Reading Time:6minutes The challenge of any SaaS provider is to continuously find ways to improve its software. At Convertize, we work hard to develop an A/B Testing tool so that it is easy to use, reliable and secure. One of our priorities is to ensure that we deliver the best page load speed possible whilst creating and […] The post 9 Ways our A/B Testing Visual Editor is Smarter appeared first on Convertize.| Convertize
Reading Time:4minutes You can now view your AB test results in unprecedented detail, marking key moments in your experiment and comparing your conversion rates to changes in your page’s traffic. The new Convertize results page incorporates three innovative features that make your data easier to analyse and interpret. Together with the A/B testing Smart Editor and Traffic […] The post Make Sense of Your AB Test Results Instantly appeared first on Convertize.| Convertize
Reading Time: 2 minutes Managing A/B Testing Goals just got easier with Convertize by Chumang Sango 28 June 2017 A/B Testing Software , Views: 3,173 Share on TwitterShare on LinkedIn Rate this post When optimising your website, you usually have a set of goals which define your conversions: usually a Lead or a Sale. Conversion optimisation is a very …| Convertize
Many of our customers have been waiting for AB testing and it’s finally live and can be used on our free plan. You can use subject line AB testing on Bulk/Marketing Campaign type only, not on automations or transactional campaigns. What Is an A/B Test Campaign? An A/B test campaign is a campaign with 2 …| www.bigmailer.io
Reading Time: 9 minutes 7 Ways to Avoid Loading Speed Issues in A/B Testing by Chumang Sango 25 July 2021 A/B Testing Software , Views: 18,805 Share on TwitterShare on LinkedIn Rate this post You’re doing A/B split testing to improve conversion rates, but A/B testing tools may actually slow down your website, increasing your bounce rate and affecting your search engine ranking. A/B …| Convertize
Overgeneralization is a mistake in interpreting the outcomes of online controlled experiments (a.k.a. A/B tests) that can have a detrimental impact on any data-driven business. Overgeneralization is used in the typical sense of going above and beyond what the evidence at hand supports, with “evidence” being a statistically significant or non-significant outcome of an online […] Read more...| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
Ad Inserter supports rotation groups which can be used to rotate between different insertion positions or different alignments.| Ad Inserter Pro
I got a question today about our AGILE A/B testing calculator and the statistics behind it and realized that I’m yet to write a dedicated post explaining the efficiency gains from using the method in more detail. This despite the fact that these speed gains are clearly communicated and verified through simulation results presented in our AGILE statistical method white paper [1].| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
What is the goal of A/B testing? How long should I run a test for? Is it better to run many quick tests, or one long one? How do I know when is a good time to stop testing? How do I choose the significance threshold for a test? Is there something special about 95%? Does it make sense to run tests at 50% significance? How about 5%? What is the cost of adding more variants to test?| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
After many months of statistical research and development we are happy to announce two major releases that we believe have the potential to reshape statistical practice in the area of A/B testing by substantially increasing the accuracy, efficiency and ultimately return on investment of all kinds of A/B testing efforts in online marketing: a free white paper and a statistical calculator for A/B testing practitioners. In this post we’ll cover briefly the need for a new method, some highligh...| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
This is a comprehensive guide to the different types of costs and benefits, risks and rewards related to A/B testing. Understanding them in detail should be valuable to A/B testers and businesses considering whether to engage in A/B testing or not, what to A/B test and what not to test, etc. As far as I am aware, this is the first attempt to systematically review all the different factors contributing to the return on investment from the process of A/B testing. Here I will cover A/B testing m...| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
Short, understandable, yet accurate explanation of p-values and confidence intervals. Starting from the problem of random variability and building up with minimal jargon, this is the most accessible introduction to these basic statistical concepts. Understand the meaning and utility of confidence intervals and p-values in statistical hypothesis testing and estimation.| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
This guide covers A/B testing, its definition, advantages, and real-world applications. We will also go over how A/B testing works, ways to implement it in your SEO practices, and common roadblocks that may come up when evaluating test results. Now, let's see how A/B testing can improve your websi...| RebelMouse
Navigating the maze of A/B testing statistics can be challenging. This is especially true for those new to statistics and probability. One reason is the obscure terminology popping up in every other sentence. Another is that the writings can be vague, conflicting, incomplete, or simply wrong, depending on the source. Articles sprinkled with advanced math, calculus equations, and poorly-labeled graphs represent a major hurdle for newcomers.| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
Discover how A/B testing your social media content can maximize your reach, engagement and ROI with our A/B testing tips >>| SmarterQueue
Running shorter tests is key to improving the efficiency of experimentation as it translates to smaller direct losses from testing inferior experiences and also less unrealized revenue due to late implementation of superior ones.| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...