Bundle Builder from Co-Purchases
Finds what customers actually buy together, proposes 3-5 margin-checked bundles, and drafts the listings — staged for the owner.
Turns a hunch about what sells together into an evidence-backed proposal set. It reads completed order history, computes co-purchase frequency and lift (returns-adjusted, trivial pairs filtered), and shapes the strongest pairs into at most 3-5 bundle candidates — each citing the co-purchase rate and order count behind it. Pricing runs through the margin policy with the math on the table; below-floor pricing is flagged, never silently proposed. Listing copy, bundle structure, and the rollout notes are drafted in full, then the whole package stages for the store owner — payloads and copy only, no store writes until the owner approves.
How it runs
Multi-agent orchestration — here's the flow, step by step.
Pull completed order lines for the window, with returns and cancellations noted so pair stats stay honest.
ecommerce scannerCompute co-purchase frequency and lift; filter trivial pairs.
data analystShape the strongest pairs into 3-5 bundle candidates, each with its evidence table.
upsell finderPrice each bundle within the margin policy, flagging below-floor results.
pricing analystWrite the listing copy per bundle from the real component SKUs.
product description writerDefine the bundle structure — components, variants, image plan, catalog placement.
catalog optimizerVoice pass across all bundle copy.
brand voice agentAssemble the owner package with evidence tables and pricing math; dedupe against prior proposals.
workflow orchestratorStage the payloads and archive the proposal; nothing touches the store until approved.
distributorRequired Agents
9- ecommerce-scanner
- data-analyst
- upsell-finder
- pricing-analyst
- product-description-writer
- catalog-optimizer
- brand-voice-agent
- workflow-orchestrator
- distributor
Connections
Required
Optional
What it does
- Co-purchase frequency and lift computed from real order history
- 3-5 bundle candidates, each citing its evidence
- Margin-checked pricing with the math shown per bundle
- Below-floor pricing flagged, never silently proposed
- Listing copy and bundle structure drafted per bundle
- Returns-adjusted pair statistics
- Idempotent per analysis window — proposals dedupe on rerun
- Staged payloads only — no store writes without approval
Example prompt
Look at the last 90 days of orders, find what customers buy together, and propose a few bundles with pricing that protects my margin — draft the listings for my review.
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