What is A/B testing?
A/B testing (sometimes called split testing) is comparing two versions of a web page to see which one performs better. This is a fantastic method for figuring out the best online promotional and marketing strategies for your business.You compare two web pages by showing the two variants (let’s call them A and B) to similar visitors at the same time. The one that gives a better conversion rate, wins!Let’s say, you have an e-commerce website and your goal is to increase your sell. So by A/B testing you can try converting your visitors from just visitors to customer of you products.
There are certain rules of doing A/B testing. If you do it wrong it will do more harm that it can do good.The secret is in what they test and how they test.
A/B testing! Good or Bad ? You’ll have the answer, soon…
- As, you’ll be testing your website by creating 2 or more variants, you need to change websites design by Visual Editor or by injecting JS, CSS from an external file; Both of them is provided by the A/B testing service provider companies. In that case your website can be slow. Amazon’s calculated that a page load slowdown of just one second could cost it $1.6 billion in sales each year. Google has calculated that by slowing its search results by just four tenths of a second they could lose 8 million searches per day–meaning they’d serve up many millions fewer online adverts.
-> Actually it’s not the scripts by A/B testing service providers, it’s the Developer who actually made your life so miserable. Excessive/bad uses of setTimeout, setInterval function might do a great loss to your website. - Say, multiple variants are running in your website. After three or four days you could see a complete winner like getting more conversion to sells or less bounce rate etc for a variant. You immediately stopped the A/B testing. You just axed your own finger. You’ve done it completely wrong for your website.
-> As an A/B test should run for at least 7 days which is a complete week cycle, cause your visitors behave differently in different days. Like, for an e-commerce website, from Monday to Friday an user may be buying things for office or business and for Saturday and Sunday the same people might be buying thing for his/her family. So result will be completely different - Another case study is like this. You have got a complete winner variation B, which has got a conversion rate 60% and the losing one has got 40% conversion rate. The fact is that A/B tests will only tell you which version works best for the majority of your consumers, completely ignoring any minority consumer groups.
-> You can create nested A/B tests for different minority groups, and reduce the amount of ‘missed off’ recipients. By checking the data from heat map(Hotjar) and Metrics you can take a great decision that takes care most of your visitors.
Time to decide
What must you do then? If the strict and complicated A/B testing ignores nearly half your audience, what are you able to do?
Every component of the website that are responsible for selling can be A/B tested. This personalization isn’t regarding “first name, last name” personalization, it’s regarding testing all engagements and customizing them on a personal level. but strange and obvious it should sound, personalizing something drives engagement and less bounce rate.
However, A/B testing and personalization can’t be done manually for every individual recipient, meaning that you have to leverage data science and heavy computing. You have to leverage predictive algorithms and artificial intelligence so you can stop guessing.
Another best practice about running A/B tests is, after spending required amount of time, when your CRO confirms this or that variation wins, immediately apply the code change in your control(current websites source code) don’t just rely on the variation. Then try the next thing.
What are the Top A/B testing tools used by experts ?
Without further ado, here are the top A/B testing tools used by experts (Sorted Alphabetically):
- AB Tasty
- Adobe Target
- Apptimize
- ChangeAgain.me
- Conductrics
- Convert
- Dynamic Yield
- Google Optimize
- Kameleoon
- Maxymiser
- Monetate
- Omniconvert
- Optimizely
- Qubit
- Sentient Ascend
- SiteGainer
- SiteSpect
- VWO
Conclusion
So, the A/B testing for your website is not bad. It totally depends on you. The technology is ready. Are you?