Cases
AI Automation

Public A/B Pricing Optimiser: Live Streamlit Tool for SMB Pricing Decisions

Built and deployed a self-serve A/B pricing tool for small retail and SMB teams without analysts. Users upload experiment data, get statistical conclusions, and receive actionable pricing recommendations via a simple UI.

Result · • Public demo shipped (Streamlit). • End-to-end build + deployment delivered.

Context

Solo-built product for small retail / SMB decision-makers. Core constraint: usability—non-technical users must get value fast without complex setup.

My role

Founder / Builder (product design, implementation, deployment).

Discovery

• Mapped the simplest decision workflow: upload results → understand outcome → choose next action. • Focused on reducing cognitive load for non-technical users. • Tested output formats to ensure recommendations are actionable, not academic.

Solution

• Streamlit app with A/B test interpretation and decision-ready recommendations. • Guided UI, clear explanations, and “what to do next” outputs. • Deployed as a public demo for easy sharing and iteration.

Result

Public demo shipped and live; proved end-to-end delivery from product design to deployment for an analytics-driven pricing workflow.

Tools & methods

PythonStreamlitexperimentation/A-B testing conceptsproduct UX for non-technical usersrapid prototyping.