When community members take over…
In our previous post, we’ve highlighted the opportunities of collaborating with participants as co-moderators. Next to moderation, participants can also add value when they are involved during the analysis phase, also referred to ‘crowd-interpretation’. The rationale behind crowd interpretation is that analysis of data is biased by a researcher gaze. To get all potential interpretations and insights hidden in the data, we should need to include multiple perspectives.
Participating in crowd-interpretation
Interpreting community data. Recently, we conducted an insightment community in cooperation with Air France and KLM where we wanted to detect new needs of transfer passengers. After an observational stage where each transfer passenger reported on their journey, we invited the community members to interpret each other’s contributions. From previous research (Verhaeghe et all, 2011), we know that consumers that are knowledgeable about the topic are most suitable for interpreting research results.
The crowd interpretation was done in a game. During the first round, members had to give their interpretation on the input of their peers. In the second round, the original contributor could rate the analysis. Upon each correct analysis, one could receive points. Consumers who were best in the analysis (highest amount of points) won the game and got a special incentive. Comparing the results of researcher group with that of the participants, we conclude that involving co-researchers leads up to 21% new insights, otherwise not reached. (Verhaeghe, et al., 2012) ; Verhaeghe et al, 2011). Thus, involving community participants in the analysis phase brings new insights to the table and helps researchers to close the gaps.
Dry-running your presentation for consumers
Another way to involve participants in the tasks of the researcher is by asking them to fine-tune our conclusions, almost like a dry-run for the community participants instead of the company. This technique was used in a recent study we did for Philips.
Fine-tune researcher’s conclusions. Last year, we setup a 3-week insight shaping community with 50 Chinese consumers together with Philips. Normally, we would work with a native moderator. Due to time constraints, we had to work with a non-native moderator and the community was run in English, while the fear existed we would lose out in terms of the fine nuances in Chinese culture and society. To avoid this caveat and increase positive feedback loops for enriched information generation we used 10 of our participants as our co-researchers in a process of crowd interpretation.
After our analyses of the community outtakes these participants would be presented our findings and asked to challenge them. In performing the task of crowd interpretation these participants were asked to explain our findings from the Chinese cultural perspective, illustrate our findings with their own personal examples as well as go beyond our first impressions. Working with co-researchers created truly unique insights that were key for Philips to find the right positioning in the Chinese market. We, as researchers and marketers would never have uncovered these insights from an online distance (Schillewaert et al, 2012).
A new milestone in the researcher-participant relationship
Based on these 3 case studies, we have truly experienced the added value of co-researchers in communities, learned how and when to use it and developed a future outlook.
Co-researchers help you to close culture, contextual and knowledge gaps. First of all co-researchers help you to overcome a knowledge barrier. Community participants all share a strong interest in a brand or topic. The more niches the theme will be, the bigger the knowledge gap and the harder it will be to moderate specific discussions and draw the right conclusions. Secondly, co-researchers can help you to close a contextual blind spots For example, we also conducted crowd interpretation for a Gen Y community in cooperation with MTV. The researchers involved in this Gen Y community were not all from Gen Y. Using crowd-interpretation with likeminded peers of the participants generating the data, helped us to overcome this generation gap. Finally, the last case shows that co-researchers are crucial to overcome the cultural barrier. These co-researchers know their culture and go further than researcher’s first impressions.
Co-researchers are the ultimate level of community engagement. Another key learning of working with co-researchers is that it’s not for everybody. It’s an extra challenge that participants need to be interested in and perceive as an exclusive reward. Therefore, we consider co-researchers as the ultimate level of method engagement, rewarding selected members to become an official co-owner of the community.
Co-researchers are the future of our profession. Participants are no longer used for exploitation for our research needs and have become our partners with whom we collaborate. When we put community participants into a different context such as a co-researcher, it does not replace the researcher. In contrary, it proves that we are building a long-lasting relationship with our participants; it’s a synergy. And sharing the responsibility of the community with participants reaffirms this new relationship. We believe this is the next step in collaborating with community participants and is the way forward for our profession as market researchers.
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