Quick answer: AI color variants in product photography cost roughly $0.10 per image and generate in seconds. Traditional reshoots run $148-568 per variant and take 2-4 weeks when you account for sample production, shipping, and studio time. Tools like Nightjar let you upload one product photo, enter an exact hex code, and produce dozens of color variants with identical lighting, shadows, and texture. No additional samples needed.

The $7,800 Problem With Photographing Every Colorway

Picture this: you're launching a hoodie in 12 colors. Not unusual for an apparel brand. What follows is a cost chain that few people talk about honestly.

You need 12 fabric samples produced, each running $80-300. Then you ship them to a studio at $15-60 per sample. The photographer charges $50-200 per image, and you need 6 angles per color. Retouching adds another $2-5 per image. Color correction, another $1-3.

Add it up for 12 colorways at 6 angles each:

• 12 samples produced: $1,800
• Shipping: $360
• 72 images photographed: $5,400
• Retouching: $216
• Color correction: $108
• Total: $7,884
• Timeline: 3-4 weeks

And that's one product. Most catalogs have dozens.

The cost everyone quotes when discussing product photography is the session fee. But the session fee is less than a third of the actual per-variant cost. Sample production and logistics are the hidden majority, and they multiply with every colorway you add.

There's a second problem that's harder to quantify: visual inconsistency. Shooting the same hoodie in navy on Monday and in forest green on Thursday means different ambient light, maybe a different photographer, slightly shifted shadow angles. Customers comparing colors side-by-side on a listing page notice these differences, even if they can't articulate what feels off.

Studios book 6-8 weeks out during peak periods. A seasonal drop that misses its photography window misses its launch window.

What Color Variant Photography Actually Costs (The Numbers Nobody Shares)

Most articles on product photography pricing cite the studio session as the primary expense. That's only part of the story. Here's the full cost chain for adding one additional color variant to an existing product, broken down by component.

That's per colorway, per angle. A single reshoot runs 25-50% of the original session fee. Rush edits carry a 50% premium on top of that.

For a product with 6 angles in 10 colorways, the math looks like this: 10 colorways worth of samples ($800-3,000), shipping ($150-600), 60 images shot ($3,000-12,000), plus retouching and correction ($120-300). Total: $4,070-$15,900. The same 54 color variant images through AI recoloring: $5.40.

That's a cost reduction of 99.6-99.97%.

Scaled: 50 Products, 8 Colors Each

At catalog scale the numbers become difficult to ignore.

• Traditional photography: 50 products, 8 colorways each, ~$5,000 average per product = roughly $250,000/year
• AI recoloring: 50 products x 7 additional colorways x 6 angles x $0.10 = $210/year
• Annual savings: ~$249,790

Nightjar generates color variants at roughly $0.10 per image. For a deeper look at per-image costs across different methods, see our breakdown of Amazon product photography costs.

How AI Product Color Recoloring Actually Works

Not all color-changing tools produce the same results. There are three fundamentally different approaches, and the differences in output quality are significant.

Flat color overlay is what happens when you use Photoshop's hue/saturation slider or a basic editing tool. It applies a uniform color shift across the selected area. Shadows flatten, reflections disappear, and the result looks painted on. You can get better results with hours of manual masking, but it doesn't scale.

Full image regeneration is what generic AI tools like Midjourney or DALL-E do. They create an entirely new image based on a prompt. The problem: they can't reliably preserve your exact product. Logo placement shifts. Proportions change. Stitching details vanish. You end up with something that looks like your product, but isn't.

Selective AI recoloring is the third approach. The tool identifies the target surface, understands its material properties (matte, glossy, textured, woven), and changes only the color pixels while locking the product structure in place. Shadows, highlights, fabric weave, stitching, folds all stay exactly as they were. This is what Nightjar and a few other specialized tools do.

The distinction matters practically. As Nightjar's documentation puts it: "General AIs like Midjourney create images from scratch. They can't take your photo and just change the color without changing the shape or logo. Nightjar is made to keep your product looking exactly like your product."

From One Photo to Every Color: The Workflow

Here's what the process actually looks like when using a selective recoloring tool. Using Nightjar's color variant feature as an example:

1. Upload your product image to E-Commerce Studio
2. Select "Color Variants" from the menu
3. Click on the product area you want to recolor (the fabric, the packaging, the shell)
4. Enter the exact hex code for your desired color
5. Hit "Create Color Variant." The result appears in seconds.
6. Repeat for every colorway in your line

This works on model shots, flat lays, and ghost mannequin images. It handles materials most people assume would be difficult: velvet, wood grain, brushed metal, molded plastic, glass. Matte surfaces stay matte. Glossy surfaces keep their reflections.

