Laurin Brechter

Can ML models learn to construct optimal customer journeys? Laurin Brechter · Follow Published in Towards Data Science · 8 min read · 8 hours ago — Optimizing Customer Journeys with Beam Search Marketing attribution has traditionally been backward-looking: analyzing past customer journeys to understand which touchpoints contributed to conversion. But what if we could use this historical data to design optimal future journeys? In this post, I’ll show how we can combine deep learning

Finding high-value patterns in transactions Laurin Brechter · Follow Published in Towards Data Science · 9 min read · 10 hours ago — In this post, I will give an alternative to popular techniques in market basket analysis that can help practitioners find high-value patterns rather than just the most frequent ones. We will gain some intuition into different pattern mining problems and look at a real-world example. The full code can be found here.

Gain better insights from your data Laurin Brechter · Follow Published in Towards Data Science · 7 min read · 9 hours ago — A/B testing, also known as split testing, allows businesses to experiment with different versions of a webpage or marketing asset to determine which one performs better in terms of user engagement, click-through rates, and, most importantly, conversion rates. Conversion rates — the percentage of visitors who complete a desired action, such