How B2B and wholesale Shopify merchants can fully automate order intake. From PDF and email purchase orders to Shopify draft orders end to end.
If you operate a wholesale, B2B, or manufacturing-focused Shopify store, you've probably received purchase orders by PDF or email. Manually retyping these orders into Shopify isn't only slow, it introduces mistakes, delays fulfillment, and frustrates customers who expect rapid processing.
Every PDF takes 2 to 10 minutes to handle manually. Multiply that by daily volume and it becomes a real operational cost.
Tools like LevelOps PDF to Order automatically extract key order fields from PDF and Excel files, customer name, SKUs, quantities, shipping address, and convert them into Shopify draft orders instantly. No configuration, no manual mapping.
The ROI is straightforward: if your team processes 20 orders per day at 5 minutes each, that's over 1.5 hours daily saved. At scale, that's a full FTE worth of capacity redirected toward higher-value work.
Beyond time savings, automation eliminates the human errors that cause fulfillment issues, customer complaints, and costly corrections downstream.
If you operate a wholesale or B2B Shopify business, PDF automation isn't a luxury, it's a competitive advantage. The best solutions install in minutes, require no IT involvement, and start delivering ROI from day one.
Maxime Lavoie
Founder & CEO, LevelOps
Industrial engineer by training. Former Deloitte supply-chain consultant. Former VP Operations at Goodfood Market. Now writes the ERP, MRP and B2B order playbooks he wishes had existed in 2018.
Product guides
Manual order entry costs B2B wholesale merchants hours every week. Learn how to automate PDF purchase order processing in Shopify with AI.
Product guides
Step-by-step guide to converting PDF and email purchase orders into Shopify draft orders automatically, without manual data entry.
Product guides
The complete guide to building your Shopify product catalog for B2B wholesale, from product structure and SKUs to company pricing and automation.
The ones needed to build the order: the customer, the line items with their quantities, and the shipping address. Each line is then matched against your Shopify catalog and priced against the company and price list that account is attached to, so B2B contract pricing is applied without anyone looking it up.
No. There is no template to build for each buyer, so orders are read in whatever layout arrives, including PDF attachments, email text and spreadsheets. The one setup step is a catalogue sync that runs once and takes about two to five minutes depending on variant count. New customers need no extra work after that.
The order lands as a Shopify draft with the source file attached, and a person approves it before anything is finalised. That review step is the control, and it earns its keep: a single erroneous order costs about $250 to unwind once you count the pick, the freight, the credit note and the call. Measured error rate with LevelOps is 0.5% against 3% for manual entry.
Two numbers do most of the work, and your team can sanity check both on their own orders. Handling one order manually takes about six minutes against about one minute with LevelOps, and the error rate is 0.5% against 3%, which is six times fewer. Multiply the time gap by your weekly volume, then add the roughly $250 each wrong order costs to unwind.
No. It installs from the Shopify App Store in about two minutes, the catalogue sync runs itself, and nothing changes in your store or on your customers' side. The people who need to be involved are the ones processing orders today, since they are the ones reviewing the drafts.
The daily volume in the example is illustrative, so check your own case on the per order figures: about six minutes manually against about one minute. At lower volume the cost of errors usually matters more than the time saved. Your first 5 successful orders are free with no expiry, which is enough to test on real POs before deciding.
Book a short demo with a real purchase order and we run it live on your own data.
