Leads arrive through several forms and shared inboxes, and nobody can say who owns them once they land. In this case, the immediate task is to build a qualified lead generation workflow. The end result should be a qualified prospect shortlist with evidence and next steps checked against the fields the store can capture today.
First replace every [bracketed] placeholder with real store scope and constraints, then add any actual records or data you have, and paste it into your preferred AI assistant or Spark agent. Spark will follow this page's workflow to produce structured output and verification steps.
Act as a Shopify operations specialist.
Help me build a qualified lead generation workflow.
My store context is [describe the business, products and target audience].
My scope is [specify the affected products, pages, customers or reporting period]. Use these inputs: [every lead entry path with the fields it actually captures, the owner per source, the qualification rules the team accepts, the destination system for those records, and the consent rules the merchant has stated].
Build the capture path around the fields the qualification rules need and the ones the store can reliably record, dropping any step that depends on data the store cannot capture, and define the owner, the routing trigger and the first response for each qualified record.
Return the qualified lead workflow with shortlist evidence and next steps, checked against the merchant's records for the specified task.
Show the relevant evidence or before-and-after examples and explain how I can verify the result.
If essential data is missing, ask for it and mark unsupported conclusions as unknown.
Do not invent metrics, product claims or customer facts.
For any publication, message, account or store change, use only connected tools within my explicitly authorized scope and report success only after verification; otherwise provide the draft or proposed steps.Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.
Map every way a lead can enter the store today, the fields each entry path actually captures, the owner assigned to each source, the qualification rules the team accepts, and where those records land, noting any field that is captured but never used.
Build the capture path around the fields the qualification rules need and the ones the store can reliably record, dropping any step that depends on data the store cannot capture, and define the owner, the routing trigger and the first response for each qualified record.
Deliver the qualified prospect shortlist with each entry's source, captured fields, qualification outcome, evidence and next step with an owner, then verify that the shortlist row count matches the captured records and that every qualified entry names an owner and a next action.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
Only the fields the qualification rules read, because every extra required field costs completions; optional fields that help routing later can stay optional, and any field that no rule or owner uses should be removed from the form entirely.
Apply the ownership rule the merchant has set for that source and keep the original source and capture timestamp on the record, so the same person arriving twice is merged under one owner instead of creating two competing follow-ups.
Recheck a sample of captured records against the stated rules: each should carry its source, owner, qualification outcome and next step; entries missing an owner or an outcome are listed as exceptions rather than counted as qualified.
Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.
Ciwi Spark builds Shopify-native AI tools and agents around the workflows merchants actually run: research, ads, translation, and customer support. Stop rewriting the same prompts by hand.