// Case study · E-commerce (Skincare)
A Shopify site and WordPress blog for a skincare brand that outgrew Squarespace
Mirra Skincare, a science-first skincare brand, had outgrown its Squarespace website. We built a Shopify landing page and connected a WordPress blog so commerce and content each ran on a platform built for the job.
- Client
- Mirra Skincare
- Platforms
- Website · Shopify · WordPress
- Industry
- E-commerce
The project
The challenge
Mirra Skincare built its brand around a community of skincare nerds, with science guiding its products and the experiences around them. Its previous Squarespace website had started to limit the business.
A science-led brand needs two things online: a store built for commerce and a place to publish in-depth content for its community.
What we built
We moved Mirra onto Shopify with a new Shopify landing page, putting its store on a platform made for e-commerce.
Then we connected a WordPress blog built for Mirra, so the team could publish long-form skincare content in a system designed for writing and search.
Pairing the two let each platform do what it does best: Shopify ran commerce, and WordPress ran content.
The result
- Mirra moved off the Squarespace site that had been limiting it.
- The brand gained a Shopify storefront with a connected WordPress blog for its content.
Built with
- Shopify
- WordPress
Where AI takes it next
How we'd extend this product with today's AI — the same thinking we bring to every client roadmap.
- 01
A routine advisor: shoppers describe their skin type and concerns, and an assistant grounded in Mirra's own product data recommends a routine and explains the science, with guardrails that keep it to cosmetic claims rather than medical advice.
- 02
An AI-assisted editorial workflow for the blog: topics drawn from real customer questions, drafts built from cited sources, and a human science check before anything publishes.
- 03
Review mining: cluster reviews and support messages by skin type and concern to show which products work for whom, and feed those patterns into product development.
- 04
Replenishment timing: predict when each customer will run out based on product size and order history, and send the reorder reminder then, not on a fixed schedule.
Services on this project
What we brought to the table.
Next step
Have a product or process like this?
Tell us what you're trying to build or fix. We'll come back with an approach, a rough timeline and the AI opportunities hiding in it.
More work
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