Your First AI Commerce Workflow
Choose a repeatable ecommerce task, test it with real inputs over five days, and hand off a workflow your team can verify.
Start with an ecommerce task your team repeats every week, can review against a source, and can correct before it reaches customers. Product data extraction, support reply drafts, and a weekly operations summary are good starting points. Give the pilot one kind of input and one deliverable that another person can check.
Find the delay in your existing process
Look back at a week of work. Find the point where people spent time reformatting files, searching for facts, or asking the same question. Ask what a colleague needs to see to know that step is done. If listings stall because dimensions and accessories live in different files, produce a draft product sheet with a source next to each value. If the support team repeatedly looks up return terms, produce reply drafts from approved material for the person who checks the live order and sends the reply.
Run a five-day pilot
On day one, complete one real instance manually. Save the deliverable and note the time. On day two, try the workflow on previously completed inputs and compare the results with the approved versions. On day three, have a teammate review the output and source links independently. Record each correction. On day four, try a record with a missing or conflicting fact and see whether the process stops for clarification. On day five, ask another teammate to start from the original files. Compare the time, including review, and the amount of rework before deciding whether to keep using it.
Write the review checklist before choosing a tool
Use four columns for the source, expected output, check, and reviewer. For the product sheet, every dimension should point to a spec sheet or measured photo. Flag missing or conflicting values for the product owner. Keep control over pricing, inventory, and publication with the existing owners. If the source includes customer records, check which data the team has authorized for the tool before you upload it.
Use public examples to define a small first output
SCTCamp publishes a sample video production queue and a GMV Max campaign report. Choose the example closest to your work and use a single section to clarify your first deliverable. Once the process holds up across repeated runs, document the trigger, inputs, checks, and sample outputs so the next person can repeat it. Video production queue · GMV Max campaign report · How to write an agent skill