to outsource data entry with micro tasks
When you outsource data entry, you usually picture hiring one person and handing over a spreadsheet. There is another way: split the work into hundreds of small, checkable pieces and let many people complete them in parallel. This guide shows how to split the work, write a spec people follow, measure accuracy with spot checks, and how the costs compare with a freelancer.
What data entry fits micro tasks
The test is simple: can a stranger complete one unit in a few minutes, with only your instructions, and can you check the result?
| Good fit | Poor fit |
|---|---|
| Copying product attributes (price, size, brand) from public pages | Bookkeeping that needs your accounting context |
| Transcribing scanned receipts, labels or forms you own (with no personal data) | Documents with customers’ names, addresses or IDs |
| Finding a company’s official website or public contact page | Building marketing lists of private individuals |
| Categorising items into a fixed list of categories | Categories that are still being defined |
| Checking whether listings or links are still live | Anything requiring logins to your internal systems |
Splitting data entry into micro tasks
The unit of work matters more than anything else. Too small (one field) and people spend more time loading pages than working; too big (500 rows) and one mistake-prone worker ruins a large chunk.
- Batch to 5–10 minutes. For example, 10 products per task. Time a batch yourself and price it by minute.
- Give every record a stable ID so answers map back to your sheet without ambiguity.
- Keep batches homogeneous. Same source, same fields. Mixed batches need mixed instructions.
- Share the batch in the task. Paste the IDs and source links in the steps, or link a read-only sheet or file per batch.
- Choose the proof format. A text answer with one line per record for short outputs; a file upload (CSV) for wider tables.
Two setups work well. For a handful of batches, post one task per batch, so the batch is part of the instructions. For many batches with identical instructions, post one task with as many worker slots as batches and link a sheet where each worker claims the next free batch by writing their username next to it. Allow repeats if you want good workers to keep going after their first batch.
Targeting and timing
Data entry rarely needs a specific country, but it does benefit from experience. A minimum approval rate of 90% and a minimum of 50 completed tasks filters out people who are new to following specs. If the source pages are in one language or show region-specific prices, target the countries where that content is shown correctly. Desktop targeting helps for wide tables and file uploads; phone users are fine for short lookups. Give each reservation a time limit that fits the batch (1 hour for a 10-minute batch) so abandoned batches return to the pool quickly, and choose a review period you can actually keep, since unreviewed submissions are approved automatically if auto-approve is on.
Writing the format spec
Most data entry errors are not typos. They are different people interpreting the same field differently. A spec removes the interpretation:
Format spec template
Output: one line per record: ID; price; currency; in_stock; source_url
- price: number with a dot for decimals, no currency symbol (e.g.
24.99). Use the sale price if shown. - currency: three-letter code (
USD,EUR). - in_stock:
yes,noorunknown. Never leave it blank. - source_url: the page where you found the price.
- If the page does not load: write
ID; NA; NA; unknown; broken.
Example: A-1042; 24.99; USD; yes; https://example.com/p/1042
Two worked examples, including one tricky case, save more mistakes than a page of rules. For writing steps and proof notes in general, see how to write a micro task.
Accuracy: spot checks and double entry
Known-answer records
Include one or two records per batch whose correct values you already know. Checking those takes seconds and tells you whether the rest of the batch deserves trust. Keep them indistinguishable from other records, and rotate them so they do not become common knowledge.
Spot checks
In addition to known answers, check a random sample of other records. A practical routine: check every record in the pilot, then a fixed share (say 10%) of each batch once accuracy is stable, and widen the check for any worker whose known answers are off. Measure field-level accuracy (correct fields ÷ checked fields) so a single bad column does not hide.
Double entry
For data that matters, have two different workers enter each batch and compare. Where they agree, accept; where they disagree, check yourself or send the record to a third person. It doubles reward cost but removes most of your checking time.
Handling mistakes fairly
| Situation | Action |
|---|---|
| Minor format slip across the batch | Request changes (once per submission) with the exact fix |
| A few wrong values, clear effort | Approve and correct; tighten the spec |
| Known answers wrong, values invented or copied | Reject with a reason that cites the spec |
| Identical output to another submission | Tasklify flags duplicate text and files; verify, then reject if copied |
Costs: micro tasks vs freelancers
On Tasklify you pay reward × workers + a 12% service fee. Worked example: 1,000 product records, 10 per task, about 10 minutes per batch at the suggested $0.70:
| Setup | Tasks | Total | Per record |
|---|---|---|---|
| Pilot (5 batches) | 5 | $3.92 | — |
| Single entry | 100 | $78.40 | 7.84¢ |
| Double entry | 200 | $156.80 | 15.68¢ |
| Optional verification of disagreements (150 × $0.35) | 150 | $58.80 | — |
Compared with hiring one freelancer:
| Micro tasks | Freelancer | |
|---|---|---|
| Pricing | Per unit, fixed before you start | Hourly or per project, negotiated |
| Speed | Parallel: many people at once | One person’s hours |
| Quality control | Proof per batch, known answers, double entry | Trust plus your own checks |
| Best for | High volume, simple, independent records | Judgement, context, ongoing ownership |
| Management | Writing the spec and reviewing | Hiring, briefing, communication |
Many teams combine them: micro tasks for the bulk, a trusted freelancer or employee for exceptions. The minimum top-up is $10, enough for the pilot above. See pricing for details.
Data you should not outsource
Anyone can reserve a public task, so treat task content as public. Do not share customers’ personal data, health or financial records, passwords or confidential business documents. Mask or remove those fields, or keep that work in-house. The Acceptable Use Policy prohibits processing third parties’ personal data without a lawful basis and unauthorised data collection, which rules out scraping private individuals’ contact details.
Frequently asked questions
What kinds of data entry can be outsourced as micro tasks?
Work that splits into small, independent units with a clear right answer: transcribing receipts or forms you own, copying product attributes from public web pages, finding a company website or public contact page, categorising items, and checking whether listings are still live.
How accurate is crowdsourced data entry?
Accuracy depends mostly on the task design: a precise format spec, examples, known-answer records and review. Double entry, where two people enter the same record and you compare, catches most slips because two people rarely make the same mistake.
Is it cheaper to outsource data entry to micro tasks or to a freelancer?
For large volumes of simple, independent records, micro tasks are usually cheaper and much faster because many people work in parallel and you pay per record. For work that needs judgement, context or ongoing communication, a single freelancer is often the better fit.
Can I outsource data entry that includes customer personal data?
Avoid it. Sharing third parties’ personal data with unknown workers needs a lawful basis and safeguards, and Tasklify’s Acceptable Use Policy prohibits processing third parties’ personal data without one. Remove or mask personal fields first.
How is data entry priced on Tasklify?
Each task has a reward per worker; you pay reward times workers plus a 12% service fee. Group records into batches so each task takes 5–10 minutes and price it using the per-minute rate.