Saturday Nov 25 2017

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Why Test?

Marketing should be treated like a science. If you are serious about making money on the Internet, it is absolutely crucial that you spend some time testing your results and refining your approach.

Let me drive this point home. Say for example you have a website that gives you a visit to sale ratio of about 200 to 1. Not really bad as far as web sites go. Most do far worse.

Now, assume that you get 5,000 visits per month. Do the math. That’s 25 sales per month. If your profit from each sale is $50, you are making $1250 per month profit from your website.Now, what would happen, if by changing one small thing on your website, you could improve that ratio to say 150 to 1. It may not seem significant, but let’s see how it works on paper.

Now, instead of 25 sales per month, you are doing 33. Multiply that by $50 and you are now making $1650 per month. That’s a difference of $400. It’s not like you’re having to work any harder for that additional $400. Your website is always there.

Now, the example I have shown you here is quite mild to some of the drastic improvements I have seen as a result of market testing. All my life I’ve heard people say "don’t work hard - work smart!"

This is excellent advice. Working smart means getting more from less effort.

Well, testing is a systematic way of helping you to work smart. It’s just like the scientific method, really. You may remember it from school. There are many versions of the scientific method for different disciplines and many scientists will argue about which approach is best. For our purposes, let’s take a very bare-boned and simple version. It’s really all we need:

a. Generate a hypothesis.

b. Test your hypothesis by performing an experiment and recording the results.

c. Perform calculations and draw conclusions.

d. Confirm or refine your original hypothesis.

For example, let’s say in the above example, we hypothesize that by adding a money back guarantee, we will get a better visit to sale ratio. This is our hypothesis. To test this, we make the change on our websites and record our results. That’s our experiment. After a few weeks (or any period of time we determine to be sufficient) we conclude the experiment and perform calculation on our data. We then discover that the visit to sale ratio did, indeed, improve during the course of our test run. We can then draw a conclusion that our original hypothesis is correct.Seems pretty simple, right? Well, actually no...

Controls and Statistical Significance

In the preceding example, we did a pretty straightforward and simple test. However, the results we have drawn may not be valid.

For example, what if the majority of visitors we received before the test run came as the result of a banner ad campaign we were running? Then, without us knowing it, sometime during the campaign a company favorably reviews our product and drives people to our site. It could be the case that people who read that review were more likely to buy the product.

It could also be the case that they were much more likely to buy and that adding the guarantee lessened the effectiveness of the site. Or, it could even be the case that the guarantee did increase the effectiveness of the site, but not as much as we thought.

The problem is, we just don’t know.To address this issue and to improve the reliability of our tests, we need to establish "controls". A control is a measure that allows us to isolate the factors which are causing the effects we record.

For example, a better way to run this test would have been to run two websites at the same time. Both of them identical in every way (promoted the same way, designed the same way - everything) except for the one element we think will make a difference. The site without the change is called the control site. The site with the change is the test subject.

This same principle can be applied to any other type of marketing. If you want to test the effectiveness of a banner ad, run two banner ads on the same site for the same period of time. If you run one banner ad on one site and the other on yet a different site, you can’t be sure that your results are valid.

Using strict control techniques improves the chances that your findings will be valid.

Statistical Significance

Even if we use good controls, we can still never be sure of our results. There may be something affecting the test we haven’t thought of. That’s why we also need to resolve ourselves to the fact that the results of one single test should not be accepted as conclusive.

Rather, we need to perform a great many tests and look at the over all trends. Only after we have compiled a considerable amount of information can we safely draw any conclusions.

Just how much testing is enough is up to you. You should test until you are satisfied, but be honest with yourself. Don’t just stop testing out of laziness!

Turning tests into profits

The idea here is to test as many different methods as possible, discover the most effective method, and crank up the volume on your best method. When you get into serious volume and your business is really doing well, even minor differences in results will have a major impact on the amount of money you take home. And sometimes very subtle and minor changes to a website will make huge differences in your results.

If you could find out which of your advertising campaigns was bringing in the most money for you, wouldn’t it make sense to put more effort into that campaign? Or do more of that type of campaign? Wouldn’t you be crazy not to?

Tracking is just recording the results of one campaign or another.

Testing is the systematic monitoring of these campaigns to discover what is working and what is not using the scientific method.


Article by Mark Joyner, was the former CEO of Aesop Marketing Corporation and creator of 1001 Killer Internet Marketing Tactics - a *must have* tool for anyone serious about doing business on the Internet. Do yourself a favor and check this one out today. Today Mark hangs out at Mark Joyner.name

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Article by Mark Joyner, CEO, Aesop.Com

Marketing should be treated like a science. If you are serious about making money on the Internet, it is absolutely crucial that you spend some time testing your results and refining your approach.

Let me drive this point home. Say for example you have a website that gives you a visit to sale ratio of about 200 to 1. Not really bad as far as web sites go. Most do far worse.

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