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Spark playbook scenarios · Spark: AI Store Assistant

Improve the presentation of an existing product photograph

Photographs shot under mixed lighting make products look unlike what buyers receive, and past corrections were ad hoc. In this case, the immediate task is to improve the presentation of an existing product photograph. The workflow should produce an edited file or a step brief, recording any colour, contrast or texture shift away from the true appearance.

Topic
Product Image Editing
Target keyword
shopify product photo enhancer
Copyable AI prompt

A prompt you can drop directly into Spark

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.

ai-prompt.txt
Act as a Shopify operations specialist.
Help me improve the presentation of an existing product photograph.
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 untouched original file, the adjustments the merchant requested, a reference for the product true colour and finish, and the required output size and format]. Apply only the requested corrections and compare against the reference after each one, watching for shifts in colour, contrast, sharpness or texture that make the item look different from what the buyer will receive.
Return the edited file or a step brief 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.
Use in Spark
How to solve

A recommended resolution workflow

Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.

01

Step 1

Start from the untouched original file, the adjustments the merchant requested, a reference for the product true colour and finish, and the output size and format the image must be delivered in.

02

Step 2

Apply only the requested corrections and compare against the reference after each one, watching for shifts in colour, contrast, sharpness or texture that make the item look different from what the buyer will receive.

03

Step 3

Deliver the edited file or a step brief recording every adjustment applied, then compare it side by side with the original at the stated output size, note each shift away from the true appearance and leave the original in place until the merchant approves.

FAQ

Common questions when running this scenario

Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.

Which corrections stay inside the brief?

Those that restore the recorded appearance, such as levelling exposure, correcting a colour cast or removing a background flaw. Removing a real feature of the product, or smoothing a texture buyers judge the item by, goes beyond correction.

How is colour accuracy checked without the product on hand?

Against the reference the merchant supplies for that product colour and finish. Where no reference exists, mark the result as unconfirmed rather than matching it to a similar listing, which only repeats an unknown error.

Should the original be kept after the edit is approved?

Yes, keep the untouched file as the fallback. If a later complaint questions the colour or the finish, the original is the only record of what was actually shot, and it lets the edit be redone.

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Next step

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