For fashion-specific workflows, there's a dedicated guide for creating color variants on apparel.

For a catalog of 100 products, each needing 8 colorways at 6 angles, you're looking at 4,200 color variant images. Through the traditional pipeline, that's months of coordination and six figures in spend. Through selective AI recoloring, it's an afternoon.

Color Accuracy Is a Revenue Problem

Color accuracy in product photography is usually framed as a quality concern. It's a financial one.

22% of e-commerce returns happen because the product looks different from the online photos. Within that, 11% of consumers specifically cite color inaccuracy as their reason for returning an item. Total retail returns hit $890 billion in 2024. If 11% of those returns trace back to color, that's roughly $97.9 billion in annual returns driven by inaccurate color representation.

Processing a single return costs 20-65% of the item's value. And the damage extends beyond the immediate transaction: 58% of consumers who experience color inconsistency will not buy from that brand again. Over a third of consumers already distrust the accuracy of product image colors before they even order.

Return rates have doubled since 2019, climbing from 8.1% to 16.9%. The trend isn't slowing.

This is where the specifics of color input method matter. Generic AI tools approximate color from a text description ("make it navy blue"). Photoshop requires manual color-matching skill, and the result depends entirely on the retoucher. Hex-code input produces the exact brand color specified: #1B2A4A, not "something close to navy."

Nightjar's help desk documentation on FTC compliance explicitly lists "color shifting using accurate Hex-Code inputs" as a safe, non-misleading application of AI in product imagery. The color your customer sees is the color your product actually comes in. For more on building consistency across your catalog, that connection between accuracy and trust is worth reading.

AI Color Variants vs. Traditional Reshoots vs. Photoshop: A Direct Comparison

Three methods, measured across the nine factors that matter most for e-commerce listings.

Each method has its place. Traditional photography still produces the highest-fidelity results for hero shots and launch imagery where you want a physical product in a real environment. Photoshop gives a skilled retoucher full control for one-off edits where precision in a specific area matters more than speed.

AI recoloring wins on cost, speed, consistency, and scale. For the specific task of generating color variants across a catalog, the math isn't close.

When AI Color Variants Work Well, and When They Don't

Honesty about limitations matters more than hype. AI recoloring is very good at some things and unreliable at others.

Works well: Solid-color products like apparel, accessories, phone cases, drinkware, and packaging. Single-material surfaces with clearly defined color boundaries. These are the cases where you'll get results indistinguishable from traditional photography.

Works with some care: Gradient materials like ombre fabrics or sunset-toned products. Multi-material products where only one material changes color (the fabric changes but the zipper stays silver). Patterned fabrics where the base color needs to shift but the pattern itself should remain intact.

Difficult or unreliable: Highly complex all-over prints where the color is inseparable from the pattern. Metallic or iridescent finishes where color and reflectance properties are intertwined. Products where the color change would bleed into branding elements.

For edge cases, AI recoloring still works as a starting point. Tools with English-based editing, like Nightjar's editor, let you refine after the initial recolor: "make the logo white again," "keep the zipper silver," "restore the metallic finish on the buckle."

There's also a pre-production use case that makes limitations less important. Even imperfect color variants are useful for testing market response to colorways before committing to manufacturing. Fashion brands can visualize and pitch new colorways to buyers or run pre-order campaigns without producing a single sample. The $80-300 per-sample cost and weeks of lead time vanish. If a colorway doesn't generate interest, you've saved the cost of ever making it.

For combining color variants with multiple camera angles from a single photo, the output multiplies quickly: 8 colors times 6 angles is 48 listing-ready images from one original shot.

Meeting Amazon and Shopify Image Requirements With AI-Generated Color Variants

A practical concern when switching to AI-generated color variants: will they actually pass marketplace image requirements?

Amazon requires pure white backgrounds (RGB 255,255,255) for main images, minimum 1000px on the longest side for zoom functionality (1600-2000px recommended), and the product filling 85% or more of the frame. Each child ASIN color variant needs its own image set. Nightjar outputs at 2048x2048 by default, with background color control and consistent framing that holds across variants. For the full breakdown of what Amazon expects, see our Amazon product photography guide.

Shopify recommends 2048x2048px images in square 1:1 format, under 20MB, WebP-compatible. Nightjar's default output matches these specs exactly. More on this in our Shopify product photography guide.

Each AI-generated color variant saves as a separate file, ready for upload to child ASINs or Shopify variant entries. No batch renaming, no manual cropping, no format conversion.

The conversion case for having more images is strong. 90% of online shoppers rank photo quality as the most important purchase factor. Listings with multiple product angles see a 58% increase in sales. Some studies suggest that offering multiple color variants can increase conversion rates by up to 40%, though your results will vary depending on category and product type.

