Step 1
Start with ideal customer profile, target markets, permitted source data and qualification criteria.
A merchant needs potential business buyers but lacks a focused, evidence-based prospect list. In this case, the immediate task is to score lead fit using explicit business criteria. The workflow should produce a qualified prospect shortlist with evidence and next steps, using the merchant's actual records and constraints.
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 score lead fit using explicit business criteria.
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: [provide ideal customer profile, target markets, permitted source data and qualification criteria].
Identify relevant prospects from supplied or accessible sources, record evidence of fit and distinguish verified details from unknowns.
Expose each scoring criterion and supporting evidence; leave unknown criteria unresolved rather than awarding assumed points.
Return a qualified prospect shortlist with evidence and next steps 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.Start with the business context, the trigger, and the expected output before moving into the execution steps.
A merchant needs potential business buyers but lacks a focused, evidence-based prospect list. In this case, the immediate task is to score lead fit using explicit business criteria. The workflow should produce a qualified prospect shortlist with evidence and next steps, using the merchant's actual records and constraints.
Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.
Start with ideal customer profile, target markets, permitted source data and qualification criteria.
Identify relevant prospects from supplied or accessible sources, record evidence of fit and distinguish verified details from unknowns.
Expose each scoring criterion and supporting evidence; leave unknown criteria unresolved rather than awarding assumed points.
Deliver a qualified prospect shortlist with evidence and next steps; verify the result against the supplied records and identify unresolved inputs.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
No. Qualification requires a plausible fit and relevant buying context, not just an email address.
Without clear criteria, large lists can contain many irrelevant companies and waste outreach effort.
No. A score organizes observed fit under chosen rules. It is not a verified prediction of purchase.
Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.
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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.