A new offer needs a page this week, and starting from a blank editor costs most of that time. In this case, the immediate task is to generate an AI-assisted landing-page draft. The workflow should produce a landing-page draft and improvement hypotheses drawn from the merchant's own campaign material.
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 generate an AI-assisted landing-page draft.
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: [the campaign message, audience, offer with terms, the verified claims and proof points, the creative assets the merchant holds rights to, and the intended visitor action].
Draft the structure so the opening section restates the campaign promise in the merchant's own words and every statement stays inside the verified claims, replacing any generated claim, figure or testimonial that cannot be traced to the supplied material with a placeholder naming what is missing.
Return a landing-page draft and improvement hypotheses checked against the supplied material 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.
Collect the campaign message, audience, offer with terms, the verified claims and proof points, the creative assets the merchant holds rights to, and the intended action, flagging any claim that appears in the material without a matching record.
Draft the structure so the opening section restates the campaign promise in the merchant's own words and every statement stays inside the verified claims, replacing any generated claim, figure or testimonial that cannot be traced to the supplied material with a placeholder naming what is missing.
Deliver the draft with its section order, copy and actions plus improvement hypotheses, then check line by line that each claim, price, term and asset matches the supplied material and report every placeholder as an open item for the merchant to fill.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
Treat it as a first version: generated claims, figures and testimonials are only as good as the material supplied, so each one is matched against the merchant's records and anything unmatched becomes a placeholder the merchant fills before the page can go live.
The campaign promise, the audience, the offer with its terms and expiry, the approved claims, the intended action and the assets the merchant can legally use; without the offer terms and verified claims, the draft will invent specifics that have to be removed later.
Give the generator the merchant's own wording for the promise and the claims and hold it to that vocabulary, then review the result for tone and for promises the store cannot honour; a fluent draft that invents a guarantee is worse than a rough one that does not.
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.