This is an overview of articles that I read this week and shared via my weekly newsletter. It covers the best of analytics and experimentation related content.
1. Recap Conversion Hotel conference 2019
Two weeks ago I visited the ‘Conference Formerly Known as Conversion Hotel’, now known as #CH2019. This was already my fourth visit to what I believe is the best conference in The Netherlands for people into data, analytics and experimentation. Read/watch links to all video summaries, slides, notes, questions and pictures (and get on the notification list for next year).
Earlier this year Simo Ahava already wrote a good blogpost on Intelligent Tracking Prevention (ITP). He recently released Cookiestatus.com: “a knowledge sharing resource for the various tracking protection mechanisms implemented by the major browsers and browser engines”. Mandatory reading material for everyone collecting and/or analysing online data. Go to cookiestatus.com
3. Creating the Experimentation Organization
A short interview with Stefan Thomke about experimentation and his forthcoming book, ‘Experimentation Works‘. “Companies better get on this [experimentation] if they don’t want to be at a major competitive disadvantage.” Read the article
4. The North Star Playbook
John Cutler from Amplitude put together this nice overview of how to define a North Star Metric. Including this checklist with the characteristics of a strong North Star:
- It expresses value. We can see why it matters to customers.
- It represents vision and strategy. Our company’s product and business strategy are reflected in it.
- It’s a leading indicator of success. It predicts future results, rather than reflecting past results.
- It’s actionable. We can take action to influence it.
- It’s understandable. It’s framed in plain language that non-technical partners can understand.
- It’s measurable. We can instrument our products to track it.
- It’s not a vanity metric. When it changes, we can be confident that the change is meaningful and valuable, rather than being something that doesn’t actually predict long-term success—even if it makes the team feel good about itself.
5. The 11 best A/B Testing tools in 2020
… according to Alex Birkett. Read the article
6. Using R to synthesise long-term findings with Meta-analysis at the BBC
Frank Hopkins from BBC’s Experimentation & Optimisation Team writes why meta-analysis of A/B tests are important. And how they do it. Read the article
7. The 2019 State of Conversion Optimization Report
CXL’s fourth edition of the State of Conversion Optimization report. Biggest challenges: better processes and buy-in from decision-makers. Download the full report