From Stock Photos to a Cohesive, On-Brand Visual System
Client: Wildflower (Yellow Springs, OH) Industry: Apparel & Accessories (boutique retail) Objective: Grow beyond a 20-something audience to include a wider range of demographics—without the cost and delays of traditional photoshoots.
The Challenge
Wildflower recently came under new ownership with a clear growth plan: expand the brand’s reach to a wider range of ages of women and a more ethnically diverse customer base.
But their product visuals were holding them back:
Reliance on wholesaler stock photos created a patchwork look that didn’t match Wildflower’s aesthetic.
Occasional, non-professional staff photos introduced inconsistent quality and styling.
The imagery didn’t represent their target demographics—especially older women and women of various races.
A prior attempt at a professional photoshoot was expensive and delivered weeks late, making the team hesitant to try again.
“We needed images that represented our vision - not the wholesaler’s catalog.” — Wildflower Team
Why Wildflower Chose SceneLab
Wildflower needed speed, control, and representation—without sacrificing quality. SceneLab provided:
On-brand AI models across ages and ethnicities
Rapid turnaround (hours/days, not weeks)
Lower cost than traditional shoots
Creative control over styling, environments, framing, and mood
Consistency across product lines for a cohesive storefront
Our Approach
Audience Alignment We aligned visuals to the new strategy: older women + broader diversity, styled with Wildflower’s real clothing products.
Style System & Cohesion We established a simple visual system—consistent lighting, backgrounds, and poses—so the entire site feels unified even when collections change.
Template-Driven Production We built repeatable prompts and shot lists (“lookbooks,” “lifestyle,” “product focus”) so the team can request new images on demand without reinventing the wheel.
Fast Iteration Loop Wildflower reviewed first passes quickly, requested tweaks, and SceneLab finalized assets quickly—no multi-week lag.
Implementation
Product coverage: Key seasonal items, new inventory, and bestsellers
AI Model sets: Inclusive age range, varied body types, and diverse ethnicities
Scenes: Lifestyle settings that feel local and approachable (boutique, street, casual indoor), plus clean e-comm frames for PLPs/PDPs
Missing representation of older women and diverse customers
Disconnected look across pages
After
Cohesive, brand-right visuals across the site
Models that reflect older and diverse demographics
Faster updates for new drops and promotions
Lower production cost and zero scheduling headaches
Before: Image of clothing provided by Wildflower
After: Clothing on-model, created by SceneLab
Before: Image of clothing provided by Wildflower
After: Image on-model, created by SceneLab
Impact
While Wildflower remains primarily a brick-and-mortar business (≈99% of revenue in-store), the revamped landing page and product visuals now:
Match the brand’s growth strategy (older + more diverse audiences)
Shorten time-to-asset from weeks to hours/days
Reduce production spend compared to traditional photoshoots
Give the team creative control to iterate whenever inventory or priorities change
Provides the confidence and aesthetic to begin growing their business into online markets
“We finally look like the boutique we are—welcoming, stylish, and for more than just one age group. And we can update images whenever we need.” — Wildflower Team
What’s Next
Extend the new visual system to seasonal campaigns and email/social
