The following is the Combine qualitative and quantitative research to evaluate the advantages and disadvantages of brand / product names recommended by recordtrend.com. And this article belongs to the classification: User Research.
The customer in the text refers to the ordinary consumer in the market (≈ C end), and the client refers to the company that purchases the market survey solution (≈ B end)
01 qualitative research
The goal of the qualitative stage is to explore consumers’ minds and refine their voices.
The qualitative stage will collect ideas at the conscious or subconscious level, which will help us design quantitative tests later.
Qualitative research can learn a lot of information about attitudes, beliefs and views, and also compare the differences in different social and psychological backgrounds.
Qualitative research provides customers with the possibility to better understand and evaluate consumer behavior and emotions.
Therefore, customers can know which names will cause positive or negative feedback from consumers.
Focus groups will help us further explore and understand the views of current or potential consumers.
Focus groups will explore these elements:
1. Demographic characteristics of consumers
2. How product names affect consumers’ purchase process
3. Positive and negative reactions to candidate names
4. What is missing from a name?
5. How easy is the name to remember?
6. What ideas will the candidate name evoke?
7. Why do you prefer name a to name B?
8. What is the lifestyle of existing or target consumers and why do they use such products?
9. Their emotions about the product
10. Consumption and purchasing habits
02 quantitative research
The objective of the quantitative stage is to score and sort each candidate product name (a total of 4).
Quantitative research will gain insights into product name preferences, market information, and exhausted / unfinished needs.
Based on our experience in similar projects, we suggest using quantitative methods to deal with “consumer voice”.
The following online consumer surveys can be quantified:
1. Preference for candidate product names
2. Importance level of product name
3. Will they not buy the product because of its name
4. How often they buy a product with a specific name
5. How often they buy products and how they use them
6. Their attitude and use of products
For each product, we will ask two questions, plus a third tracking question:
The first question is the fixed total allocation question, which is used to measure relative preference
For example:
Assign 20 points to the following four product names, and your allocation result represents your relative preference for these names.
Such questions are used to measure the degree of preference (which can be interpreted as equidistant or proportional data).
It should be noted that the total score setting needs to be divisible by the number of names participating in the test, so that respondents with no difference in preferences can give the same score for each option (for example, here, 4*5=20).
The second question is about absolute liking for the favorite option
For example:
If 1 indicates very dislike and 7 indicates very like, how would you rate your favorite product name in question 1?
This 7-point scoring scale is the classic Likert scale, but other scales are also feasible.
But remember, the scale with odd points allows the respondents to give neutral answers, while the even scale (such as 1-10 subscale) will make the respondents unable to give neutral answers in a mathematical sense. I think it is desirable in this case.
In question 3, only those respondents whose scores in question 2 are lower than a certain threshold are asked to explore whether there is a better alternative
For example:
Can you provide a better name than [the best choice you chose in question 1] in your opinion?
This question should be allowed to skip, and it needs to be answered in a very short time (such as 5 seconds) in order to get a subconscious answer, rather than a thoughtful answer.
Some alternatives and insights
The survey can also ask the second question about only four products, and then infer the relative preference from the absolute preference.
However, compared with the fixed total allocation question, the participation depth of the respondents will not be so deep, and there will be the risk of “choosing the same for all”.
This risk may come from the respondents’ unwillingness to make judgments, or the mentality of “I’ll just fill in and get the money”.
When it comes to alternative names, some companies will give a name that is semantically related to the product.
However, this also means that in the same category of products, names may be interchangeable.
If so, we can also naturally ask the respondents a “matching” question.
For example:
Please choose the best name for these four products from the seven candidate product names.
Some customers will imagine different consumer portraits for these four products.
These portraits are mainly a combination of categorical variables (gender, age group, race / ethnicity, etc.).
Therefore, these information can also be collected in the survey, so that we can judge whether there are differences in the attractiveness of different candidate names between demographic backgrounds.
03 strategic analysis
The strategic analysis will combine the information obtained from the qualitative research (focus group) in the first stage and the quantitative research (online consumer survey) in the second stage, and display it in a coherent and effective form.
The deliverables can be a comprehensive ppt report, including:
1. Consumer perception of candidate product names
2. Positive reaction
3. Negative reaction
4. Factors affecting consumers’ perception of product names
5. Advanced analysis
6. Best name for each product
7. Recommended name
8. Conclusion
For advanced analysis, it is best to ask questions first, and then choose the corresponding analysis tool.
However, considering that we use discrete options on target variables (product names) and demographic variables, we can explicitly use nonparametric tests to examine the relationship between ordered data.
Cluster analysis and logistic regression may also be helpful, depending on what the customer wants to know and, more importantly, the result itself.
For example:
Within the target variable: will respondents who like one name also prefer another name? Are there high preference “clusters” between names?
Between target variables and demographic variables: will respondents with some demographic backgrounds prefer some names? Is the absolute preference of names related to demographic characteristics?
The final deliverable will be a high impact report that provides management with an action plan.
作者 | SIS INTERNATIONAL MARKET RESEARCH
原题 | Brand Name Testing Market Research
Translation | big cake
Proofread | Duke
Transferred from | uxren
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