Implicit mobile research can minimize response bias in Asian markets

Marketers are realizing that the rapidly changing digital landscape requires new methods to accurately assess how today’s consumers think and behave. To evoke everyday uses of mobile technology, these new methods would be entertaining, replacing fact-based questions with fast-paced intuitive exercises. Implicit mobile research also reduces response biases prevalent in Asian cultures, providing a more accurate representation of consumers’ true preferences.

Not better left unsaid
Many Asian cultures are characterized by high context effects. In other words, in social settings, much is unsaid. Acquiescence and embeddedness are also prevalent in these societies and can distort survey findings through Acquiescent Response Style (ARS) and Socially Desirable Responses (SDR). ARS is the tendency to agree with propositions in general, regardless of their content, while SDR is defined as the propensity of respondents to answer questions in a manner that they expect will be viewed favorably by others. These effects are particularly strong when explicit judgements are sought and questions are administered by an interviewer who is physically present.

Over the past two decades, neuropsychological research has deepened our understanding of the human brain and raised serious questions about widely accepted research techniques. Daniel Kahneman’s “Thinking, Fast and Slow,” published in 2011, is probably the most significant popularizer of the “dual processing of information” theory, in which “system 1” refers to the brain’s fast, automatic, and intuitive side, and “system 2” is the slower, analytical mode. The distinction is significant, but the systems often work together, and considering either in isolation risks overlooking important elements of the decision-making process.

Uncover conscious and unconscious drivers of actual behavior
Traditional research methodologies tend to activate cognitive processes in the brain, creating a bias toward rational outcomes that are incomplete reflections of actual consumer behavior. This reality calls for the creation of a new methodology that bridges conscious and subconscious drivers and produces practical, actionable results. In addition to its popularity and familiarity, mobile technology can both eliminate the need for an interviewer and allow the participation of people who may have been underrepresented in traditional online panels.

SKIM’s mobile implicit testing methodology consists of two core modules. In the attraction module, consumers swipe a series of stimuli to the right if they like it and to the left if they do not, with each stimulus shown in isolation. We know judgments made quickly and in isolation tend to be more automatic, emotional, and associative. In the conversion module, consumers compare two competing stimuli. These joint judgments tend to trigger rational processes and simulate actual conditions of choice, such as at a supermarket shelf.

Case study: Shampoo claims in Asia and Austrailia
To determine the effects of the new mobile methods on the response biases of interest, a study presenting claims about shampoos was conducted with samples from India, Singapore, and the Philippines, representing variation across Asian cultures, and Australia, a more Western culture where response biases were expected to be less pronounced. The shampoo category was used because of its universal appeal and high penetration across markets. Claims were selected to represent product characteristics that could trigger different responses across cultures. All were presented in English, commonly used in each of the countries, to maximize the comparability of the results and minimize any effects of translation.

SKIM’s new mobile approach was found to mitigate the bias produced by Acquiescent Response Style bias in the three Asian countries when compared to traditional methods such as rating and MaxDiff. In Australia, no significant adjustment towards a more consistent mean could be observed.

Claims that could be identified as highly socially desirable within the various cultures performed less well in this study as compared to traditional methods, and less socially desirable claims performed better on average. In other words, the responses of the individual are more likely to deviate from social desirability when the new method is employed. This result suggests that the new approach filters out some response bias, more accurately measuring what consumers are really thinking.

The last component of the study asked respondents to compare this method to traditional approaches. The baseline score for the traditional methods was relatively high, possibly because the survey was shorter than most. Nevertheless, in three of the countries the new method produced significantly higher engagement levels.

Overall, the results support the hypothesis that traditional methods such as rating and MaxDiff favor stimuli that are socially desirable because they rely more on rational processes of the brain. When the need for these rational processes in answering questions is reduced, so are certain types of biases. Consumers appear to appreciate this new way of conducting research, which keeps them engaged and provides information that is both more meaningful and more reliable.

Editors note: SKIM will be speaking and exhibiting at the upcoming MRMW APAC conference on June 28-29 in Singapore. Join Robin de Rooij and his team and learn about their latest mobile research methodologies.

Author

  • Robin de Rooij

    Robin de Rooij is Director APAC at SKIM, a global market research firm specialized in choice and decision making behaviour. With more than 8 years of experience, Robin has performed research in FMCG, Telecom, Services and Technology industries. He is able to translate business problems into customized research solutions and does not shy away from new approaches.

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Robin de Rooij

Robin de Rooij is Director APAC at SKIM, a global market research firm specialized in choice and decision making behaviour. With more than 8 years of experience, Robin has performed research in FMCG, Telecom, Services and Technology industries. He is able to translate business problems into customized research solutions and does not shy away from new approaches.

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