The hottest A/B Testing Substack posts right now

And their main takeaways

Category

Top Business Topics

💡Conversion: Bigger numbers are not always better

First 1000 • 904 implied HN points • 25 Apr 23

💼 Business Marketing Entrepreneurship A/B Testing

Bigger numbers are not always better, especially with weaker value propositions.
In A/B testing, a smaller increase in a valuable metric can be more appealing than a larger increase in a less valuable one.
Acquiring your first 1000 customers requires experimentation and finding the right approach.

💡Everyone is betting on Discovery

First 1000 • 707 implied HN points • 16 May 23

🕹 Technology Experiments Tech stack A/B Testing Discovery

Multiple big companies are investing in discovery experiments.
LinkedIn, Snapchat, and Amazon are running significant discovery tests.
The results of these experiments are still pending.

Embracing the New Era of Accelerated Testing - Issue 150

Data Analysis Journal • 235 implied HN points • 28 Jun 23

🕹 Technology Data science Analytics A/B Testing Experimentation Tooling

Embracing accelerated testing in the modern data analysis landscape is essential for success.
The current traditional academic workflow for A/B testing may not be suitable for the evolving landscape of experimentation.
To thrive in the era of rapid feature flagging and A/B testing, teams need to adapt by automating statistical checks, simplifying documentation, and eliminating bias.

How To Run An A/B Testing On Low Traffic - Issue 181

Data Analysis Journal • 137 implied HN points • 10 Jan 24

🕹 Technology Data science Analytics A/B Testing Experimentation Statistical Analysis

No specific rules on when to start A/B testing or the minimum user numbers required.
Consider adjusting thresholds when experimenting with small sample sizes.
Address factors like confidence levels and test timelines for effective decision-making.

Use feature analytics for better products

timo's substack • 157 implied HN points • 31 Jul 23

🕹 Technology Analytics Product Development A/B Testing

Digital products benefit from feature analytics for iteration speed and feedback.
Features are the core aspect of product development that teams and users focus on.
Creating feature dashboards and analyzing feature initiatives can enhance product development and refinement.

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Revisiting A/B tests in SaaS 💯

The SaaS Baton • 117 implied HN points • 26 Apr 23

🕹 Technology SaaS A/B Testing Data Quality Network Effects

Running A/B tests on SaaS products has unique challenges beyond just having enough users for statistically significant results.
Incorporating minimal clear constraints in projects can drive creativity and productivity, as seen in Buffer's Build Week.
Establishing indirect growth channels, like Gusto did with accounting firms, can create network effects and be a win-win for both parties.

Demystifying A/B Testing for the web, a glimpse into the past and a book you can't miss

Cristian’s Substack • 39 implied HN points • 15 Apr 23

🕹 Technology A/B Testing Web Development Data Analytics Product Management User Experience

A/B testing has a fascinating history, from Google to Obama's campaign success.
Implementing website A/B tests involves creating variants with CSS/JS code.
Developing test hypotheses requires cross-functional team collaboration and data analysis.