Analysis / Ecommerce and retail
Discover products commonly purchased together
Find supported product pairs in uploaded order lines using basket frequency and lift, excluding existing bundles before proposing crosssell ideas.
Ecommerce operator · Retail analyst
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Your starting prompt.
Use [uploaded order line data] to identify product pairs and category combinations purchased together. Calculate pair frequency, support, confidence and lift for [period], excluding canceled orders and existing bundles under [rules]. Apply [minimum support] and show base purchase rates. Produce a merchandising review with candidate crosssell combinations; do not assume frequent pairs will generate incremental sales if promoted.
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Method and review
Keep the assumptions visible.
Reconcile orders, refunds, costs and fulfillment at a consistent grain. Use supplied exports when a native Connection is unavailable, and distinguish revenue from contribution.
For this task, check
Existing bundles and promotions can mechanically create co purchase patterns.
This starting prompt has no published worked example yet. Begin with a small sample and check the calculations before relying on the result.
Before you begin
- Bring exports you are allowed to upload, or data your Workspace can already query.
- Choose the reporting period and agree what each record represents.
Work with permitted files or queryable data. Verify the result against the original records.
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Make it your investigation.
Copy the prompt above, create or open your Workspace, and paste it into Chat. Add the inputs you have permission to use and adapt the assumptions with your agent.
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