Georgi Georgiev
Owner at Web Focus Llc
Author of "Statistical Methods in Online A/B Testing" | Founder of Analytics-Toolkit.com | Advisor @ ABsmartly | Owner @ Web Focus LLC
About Georgi Georgiev
I'm passionate about data-driven decision making in the internet industry and beyond. Logic and empiric evidence is the way forward and I want to be paving the way as much as I can. To that end I've developed statistical tools for A/B testers at https://www.analytics-toolkit.com/ , wrote dozens of in-depth articles and white papers on the topics of web analytics, statistics, and online controlled experiments (A/B tests) as well as the book "Statistical Methods in Online A/B Testing". It also includes designing and presenting lectures for leading online education platforms such as the CXL Institute, starting the OneSided Project (https://www.onesided.org) and developing a huge repository of online computing resources at GIGAcalculator.com. In between working on my own projects I consult clients on statistical and experimental methodology. I specialize in auditing experimentation programs to pinpoint issues and areas of improvement in methodology that lead to higher ROI tests and more trustworthy inferences. I am also an advisor to A/B Smartly, a fast-growing startup developing a sophisticated experimentation platform. Backing that up is more than a decade of experience with A/B testing, mostly focused on experimental design and statistical methodology. My prior experience is as an online marketing expert and analyst, SEO, Google AdWords, Web Analytics and statistical analysis specialist. For many years I've been a Google certified AdWords Expert, Google Analytics specialist, as well as a Google Certified Trainer for both. My experience also includes developing and operating dozens of websites. To this day I love to code in any language that makes life easier.
Skills & Expertise
Career Journey
Owner
Web Focus EOOD was developed as a boutique online marketing and analytics agency, but currently mainly operates its owned web properties among which Analytics-Toolkit.com and GIGAcalculator.com.
Author
This is the book I wish I had when I started learning A/B testing stats. It will help you navigate the statistical jungle of jargon & formulas. You will understand the advantages and limitations of statistical approaches for assessing the uncertainty of data from online controlled experiments. You will learn how to design efficient statistical tests and to adapt statistical models in a number of practical scenarios, primarily from e-commerce A/B testing. Subtitled Statistics for data-driven business decisions and risk management in e-commerce , it is as much a book on statistics and design of experiments as it is a book on doing business in a sustainable way - innovating and improving while managing risk through experimentation. Grab your copy www.abtestingstats.com What people are saying about Statistical Methods in Online A/B Testing : If you re running online experiments, you absolutely need this book. It will help you avoid costly testing mistakes stemming from misuse and misunderstanding of statistics. Peep Laja, CXL Institute This is simultaneously the most comprehensive and the most accessible book on A/B testing statistics I ve encountered. Alex Birkett, HubSpot Statistical Methods in Online A/B Testing transforms the often-complex area of statistical modeling into an understandable and useful framework for those will little or no math background. Barry Garner, Sales Development Manager, SiteGainer Finally, a comprehensive reference on statistics for my own industry No longer do I need 8 different books on statistics that were each bought for only one or two chapters each. Philip Cross, Premeni Services Company No fluff, straight to the point, practical manual you need on your desk. Masterfully delivered by a true practitioner and an excellent teacher of the somewhat complicated world of statistics. Hristian Kambourov, Revise
Advisor
As an advisor to A/B smartly I assist the company with statistical engine development, experimentation methodology, and the user experience surrounding the design and analysis of A/B tests.