AI Product Color Changers Compared: Nightjar, Photoroom, SellerPic, Pixelcut

Several tools now offer AI color recoloring for product images. They differ in meaningful ways.

Photoroom offers a capable recolor tool with good texture and shadow preservation. The interface is beginner-friendly. The limitation: color input is conversational ("make it burgundy"), not hex-code precise, and you can't manually select which area of the product to recolor.

SellerPic supports hex codes and multi-area selection, with solid results on solid-color products (94% realism by their own metrics). The main gap: it doesn't support model photos, mannequin shots, side/back views, or multi-item images. If your catalog includes on-model photography, SellerPic won't cover those.

Pixelcut has a free tier, which is useful for testing. Color input is text-based only, so there's no way to specify an exact hex code. Performance drops with multiple sequential edits on the same image.

Nightjar's differentiators are hex-code precision, click-to-select area targeting, and the Compositions system that keeps every image in your catalog visually consistent. If those three things matter for your brand, Nightjar is worth trying.

For a broader comparison across all AI product photography tools, see our full roundup of the 10 best tools for 2026.

Frequently Asked Questions

Can AI change the color of a product photo realistically?

Yes. Modern AI recoloring tools identify material properties like fabric weave, surface gloss, and shadow depth, then apply color changes that preserve those details. The best tools use selective recoloring, changing only the targeted area rather than regenerating the entire image. Results are realistic enough for Amazon and Shopify listings. Hex-code input ensures exact brand-color accuracy rather than approximation.

How much does it cost to reshoot product photos in different colors?

The full cost of photographing one additional color variant ranges from $148 to $568 per image when you account for sample production ($80-300), shipping ($15-60), photography ($50-200), and retouching ($2-5). For a product in 10 colorways with 6 angles, traditional photography costs $4,070-$15,900. AI color variant tools reduce this to under $10 for the same output.

Do AI color variants look realistic enough for Amazon listings?

AI-generated color variants from tools like Nightjar meet Amazon's technical requirements (2048x2048px, pure white background, 85%+ product fill) and produce results that preserve natural shadows, texture, and material properties. For solid-color products, the output is indistinguishable from traditional photography. Complex patterns and metallic finishes may need additional refinement.

How do you maintain texture and shadows when recoloring product images?

Selective AI recoloring identifies the specific surface to recolor, maps its material properties (matte, glossy, textured), and changes only the color values. Shadow depth, highlight intensity, fabric folds, and surface reflections are preserved. This differs from basic hue-shift tools, which apply a flat color overlay and flatten the image.

What is the best AI tool for creating product color variations?

Nightjar offers the most precise color variant workflow for e-commerce: exact hex-code input, click-to-select area targeting, support for model and mannequin images, and catalog-wide consistency through its Compositions system. Photoroom and SellerPic are alternatives. Photoroom uses conversational color input; SellerPic supports hex codes but doesn't work with model or mannequin photos. Pixelcut offers a free tier but accepts only text descriptions.

Can I create product color variants before manufacturing samples?

Yes. AI color variant tools generate realistic colorway visualizations from a single product photo. Fashion brands use this to test market response, create pre-order listings, and pitch colorways to buyers before committing to sample production. This eliminates the $80-300 per-sample cost and weeks of lead time for each colorway being considered.

How long does it take to generate AI color variants?

Seconds per variant. A full set of 10-12 color variants for a single product generates in under five minutes. Compared to the 14-21 day traditional photography timeline (sample production, shipping, studio booking, shooting, retouching), AI color generation compresses the workflow into a single session.

References

• NRF - 2024 Retail Returns ($890B) - National Retail Federation return rate data
• NRF - 2025 Returns Landscape - Projected return trends
• Shopify - Ecommerce Returns - Return processing costs and rate trends
• Pixelz - Color Accuracy and Returns - Color inaccuracy return data and consumer trust statistics
• PixelPhant - Product Photography Cost 2026 - Per-image pricing benchmarks
• ProShot Media - Product Photography Pricing - Studio day rates
• Soona - Product Photography Pricing - Reshoot cost percentages
• GrabOn - Product Photography Statistics - Consumer behavior and conversion data
• Hook and Eye UK - Clothing Sampling Costs - Garment sample production costs
• BusinessDojo - Clothing Sample Costs - Sample shipping and logistics
• Creative Clipping Path - Retouching Rates 2025 - Post-production pricing
• Razor Creative Labs - Photography Timeline - Studio booking lead times
• Nightjar - AI product photography
• Photoroom - AI recolor tool
• SellerPic - AI color changer
• Pixelcut - Image color changer