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10 Useful Tips For A/B Website Testing

As we are always busy, we do not spend much time for different experiments and testing. But we all know that the quality experiment can sighnifically increase the conversion and the profit. Here I am to share with you some information about website testing which can be very useful if you want to increase the effectiveness of your web pages.

A / B or split testing is a simple and qualitative way to compare two versions of the implementation of one element to each other in order to identify more successful.

A/B testing

To begin with some important questions:

  • № 1 What is your conversion?
  • № 2 When did you last performed testing of some elements of your site?
  • № 3 When did you last performed testing of some elements of your business?
  • № 4 Did you do any testing of the elements of the site or business at all?
  • № 5 Why do you need website? A business?

If the answer to the 1st question, you write “100%” – do not read on – you are the God!
The correct answer to the second and the third questions is “In progress” . If so, then this article will enhance your knowledge. If not, then, provided that you do not find it difficult to answer the last question – this article is for you!

In this article we will discuss 10 simple things to consider when conducting A / B testing of your website, business, life, or indeed anything. But of course we’ll talk first about the sites.

  • Test everything you can. There are so many things that can be measured: the colors, patterns, text, forms, buttons, design, time and frequency of posting tweets, banners, traffic sources – a list of elements is practically limitless. The more variables you can compare, the best score you can achieve.
  • Do not test all at once. At each moment of time test only one element on a page or group of pages, otherwise you will not be able to determine exactly what has given the result. For example, if you test the options of the button ‘buy’ and thus change the selling text, how to determine what proportion of that works? If you test only one element – the problems will not arise.
  • Start with something small. When carrying out A / B testing it is not needed immediately undertake a global change, try to change something small and evaluate the result. Such a change may be a change of the button “add to cart” or “buy” – perhaps this will give a good conversion. In addition, starting with small things you can upgrade your skills and be able to more global experiments.
  •  Do not be afraid to carry out more sophisticated tests. When you get comfortable with the simple test cases, you can go to the A / B / C testing and try to compare two completely different page designs. He last words seemingly contradict the second paragraph (not to test all at once), but in this case we can say that the variable is ‘design’.
  • Test always. It is always needed to test something, because there is no limit in perfection. Completed the test of an element? Start testing other. Your goal is to reach 100% conversion. When you do this, you can stop, but not before! You can test different things in parallel on different pages, such as “Buy” button on one product group, the pattern – on the other, the addition of feedback – on the third. It is important that these changes do not overlap.
  • Do not limit testing only within the site. No need to concentrate only on the site – try to change the style of your corporate blog, try on different roles in social networks, experiment with the stylistics of tweets, status and notes. Explore the marketing channels and opportunities – the main thing is to analyze the right metrics.
  • Do not assume that every result is statistically significant. Not all results are statistically significant. For example, if you compare the effectiveness of two mailing headers, it is not a fact that the result of this was provided by the title may.
  • Analyze the statistical reliability of the results. Instead of assuming something, you must analyze any result for statistical significance. For a simple determining of statistical significance of results, you can use on-line calculator.
  • Do not stop if your results are not reliable. From time to time, your results may be like that. In this case, there are two options – maybe we should wait and get a larger sample of the results, and may be audited figure really is not important for the client or the alternatives are equivalent.
  • Implement the results. If the results are valid, implement them them. If you came to the conclusion that the option does not affect the results – rely on taste and continue to the next factor.

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2 comments

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