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Dolls Kill Tech Stack

DTC fashion brand scaling creative production and performance marketing

Retail San Francisco, CA 201–500 employees Founded 2012 Privately Held

Dolls Kill operates a direct-to-consumer fashion brand built on Instagram-native community (2M+ followers) with a tech stack heavily weighted toward creative automation and marketing analytics. The hiring mix skews marketing-first (3 of 7 roles), supported by design system work and custom Shopify development — a pattern consistent with scaling visual content production at DTC velocity. Active projects reveal internal friction around manual workflows: image production, campaign design, and asset generation all appear on both project and pain-point lists, suggesting the company is investing in automation and repeatable systems to unblock downstream marketing execution.

Tech Stack 33 technologies

Core StackGoogle Ads Google Analytics Metabase NetSuite Adobe Illustrator Figma Python Shopify JavaScript TypeScript React Tailwind CSS Express.js GraphQL Prisma PostgreSQL Docker Adobe Photoshop Pinterest Google Analytics 4 Snapchat Shopify POS Photoshop InDesign Midjourney Stable Diffusion ComfyUI Runway Sass GCP+3 more

What Dolls Kill Is Building

Challenges

  • Roas target achievement
  • Budget optimization
  • Paid media reach expansion
  • Full funnel reporting and attribution
  • Monitoring new trends
  • Entering new performance marketing channels
  • Increasing speed and output across large catalogs
  • Reducing manual bottlenecks
  • Streamlining image production
  • Improving site performance

Active Projects

  • Structured testing roadmap development
  • Campaign performance analysis
  • Forecasting support for product launches
  • Homepage and site refreshes
  • Email campaign design
  • Design system development
  • Scalable workflows for multiple image angles and marketing assets
  • Repeatable workflows for product launches
  • Automation to reduce manual bottlenecks
  • Custom shopify theme development

Hiring Activity

Accelerating7 roles · 7 in 30d

Department

Marketing
3
Sales
2
Engineering
1
Product
1

Seniority

Junior
2
Manager
2
Senior
2
Mid
1

Notable leadership hires: Art Director

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About Dolls Kill

Dolls Kill is a San Francisco-based fashion retailer founded in 2012, selling primarily through direct-to-consumer channels to young women aged 18–35. The brand operates 201–500 employees across retail, creative, marketing, and engineering functions. Core business levers are Instagram community (cult following among DJs, celebrities, artists), paid media (Google Ads, Pinterest, Snapchat), and Shopify-powered commerce. Internal operations run on NetSuite for finance/inventory and Metabase for analytics. The creative team uses Adobe suite (Photoshop, Illustrator, InDesign), Figma for design, and AI image generation tools (Midjourney, Stable Diffusion, Runway, ComfyUI) to accelerate asset production at scale.

HeadquartersSan Francisco, CA
Company Size201–500 employees
Founded2012
Hiring MarketsUnited States

Frequently Asked Questions

What tech stack does Dolls Kill use?

E-commerce: Shopify + custom theme development. Analytics: Google Analytics 4, Metabase. Paid media: Google Ads, Pinterest, Snapchat. Creative: Adobe suite, Figma, Midjourney, Stable Diffusion, Runway. Backend: Python, Node.js (Express, React), PostgreSQL, GraphQL, Docker, GCP.

What is Dolls Kill working on?

Design system development, campaign performance analysis, custom Shopify theme work, email design, and automation to reduce manual bottlenecks in image production and product launch workflows — signaling a push to scale creative output and streamline asset production across large catalogs.

How this profile is built

Dolls Kill's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.