Ever since I have heard about
Distilled’s SEO Split Testing Platform, I have been obsessed with the idea to replicate this tool.
I have read every post I could find about A/B testing engineering, and made this list of resources I found really helpful.
Here are a few things that I learned.
It is hard to collect data properly for SEO Split Testing; The CausalImpact Package is far from perfect. It is hard to detect variations with the package. I will probably migrate to Neural Network instead; If you have to choose between learning R or Python, choose whichever you want, but after a while, I ended up using Python.
You might want to check out Trevor Fox’s post giving
practical tips on SEO split testing.
First, let’s look at the original CausalImpact Package that inspired Distilled’s SEO tool.
SEO Split Testing Resources
Here are a lot of useful articles to learn to make your own SEO Split Testing.
What is SEO Split Testing – Distilled
19 Lessons I learned from a year of SEO split testing CausalImpact Package Documentation
Finding the ROI of Title tag changes using Google’s CausalImpact R package Next Era of SEO: A Guide to SEO Split-Testing
Compare Actual Vs Predicted Data With Google Analytics And CausalImpact – Bounteous
CausalImpact Wrapper for Python Improve CausalImpact Package
If you want to adapt CI package to become more precise you’ll need to investigate the BSTS model.
Fitting Bayesian structural time series with the bsts R package – Steven L. Scott Other Businesses Experiment Platforms
It’s All A/Bout Testing: The Netflix Experimentation Platform
Under the Hood of Uber’s Experimentation Platform
AirBNB – Experimentation & Measurement for Search Engine Optimization Optimizing Meta Descriptions, H1s and Title Tags: Lessons from Multivariate SEO Testing at Etsy
Etsy – Double-bucketing in A/B Testing
Etsy – SEO Title Tag Optimization at Etsy: Experimental Design and Causal Inference Pinterest – Demystifying SEO with experiments
Pinterest – Building Pinterest’s A/B testing platform
Pinterest – Scalable A/B experiments at Pinterest Thumbtack – SEO Tip: Titles matter, probably more than you think
Thumbtack – A/B testing at Thumbtack
Indeed – Proctor A/B Testing Framework LinkedIn – From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks
Lyft – Part 1 of 3: Experimentation in a Ridesharing Marketplace
Lyft – Part 2 of 3: Simulating a ridesharing marketplace Lyft – Part 3 of 3: Bias and Variance
Twitter – Implications of use of multiple controls in an A/B test DIY Split Testing
Extract Data From Google Trends Using Python – DataCamp SEO: Get started 10x’ing your traffic
A/B Testing With Google Tag Manager
A/B-testing via GTM – free with unlimited traffic
Ideas Of SEO Tests That You Can Run
SEO split tests you should run – Will Critchlow
Rand Fishkin’s 5 Simple Experiments for Improving SEO Health A Journey Through SEO Testing with ODN (Videos)
SEO Split Testing Tools
Distilled ODN CRO SEO Tools
Orthogonal Random Forest for Causal Inference Causal Inference and Stable Learning
SEO Strategist at Tripadvisor, ex- Seek (Melbourne, Australia). Specialized in technical SEO. Writer in Python, Information Retrieval, SEO and machine learning. Guest author at SearchEngineJournal, SearchEngineLand and OnCrawl.