Refine source images into polished campaign variations with Nano Banana Pro.

Nano Banana Pro works best when the source image has a clear job. Tell the model what the original image already gets right: the product shape, face, pose, packaging color, camera angle, room geometry, or brand atmosphere. Then separate the requested changes into background, lighting, crop, offer messaging, surface treatment, or localization so the refinement does not drift away from the asset you already trust.

For product work, use the first pass to establish a believable environment before asking for many variants. A packshot can become a seasonal set, a clean ecommerce card, a premium launch hero, or a social ad, but each output should still preserve product readability. Brief the surface, shadows, lens feel, and negative space so the final image can accept badges, price copy, or translated headlines.

For creator, portrait, and regional campaign assets, keep identity and composition constraints explicit. Ask for wardrobe, background, crop, and text changes without changing the person or the source direction. When an image must work across markets, generate the layout with safe text zones first, then localize short copy and review every export for spelling, cultural fit, and platform crop safety.

A good refinement workflow also protects the decision trail. Keep the original source, the strongest intermediate version, and the final export in the library so the team can return to a known-good visual state. When a variation drifts too far, restart from the closest approved image instead of stacking more instructions onto a weak result.

Use naming and notes to separate exploration from approval. Mark which versions tested a new background, which protected the original crop, which added localized text, and which was cleared for an ad or product page. That context helps designers, media buyers, and stakeholders reuse the right asset without reopening the whole creative debate.