Cultural response bias

What is cultural response bias? 

Cultural response bias is the effect of respondents from different cultures answering in different ways to quantitative research. There are at least three types of cultural bias in the ways respondents answer quantitative questions in surveys. These are:

1. Acquiescence: a tendency to agree with what is being asked in the survey
2. Middling: a tendency towards neutrality
3. Nay-say: a tendency to disagree with what is being asked in the survey

Experienced researchers hold several truisms on cultural biases. Examples of these are that North American respondents react more positively to stimuli than the British, Japanese respondents typically nay-saying, or that many Indian consumers show an acquiescence bias when they are presented with a statement and ask if they agree or disagree with it (Tellis & Chandrasekaran, 2010).

Note: This article will make no attempt to attribute these biases to specific causes, they may be cultural, economic, or socio-political in nature. Instead, this article deals with the differences that we observe, and how best to account for these differences when running market research.

Accounting for cultural response bias 

It is essential to account for these biassed responses when analyzing the results of a study, as the extent of the differences can be considerable. For example, if you directly compared findings from a study containing Japanese and Indian respondents, there could be a difference as high as 2 on average Overall Appeal purely due to cultural response bias, which could greatly skew the findings if unaccounted for and lead to a faulty interpretation. Being aware of this type of bias beforehand also allows to put scores into perspective and avoid a shock at particularly high scores or particularly low scores for concept or advert responses.

Our findings exploring cultural variances

The meta-analysis capability on our platform allowed us to explore general cultural variances in survey responses across different tools, based on the library of tests run by platform users.

Below are the findings from the data collected using Zappi’s Concept Test, one of our product innovation solutions. Each row shows the average market score for the Overall Appeal measure, split by market and category (industry vertical). 

We found that Japanese respondents tend to score concepts lowly, US respondents tend to score concepts slightly higher than UK respondents, and Indian respondents tend to score concepts very highly.

Additionally, when we grouped the data by continent we found that:

• Respondents in the Asian countries Philippines, China, Vietnam, and India tend to score concepts higher than most other regions, with Japan as an exception.
• South American respondents appear to give fairly extreme scores, with Mexico and Brazil scoring concepts highly, but Argentina much lower on the spectrum.
• European countries appear to cluster towards the middle, perhaps displaying a tendency towards neutrality.
• Interestingly, when the North American markets are split, the US and Mexican respondents appear to score concepts slightly higher than Canadian respondents, who appear to score concepts more in line with European respondents, as do Australian respondents.

These trends are not only present within product innovation, but also within advertising - as shown above using the aggregated scores for Overall Appeal across Creative Video ads. 

Analyzing cross-country: how can I avoid bias?

The safest solution for cross-country analysis whilst avoiding cultural response bias is to analyze within countries first, utilizing the country and category norms available on the platform, and compare the eventual insights afterward. In other words, it is best to compare the scores for stimuli to the norms of the countries that stimuli are tested in, and then compare these differences to norms to each other across markets when making cross-country comparisons. 

It is important to note that country appears to be far more influential than a category when observing the data above, so it is almost always better to use a country norm containing many categories than a category norm from many countries.

Can I group my stims? 

With the Zappi platform, you have the ability to group your stimuli by market, as well as group your stimuli in any way you choose, create norms, and perform meta-analyses using tags of your own creation. 

A core element of our reporting platform is the ability to tag your tests with metadata. You can then aggregate survey scores according to the tags that you’ve applied. A tag can represent almost anything, but at Zappi we encourage our users to use them to codify the content of your stimuli. This could be as simple as marking the length of an advert, or whether a creative ends in a ‘chug shot’ of a consumer drinking from a carbonated soft drink. 

As your library of tested stimuli grows, you will be able to unlock additional value and insight from previously conducted research. This is achieved by both conducting retrospective analysis on the content of your previously tested stimuli and by establishing more relevant norms and benchmarks for future testing.