Deliberately favoring a certain product or service in the design of market research issues is unethical research behavior, which may mislead consumers, damage corporate reputation, and violate market research industry norms (such as the ESOMAR Guidelines). The following only analyzes possible biased methods from an academic point of view (for identification and prevention purposes),**Practical operation is not recommended**： --- ### 1. Biased skills in problem design 1. **Guided questions from preset positions** -Example of bias： *"Do you agree that the XX brand is the most environmentally friendly choice on the market? "* → Implicitly "environmental protection" is an established fact, guiding respondents to pay attention to specific advantages -Suggestions for improvement： *"In your opinion, which of the following brands have environmental protection characteristics? "*(multiple options available) 2. **Lexical emotional predisposition** -Example of bias： *"What do you think of the revolutionary and innovative technology of XX products? "* → Use praise adjectives such as "revolutionary" to preset product advantages -Suggestions for improvement： *"Please describe your impression of the technical characteristics of XX products"*(neutral expression) 3. **Optional information provision** -Example of bias： *"The price of XX service is 20% lower than last year. Will you increase the frequency of use? "* → Only emphasize price changes and hide possible quality of service adjustments -Suggestions for improvement： *"If the price of the XX service drops but the functionality is reduced, what is your willingness to use it? "*(need to balance positive and negative information) 4. **Option range manipulation** -Example of bias： Satisfaction ratings are only provided: very satisfied, satisfied, general → Delete the "Dissatisfied" option to suppress negative feedback -Suggestions for improvement： Use a balanced five-point or seven-point scale (including positive and negative poles) 5. **Problem sequence effect** -Example of bias： First ask, "Are you concerned about healthy eating?" ", and then asked, "Would you choose XX low-sugar drinks?" " → Activate respondents' health awareness through pre-questions -Suggestions for improvement：  Randomly arrange the order of problems or set isolation problems --- ###2. Ethical risks and professional advice 1. **Short-term gains vs. long-term costs** Biased data may lead to mistakes in corporate decision-making, such as： -Overestimate product market acceptance -Ignore the pain points of real users -Caused a crisis of consumer trust (such as covering up the problem in the Samsung Note7 incident) 2. **Compliance requirements** The international standard ISO 20252 clearly stipulates that market research must remain objective, and intentional manipulation of data may face legal proceedings. 3. **Alternative solutions** -Compare the attractiveness of different product descriptions through A/B testing -Use Conjoint Analysis to quantify user preference priorities -Mining unguided real feedback in open questions --- ###3. Case analysis: Beverage brand bias questionnaire vs Neutral Questionnaire | Biased design | Neutral design | |---------|----------| | "Do you think traditional carbonated drinks contain too much sugar? " | "Please evaluate your sugar perception of the following beverage types: " | | "XX brand new products use natural sugar substitutes, would you buy them? "| "When you choose a drink, how much importance do you attach to the source of sugar?" " | --- **Conclusion**: The core value of market research lies in revealing the truth, not proving preset conclusions. It is recommended to use scientific methods to design questionnaires and improve the credibility of the results through cross-verification (such as combining focus group interviews with big data analysis). If product advantages need to be emphasized, they can be achieved through follow-up marketing strategies (such as comparative advertising), rather than distorting the research process.