The field of affiliate marketing is moving out of its first stage of growth and a new profession is coming into focus. To sustain the profession, new entrepreneurs must be trained. Entrepreneurs who have found success in the market decide to formulate that success as training programs. They tell you about their fabulous successes, they tell you the best way to be successful in the business is to find someone who has been successful and do what they do. Success has happened for them, it can happen for you. After all, they were exactly where you are. You are told they are no different from you. And all that contains much truth. It is easy to believe these stories, because you want to believe them. But can you really know if you will be successful as an entrepreneur? The answer is no. But you can get an idea of your chances, and that is much better than a wild guess or emotional laden intuition. In this post, I will explain how to do that.
Population of Customers
When a training program tells you that it will work for you, the program actually refers to many more people than just you. What the program claims is that the program will be effective for everyone in the United States. If the program is being sold in the United States and Europe, then it claims to be effective for everyone who lives in the United States and Europe. Advertisement never explicitly states these claims. As far as you are concerned, the ad is all about what it can do for you. All the people who would conceivably purchase the program is called the population for which the program was made. So, lets assume the program is very effective in teaching you to be an entrepreneur. However, not everyone who will purchase the program learns exactly like you do. Not everyone has the same background knowledge that you have. Not everyone has the same learning skills you have. There is a large variety of learning abilities in the population of all people in the United States who would purchase the entrepreneur program. So, to suggest that the program will be effective for everyone is making a large statement. The program developers can’t possible know everyone in the population. There are at least 50 million. So, upon what do they base their claim? Are they just guessing?
The Experimental Group
Lets assume you are a researcher and want to know if a particular, Affiliate Program A, will be effective with all your potential customers. You realize that you have about 50 million potential customers. The only way to answer your question is to give all 50 million the program and see if it is effective with the majority of customers. Obviously, that is impractical. You have to shrink your testing group. Maybe, you can test 50 people. So, who do you test out of the 50 million. You have in your experimental toolbox, a device called random selection. The idea in the experimental group is that it will be very similar to the entire population of customers. That means the customers you will select to test the program will have all the variety of learning skills that are found in the population of 50 million customers. If you try to decide which customers to pick, you will likely pick a group of people that possess only a small part of the learning skills found in the total population of 50 million customers. You have biases that your not even aware if having. These biases will come out in your choosing. However, you random selection device has no such biases. It doesn’t have any ideas about who should be in your group. Thus, the random selection device will likely pick a group of 50 customers that possess the variety of learning skills found in the total population of 50 million customers.
Randomization of Experimental Group
By randomly choosing the people who will test your program, you have the best chances of choosing a group that has the same variety of learning skills as is found in the population of 55 million. Not only does your chosen group have the same skills as the population of possible students, but they have those characteristics in the same proportion as does the total population of possible students. Thus, your group that will test the program for you looks exactly like the population of 55 million people who will be buying the program. This experimental group is just smaller. So, if the program works for most people in the experimental group, it will likely work for most of the 55 million people in the population.
Low Probability of Data Set
Having a small group of people who have the same learning skills as those in the general population, you give them the test. Because of their similarity to the population, you are essentially giving the test to the 50 million people, even thought your group is only 50 people. Their scores on the program are what we call a data set. Most people think that when scientist run a test, they are testing some theory or statement about how the world works. That is not exactly true. Science works with sets of data and it only asks one question: Could this data set have happened by chance? The scientist then applies a statistical test to the data set to determine what its probability is to have happened by chance. The scientist wants to know that if they give a similar group of people the same test, will they make similar scores. If the statistical test says the probability of the data set happening by chance is 1/100, then the chances that a different but similar group of people will make a different score is very low. The scientist concludes that the results of the test did not happen by chance. If the scores were high, then the program is probably effective in teaching people to be entrepreneurs. If the scores were low, then the program is probably ineffective in teaching people to be entrepreneurs. This is how the developer of the program can claim that the program will teach you, an individual among 50 million others, to be an entrepreneur. But what if the program developer is making these claims and these scientific tests have not been done?
Importance of a Test Drive
If a program developer has conducted these tests, then they will tell you. It is good advertisement for their program. But what I find in the industry is not description of test results but enthusiastic descriptions of programs. You can be assured these tests are not mentioned because they have not been done. When scientists do these tests, they don’t just test one experimental group, but several. The more groups tested the more confidence one will have in the results. In science, nothing can be concluded from a single study, because one more study might find something quite different. So, what is the next best thing to adequately testing a program, allowing the customer to test drive the program for free. Most customers will have a decent opinion within a few lessons if the program will be effective for them. This is not as convincing as the scientific studies described above, but it does give the customer a chance. I’m aware of only one affiliate marketing program that gives the customer a free test drive. That is Wealthy Affiliates. Giving the customer an option of dropping out of the program within a certain number of days, usually very few, and getting a percentage of the cost of the program back does not do the same as a test drive. In a test drive, the program developer is alerting the customer to pay attention to the effectiveness of the program and to make a decision about its effectiveness. To me, that is basically different. For sure, the profession of affiliate marketing should start testing its educational programs, but until it does, a good test drive is the next best guarantee of quality for the consumer.