Blog

Practical guides on multi-armed bandits, algorithmic testing, and conversion optimization.

Featured
5 min read
Guide

What Is Multi-Armed Bandit Testing?

A practical introduction to multi-armed bandit algorithms for website optimization. Learn how bandits balance exploration and exploitation to maximize conversions without wasting traffic.

March 27, 2026

Strategy

How Costco Could Turn 600 Warehouses Into One Giant Optimization Engine

A thought experiment: apply A/B testing, multi-armed bandits, and funnel algorithms to retail floorspace and product placement. See why a chain with hundreds of locations is the ideal environment for algorithmic optimization — and how bandits adapt to seasonality without a single manual re-test.

10 min read
Guide

From A/B Testing to Trained Models: When to Graduate to Each Algorithm

A/B testing, multi-armed bandits, contextual bandits, and custom trained models each need an order of magnitude more data than the last. Here's how to tell which rung your traffic actually supports.

5 min read
Guide

Why Bandit Runs Thompson Sampling and Not Epsilon-Greedy or UCB1

We compared Epsilon-Greedy, UCB1 and Thompson Sampling on convergence speed, regret, tuning and real-world suitability, then shipped only one of them. Here is the reasoning, and what you configure instead.

6 min read
Deep Dive

Understanding Exploration vs Exploitation: The Core Trade-Off

The explore-exploit dilemma is the fundamental challenge in optimization. Learn how bandit algorithms navigate this trade-off through real-world analogies, interactive visualizations, and practical examples.

6 min read
Tutorial

How to Set Up Your First Bandit Experiment in 5 Minutes

A step-by-step tutorial for launching your first multi-armed bandit experiment. From creating an experiment to integrating the SDK and tracking conversions.

4 min read
Strategy

Why Your A/B Tests Keep Failing (And What to Do Instead)

Most A/B tests end inconclusively. Learn the five most common reasons, from insufficient traffic to the peeking problem, and how adaptive algorithms can help.

5 min read
Comparison

Multi-Armed Bandit vs A/B Testing: A Side-by-Side Comparison

Watch a live simulation comparing traditional A/B testing against bandit algorithms. See how adaptive traffic allocation reduces wasted conversions and cumulative regret.

4 min read
Tutorial

Getting Started with Algorithmic Testing in 5 Minutes

A step-by-step tutorial to integrate the Bandit SDK into your application. Install, initialize, get assignments, and track conversions, with copy-paste code examples.

3 min read
Deep Dive

Thompson Sampling Explained: The Bayesian Approach to Optimization

A visual deep-dive into Thompson Sampling, the most effective bandit algorithm for website optimization. Understand Beta distributions, posterior updates, and why Bayesian exploration naturally balances the explore-exploit tradeoff.

4 min read
Strategy

A/B Testing with Low Traffic: Why Bandits Are the Better Choice

Traditional A/B testing requires thousands of visitors to reach significance. Learn why multi-armed bandit algorithms are better suited for low-traffic sites and how to calculate when each approach makes sense.

4 min read
Strategy

Funnel Experiments: Optimizing Every Step of Your Conversion Path

Learn how to run linked experiments across your entire conversion funnel. Optimize landing pages, signups, onboarding, and purchases as a coordinated system instead of isolated tests.

5 min read