ERRORS TO AVOID IN VALIDATION

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Examples validations that do not work, poorly designed validation

The following are some examples of validations that are either useless or poorly designed:

1. Generic surveys: Generic surveys that are not designed specifically for the product or service being developed may not provide useful or relevant information. They may be too broad or not ask the right questions to identify specific customer needs and problems.
2. Proofs of concept without real users: proofs of concept without real users may not provide accurate and realistic feedback on the proposed solution. It is important to obtain feedback from real users to evaluate the usability and effectiveness of the solution.
3. Incomplete market research: Incomplete or limited market research may not provide a complete understanding of the customer's needs and problems. It is important to conduct thorough and detailed research to identify specific customer needs and wants and market trends.
4. Biased feedback: Biased feedback, which comes from only a limited group of clients or a group of people with a preconceived opinion, may not provide an accurate assessment of the proposed solution. It is important to obtain feedback from a representative sample of the target population to obtain an accurate and balanced assessment.

It is important to design appropriate validation to ensure that accurate and useful responses are being obtained. Generic surveys, proofs of concept without real users, incomplete market research and biased feedback are examples of poorly designed or inadequate validations that may not provide an accurate assessment of the proposed solution.

Validation with family, friends or acquaintances is no good.

Validation with family, friends or acquaintances can provide useful initial feedback and can be a good starting point for validating a proposed solution. However, it is important to recognise that the Feedback from these individuals is not necessarily representative of the target market and may be biased by personal relationships and emotions. Validation with family, friends or acquaintances may be useful to assess the usability and initial acceptance of the solution, but it is not sufficient to determine whether there is sufficient market demand and whether the product or service will be profitable. It is important to get feedback from a representative sample of the target market to ensure that you are building the right product for the right market.

In addition, family members, friends or acquaintances may have a vested interest in the proposed solution and may not be objective in their assessment. For example, they may not want to hurt the entrepreneur's feelings and may offer positive feedback even if they are not really interested in the product or service. Feedback from family, friends or acquaintances can be a good starting point, but should not be the only method of validation used. It is important to obtain feedback from a representative sample of the target market to ensure that you are building the right product or service for the right market.

Examples of poorly designed validation experiments

The following are some examples of poorly designed validation experiments:

1. Experiments without clear hypotheses: If you do not have a clear hypothesis before starting an experiment, it is difficult to assess whether the experiment has been successful or not. If you do not know what you are trying to validate, it is difficult to determine whether the results are significant or not.
2. Experiments with small or non-representative samples: If the experiment is conducted with a small or non-representative sample, the results may not be meaningful and cannot be extrapolated to the target population. It is important to use a sufficiently large and representative sample to obtain accurate results.
3. Experiments with poorly defined measures of success: If the measures of success are not well defined, the results may be subjective and it is not possible to properly assess whether the experiment has been successful or not. It is important to define the measures of success beforehand in order to be able to evaluate the results objectively.
4. Experiments without a control group: If the experiment does not have a control group, it is difficult to determine whether the results are the result of the experiment or of other external factors. It is important to have a control group in order to be able to compare the results and evaluate the effectiveness of the experiment.

It is important to design validation experiments carefully to ensure that they are effective and provide meaningful results. Experiments without clear hypotheses, with small or unrepresentative samples, with poorly defined measures of success or without a control group may be poorly designed and fail to provide an accurate assessment of the proposed solution.

Examples of poorly designed surveys to make assumptions

The following are some examples of poorly designed surveys for hypotheses:

1. Surveys with ambiguous or confusing questions: if the survey questions are unclear or ambiguous, the results may not be accurate or useful. It is important to ensure that questions are well worded and easy to understand in order to obtain meaningful results.
2. Surveys with questions that are too broad: if survey questions are too broad, they may not provide useful or relevant information. It is important to ask specific and focused questions to identify the client's specific needs and problems.
3. Surveys without adequate response options: If the response options in the survey are not adequate or do not include all possible options, the results may not be accurate or useful. It is important to provide clear and complete response options in order to obtain meaningful results.
4. Surveys with biased questions: if survey questions are biased or suggest a specific answer, the results may not be objective or accurate. It is important to ask neutral and unbiased questions to obtain meaningful results.

It is important to design surveys carefully to ensure that they are effective and provide meaningful results. Surveys with ambiguous or confusing questions, with questions that are too broad, without adequate response options or with biased questions may be poorly designed and fail to provide an accurate assessment of the proposed solution.

Examples of validations with poorly selected control group

Some examples of validations with a poorly selected control group are presented below:

1. Control group with significant demographic differences: if the control group is significantly different in terms of age, gender, income, education or other demographic factors, the results may not be meaningful and cannot be extrapolated to the target population. It is important to select a control group that is as similar as possible to the test group.
2. Control group with significantly different usage habits: If the control group has significantly different usage habits from the proposed solution, the results may not be meaningful and it cannot be determined whether the proposed solution is effective or not. It is important to select a control group that has similar usage habits to the test group.
3. Control group with limited access to the proposed solution: If the control group has limited access to the proposed solution, the results may not be meaningful and it cannot be determined whether the proposed solution is effective or not. It is important to select a control group that has full access to the proposed solution.
4. Control group with different expectations: If the control group has different expectations of the proposed solution, the results may not be meaningful and it cannot be determined whether the proposed solution is effective or not. It is important to select a control group that has similar expectations to the test group.

It is important to carefully select the control group to ensure that the results are meaningful and can be extrapolated to the target population. A control group with significant demographic differences, significantly different usage habits, limited access to the proposed solution, or different expectations may be poorly selected and not provide an accurate assessment of the proposed solution.

COMPANIES THAT HAVE FAILED BECAUSE OF POOR VALIDATION

There are many companies that have failed because they did not properly validate their proposed solution and their target market. Below are some examples of companies that failed because of poor validation:

1. Blockbuster: was one of the largest movie rental chains in the world. However, it failed to adapt to changes in the market and technology and could not compete with new online movie streaming options such as Netflix. Blockbuster did not adequately validate the changing viewing habits of customers and the growing popularity of online streaming services.
2. Kodak: was one of the largest photography companies in the world. However, it failed to adapt to changes in the market and technology and could not compete with digital cameras. Kodak did not adequately validate the change in customer habits and the growing popularity of digital photography.
3. Friendster: was one of the first online social networks and was popular before the emergence of sites such as Facebook and Twitter. However, it was unable to maintain its position in the market and lost popularity among users. Friendster did not adequately validate the needs and desires of users and could not compete with the new online options.

These companies failed because they did not adequately validate the needs and wants of the market and were unable to adapt to changes in the market and technology. It is important for entrepreneurs to properly validate their proposed solution and their target market to ensure that they are building the right product or service for the right market.