Ecommerce data entry and store operations, outsourced

Ecommerce data entry outsourcing covers more than listings. Behind every online store sits a queue of repeatable work: products to load, prices to update, orders to fix, returns to process and reviews to check. Deepen AI's team does that work in your store admin and seller accounts, to your written rules.

Who this is for

This page is for brands selling direct and on marketplaces, multi-channel retailers, and marketplace sellers whose operations team is small compared with their SKU count and order volume. Ecommerce work also peaks: new collections, sale events and the holiday season. A managed team that already knows your rules is easier to grow for a peak than a group of new temporary hires, and the same team lead stays your contact all year.

What our team does, by area

Catalog

• Build new listings and variants from line sheets. See ecommerce product data entry.
• Keep prices, stock and categories current. See catalog data management.
• Fill missing attributes and fix titles. See product data enrichment.

Orders and returns

• Process returns, exchanges and refunds in your admin panel, within limits you set
• Fix order errors, such as a wrong address or a missing item, using your written process
• Tag orders and customers for your reports

Reviews and messages

• Check product reviews for spam and policy breaks before they publish. See content moderation outsourcing.
• Tag reviews by product issue, such as sizing, quality or shipping, so merchandising sees the pattern
• Sort the shared inbox and buyer messages by type, and route each to the right person

Suppliers and research

• Key supplier invoices and packing lists, and match them to purchase orders
• Collect public prices and product details from other stores into a sheet

Platform access

On Shopify, we work on staff accounts. On Amazon Seller Central and Walmart Seller Center, we work through the user permissions you grant. In each case you choose what the account can see and do.

How it runs

1. You share your rules and examples. Send the written process for each task, such as your returns policy, title rules or inbox rules, with a few finished examples.
2. We agree scope and train. Our ops team sets the people and hours in your pilot plan. The team trains on your examples, and we build a gold set of known-correct cases for you to confirm.
3. We deliver, with a named team lead and QA sampling. The team works your live queues. The team lead keeps a decision list and sends anything outside your rules to your contact.
4. You get a weekly report. Hours by task, items done, QA sample results and open questions.

Illustrative example: a return processed to your rules

Illustrative only. The order, product and rules are invented.

• Input, return request RMA-5512: order #10433 · Women's Rain Shell, Navy, size M · reason "too small" · delivered 12 days ago
• Input, your rules: free exchange up to 30 days after delivery if unworn · refunds over 150.00 go to your team · tag every sizing return
• Output, action: exchange to size L created in the admin panel. Size L is in stock.
• Output, refund: none, exchange only
• Output, tags: "sizing-runs-small" added to the order and to the product notes
• Output, report note: third "too small" return for this product this week. Listed for your merchandising review.
• Who did what: one team member processed the return. It was not in this week's QA sample.

How we keep store work accurate

Store work goes wrong when people improvise, so the team follows your written rules and sends anything outside them to the team lead. Gold cases measure each person before and during live work. QA reviewers re-check a sample of finished items, such as returns, listings or review decisions, against your rules. They do not re-check every item. The weekly report shows the acceptance rate on the sample for each task. See how we check quality.

Pricing scope

Ecommerce data entry and store operations work in English are standard tasks at $5 per person-hour, with a named team lead and QA sampling included. One team can split its hours across several tasks, and the weekly report shows where the hours went. Work starts with a two-week prepaid pilot: people × hours per week × 2 weeks × $5, with at least 20 hours per person per week. After the pilot, we invoice weekly in arrears. Other languages and work that needs specialist knowledge are quoted after our ops team reviews the task. See the pricing page.

When to use the enterprise team instead

If you are training a model to inspect returned items from customer photos, or to recognize products on a packing line camera, the training data needs computer vision annotation. That is work for the Deepen AI enterprise team, scoped and priced per project. See enterprise AI data services.

Tell us your platforms and the tasks that eat your week. We email you a pilot plan with a quote.

Request a pilot plan