What are the advantages of using a Likert scale in market research?

A Likert scale is a widely used psychometric tool that measures attitudes and opinions by asking individuals to respond to a series of statements or questions. Respondents indicate their level of agreement or disagreement with each statement using a predetermined set of response options. A typical Likert scale consists of a series of statements or questions, each followed by a set of response options. The response options typically include: Strongly Disagree Disagree Neutral Agree Strongly Agree The Likert scale is commonly used in market research, social sciences, psychology, and various other fields to measure and quantify people's opinions, attitudes, perceptions, and preferences.

It is more intutive. An objective response on a subjective topic like attitude, lifestyle, behaviour. So it helps capture the most intutive response based on (degree and scale of ) experiences

A Likert scale is used in various research and survey contexts for several compelling reasons Measuring Attitudes and Opinions Quantitative Data Precision Standardization Comparative Analysis Easy Graphical Representation Reduced Social Desirability Bias Ease of Reporting Results from Likert scale questions can be summarized and reported quickly, streamlining the reporting process. Likert scales are a popular and effective tool in research

Writing effective Likert scale statements is crucial to ensure that the collected data accurately reflects respondents' attitudes or opinions. 1. Clearly define what you want to measure or understand. 2. Choose a specific topic or concept that aligns with your research objective 3. Choose an Appropriate Response Format 4. Write statements that are clear, concise, and easy for respondents to understand. 5. Maintain consistency in the language and phrasing of statements. 6. Before deploying the Likert scale in your survey or research, conduct a pilot test with a small sample of respondents. 7. Be prepared to revise Likert scale statements based on the feedback and insights gained from the pilot test.

Likert scale data collected across cultures/markets are tricky to merge & analyse together. Hence this step requires a deep understanding of the cultural nuances that impact how people respond to Likert scale questions Different cultures respond to the scale differently, with some markets (eg, the Philippines) being high-rating and others (eg, Scandinavian ones) being consistently low-rating. This is driven by a variety of factors: 1. Cultural norms: eg In many parts of Asia is seen as 'rude' to say 'don't agree/like' when being asked for your opinion 2. Linguistic differences: 'Very' and 'Somewhat' are not equidistant in people's minds across cultures 3. Educational differences: Education does impact grasp on numbers/nuanced phrasings

Clean and organize the data. Address any missing or incomplete responses. Calculate basic descriptive statistics to get an overall picture of the data. Create frequency distributions for each Likert scale item. This displays the distribution of responses for each statement. Assess the reliability of the Likert scale items using internal consistency measures like Cronbach's alpha. Create visual representations of the data, such as bar charts, histograms, or box plots, to visualize the distribution of responses and trends in the data. Keep in mind that the specific analysis techniques and approaches may vary depending on the nature of your research, the number of Likert scale items, and your research objectives.

To address the challenges I raised above, here are potential solutions: 1 Use a culturally sensitive Likert scale: Adjust the scale descriptions to include more culturally suitable labels or just use a different scale altogether 2 Replace the Likert scale with a semantic scale, which use words/phrases to measure agreement/disagreement, without use of a scale 3 Translate carefully. Make sure that the translations are accurate & culturally right 4 Pilot the survey to check the response patterns. Will help identify any potential problems with answer options/translations before the fieldwork launch. 5 Normalise the data. Statistically adjust the data collected to account for differences in response patterns between different cultures

Improving a Likert scale question is essential to ensure that it effectively measures respondents' attitudes, opinions, or perceptions. Major tips to follow are Be Clear and Specific, Avoid Double-Barreled Questions, Avoid Double-Barreled Questions, Offer a Balanced Range of Responses, Offer a Balanced Range of Responses and Review and Revise. Improving Likert scale questions is an ongoing process that requires careful consideration, testing, and refinement. Well-constructed questions lead to more accurate and valuable responses, enhancing the quality of your research data.