What is Testing?

Testing is the process of changing the content of web pages, recording the results and implementing those changes that improve conversion rates.

The testing process needs to be statistically valid and takes some discipline. Testing without recording results is a waste of time, money and effort.

The principles underlying testing are that changes to your site, and especially copywriting changes, will have an impact on how well your site converts visitors into subscribers or customers. Some changes will make your conversion rates smaller. Some changes will improve conversion rates.

It follows then that making changes and recording the results will result in an overall improvement in your site's conversion rate if you delete the poorer performing versions and stick with the better ones.

If you continue with this process you can get a page to "evolve" into a highly effective sales tool.

To make testing work properly though you need to make the tests as unbiased as you can. This means taking out of the test any factors that may twist the results. For example, it is rarely sensible to test one page on a Friday and another on a Saturday and compare the results because search traffic is different at weekends.

The best way of avoiding problems like this is to split your web traffic evenly so that it alternates between two different pages under test. This removes as many time and location biases as possible. This process is also known as A/B testing.

To get the best value from test results you need to apply statistical theory. Statistics can be very complex but there are some key concepts worth understanding such as confidence intervals, normal distribution and standard deviation. The key issue is knowing whether your results are sufficiently robust for you to be able to make reasonably accurate predictions based on them.

A simple example illustrates the point.

Suppose you toss a coin and it comes up heads. Can you assume therefore that it will come up heads every time you toss it.

The answer is clearly no because you do not have enough data to make a statistically valid judgement. If however it had come up heads 45 times in a row you can be much more confident in your prediction and can assume farly safely that it is heavily biased.

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