pixelwright UI Development & Design

Transforming SME Marketing with AI & Data Science

05 Sep 2022

Project Overview

Role: Head of User Experience
Duration: March 2019 – August 2022
Platform: AI-powered SaaS for e-commerce marketing
Stack: React, Figma, Design Systems, Data Visualisation, Cross-functional Delivery

Machine Labs is an Edinburgh-based startup delivering artificial intelligence–powered marketing and data science solutions to small and medium e-commerce businesses. Its flagship offering enables independent retailers, especially those on Shopify, to harness big-company data capabilities, automate customer engagement, and drive repeat purchases through more effective email and database marketing.

The Challenge: Democratizing Data-Driven Growth

While enterprise e-commerce platforms had embraced advanced machine learning and data-driven growth, these capabilities were largely out of reach for SMEs. Typical pain points included:

  • Fragmented data and tools: SME teams lacked affordable, unified solutions for targeting, segmentation, and campaign optimization.
  • Opaque insights: Most marketing platforms failed to surface actionable data, relying on “gut feel” and basic metrics.
  • Need for automation: Resource-constrained merchants were unable to leverage data science to drive repeat business and retention, or to automate manual workflows.

The goal for Machine Labs was to bring scalable, enterprise-grade AI marketing to SMEs through Shopify app integration and intuitive, accessible product design.

User Research & Market Insights

  • Surveys and interviews with 150+ Shopify merchants uncovered the need for an approachable, trusted platform that could automate complex marketing tasks, personalize customer interactions, and yield real intelligence from messy e-commerce data.
  • Beta user pilots revealed demand for clarity, simplicity, and clear value-delivery in both UX and communications.
  • The team tracked rapid market adoption, achieving 300 installs across dozens of countries within two weeks of launch, and earning a “Top Pick” feature on the Shopify App Store homepage.

Solution: Product & UX Innovations

Unified, Accessible Marketing Suite

  • Shopify integration: One-click onboarding enabled instant syncing of store data, campaign histories, and customer profiles.
  • No-code automation: Merchants could deploy and edit automated campaigns, segments, and smart recommendations without technical expertise.
  • Personalized, data-driven campaigns: ML-driven segmentation and targeting powered relevant, timely communications to the right customer at the right time.

Data Science and Insights for Every Merchant

  • Actionable dashboards: Visualized analytics on customer lifecycle, churn risk, and campaign ROI; embedded guidance and next-action suggestions.
  • AI recommendations: ML models predicted customer behavior, optimized send times, and surfaced high-value opportunities and at-risk customers.
  • Continuous improvement: Automatic adaptation to new data, demographic shifts, and seasonality using deep learning models.

Design System & UX

  • Consistent design system: Led end-to-end creation, documentation, and rollout of a reusable design system enabling rapid feature growth and unified product branding (across web and future mobile touchpoints).
  • User-centric workflows: Streamlined key flows for campaign creation, segmentation, data exploration and performance reporting, validated through iterative prototyping and merchant feedback.
  • Accessibility, clarity and trust: Focused on language simplicity, microcopy, and inclusive UI for less technical merchant segments.

Business Impact & Recognition

  • Platform grew to support thousands of Shopify merchants globally, driving repeat sales and marketing ROI for independent retailers.
  • Achieved “Top Pick” on Shopify App Store, immediate global traction and positive merchant reviews for ease of use and time savings.
  • Supported rapid sales and VC-led team growth, with multi-million pound funding rounds.
  • Created design foundation for extension into multiple sales channels and e-commerce platforms.

Learnings and Recommendations

  • Approachability is a core differentiator: Even advanced AI must be delivered in a human, actionable, and transparent way for non-expert SMEs to trust and adopt.
  • Design systems unlock cross-team velocity: Mature design systems were critical to feature velocity, platform scalability, and branding.
  • UX and data-science must be tightly coupled: Bringing marketers and product teams into early-stage prototyping maximized real-world relevance.
  • Continuous product iteration: Rapid feedback loops from real merchants kept the tool valuable and differentiated.

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