Rank promotional banners dynamically with a multi-armed bandit
Let a multi-armed bandit allocate banner exposure by observed performance, while keeping strategic placements under human control.
Why this can grow a startup
Static manual ordering can keep weak banners in premium positions after customer response changes. A controlled bandit can shift exposure toward better-performing options while the team protects placements that serve strategic priorities.
Company example
Kolon Mall compared algorithm-ordered banners with manual curation. The automated variant achieved a 793-basis-point higher conversion rate (p = 0.0143) and higher click-through rates; the team planned to automate where appropriate while retaining human control of strategic slots.
Source and metric
Source: Mixpanel customer story: Kolon Mall experimentation
Kolon Mall's automated banner variant achieved a 793-basis-point higher conversion rate than manual curation (p = 0.0143), plus higher CTR
Evidence scope: claims and metrics are attributed to the linked source; GrowthDex has not independently replicated the reported result. Check the original context and validate fit before applying it. Read the evidence methodology.
Added October 2026 · Growth techniques collection
Source discovered: October 2, 2026
When to use it
Use this when Experimentation, Ecommerce, Personalization is relevant to Growth, experimentation, personalization and you can run a bounded test with a medium budget.
When not to use it
Do not use it as a substitute for customer evidence, a clear owner, or a measurable stop condition. Local platform rules and market behavior still need checking.
Founder checklist
- Read Mixpanel customer story: Kolon Mall experimentation and identify what is directly supported.
- Choose one channel context: Experimentation, Ecommerce, Personalization.
- Define the test around Kolon Mall's automated banner variant achieved a 793-basis-point higher conversion rate than manual curation (p = 0.0143), plus higher CTR.
- Set an owner, evidence window, and stop condition before launch.
Explore the context
Apply this with an operator
Choose product surfaces that compound distribution without hiding weak activation or retention.