By Darren W. Dahl and Reto Hofstetter
The term “crowdsourcing” was first defined in 2005 by the editors of Wired magazine to describe how organizations began leveraging internet users to outsource tasks. Over the years, the notion has been defined in a variety of ways (e.g., crowdfunding, crowdvoting, and crowdsolving), with specific application to business, government, and nonprofit organizations’ innovation efforts. Indeed, companies in almost every business vertical— from Lego to BMW to Frito Lay—have embraced crowdsourcing to gather new ideas and engage the broader consumer marketplace.
In response, researchers have done significant work to define crowdsourcing’s advantages and limitations. The work has broadly shown crowdsourcing provides organizations enhanced innovation performance, increased sales, and better customer engagement (Boudreau and Lakhani 2013; Kohler 2015). Ramamurti (2020) even suggested the strategy could be used to address the COVID-19 pandemic.
Other scholars have identified significant limitations to crowdsourcing, including idea quality variability, brand reputation risks (Verhoef, van Doorn, and Beckers 2013), and misleading idea quality signals (Hofstetter, Aryobsei, and Herrmann 2017).
Most recently, several Journal of Marketing Research articles have sought to add insight to the crowdsourcing discussion. Specifically, researchers have examined how to manage innovation crowdsourcing to optimize success probability in the context of online platforms and innovation contests. Other scholars have explored the value of signaling to potential customers that a product has been crowdsourced.
Managing the Crowd for Success
Stephen, Zubcsek, and Goldenberg (2016) have investigated the role of social networks in facilitating innovation in crowdsourcing platforms. The authors note that many crowdsourcing platforms have adopted interdependent ideation, whereby customers can be exposed to or inspired by others’ ideas when defining their own. The researchers used an experimental approach to determine how a network of other customers’ inspirations affected individual customers’ innovativeness. They showed that a high level of interconnectivity between the social network defined on a crowdsourcing platform could negatively impact innovativeness among ideas produced. The researchers suggest the outcome is due to the redundancy and similarity of ideas shared when a social network is defined and when its members actively communicate with one another. The authors advise that firms can attenuate the issue by explicitly instructing crowdsourcing participants not to rely on other customers’ ideas for inspiration.
Building on the research, Hofstetter and colleagues (2021) show that the number of potential solutions to a task shown on crowdsourcing platforms can significantly impact innovation outcomes. Using an innovation contest (a common modern crowdsourcing mechanism), the authors found that exposure to numerous competitive ideas harmed rather than stimulated creative performance. Importantly, they found the competitive display of others’ ideas underlay the effect, as exposure to an increasing number of ideas demotivated participants. The researchers found noncompetitive exposure to an increasing number of ideas benefited participants by inspiring creative efforts. The authors spotlight multiple strategies firms can use to mitigate the harmful influence of competitive exposure, including limiting the number of crowdsourced ideas shown or categorizing the ideas.
Communicating Crowdsourcing to Consumers
While researchers have done considerable work to define crowdsourcing’s value, few have sought to understand consumers’ feelings and attitudes toward crowdsourced products and services. So, does marketing products to consumers as crowdsourced have benefits?
Recent research by Nishikawa and colleagues (2017) shows that labeling new products as crowdsourced can improve market performance. The authors used field studies to show that marketing products as crowdsourced increased sales by up to 20%. Their follow-up, controlled studies showed that a quality inference for crowdsourced products drove the positive outcome. In other words, the researchers found some consumers believed crowdsourced products would address their needs more effectively and be more likely to be successfully designed than non-crowdsourced products.
Song, Jung, and Zhang (2021) provide additional insight into when communicating crowdsourcing to consumers is likely to be beneficial. They found consumers preferred either consumer-designed or designer-designed products depending on context. The researchers showed that the consumer’s power distance belief (PDB) moderated which type of product was preferred. Specifically, they found that low-PDB consumers, identifying more with crowdsourcing companies, preferred consumer-designed products, whereas high-PDB consumers preferred designer-designed products. The authors found the effect pattern at both the country and individual PDB levels. The research suggests that crowdsourcing’s positive effect is not ubiquitous, and marketers are best served by the approach if it resonates with their target consumers and fits their product context.
Crowdsourcing has become an essential instrument in every marketer’s toolbox, and recent research provides guidance for how firms can best use the strategy. Although putting a brand in a crowd’s hands poses risks, the benefits prevail when the firm implements crowdsourcing judiciously. Managers should ensure that the crowd is heterogeneous so consumers truly benefit from finding each other’s ideas inspirational rather than competitive. As it pays to market products as crowdsourced, marketers should find effective ways to communicate their efforts. And they must carefully balance the efforts, as some consumers such as those with high power distance belief, prefer designer-based products.
Darren W. Dahl is Innovate BC Professor, Marketing and Behavioral Science Division, UBC Sauder School of Business, University of British Columbia.
Reto Hofstetter is Professor of Marketing, Faculty of Economics and Management, University of Lucerne.
Dahl, Darren W., and Reto Hofstetter (2021), “Crowdsourcing for Marketing Success,” Impact at JMR, (November 17, 2021), Available at: https://www.ama.org/2021/11/17/crowdsourcing-for-marketing-success/
Boudreau, Kevin J., and Karin R. Lakhani (2013), “Using the Crowd as an Innovation Partner,” Harvard Business Review, 91(4), 60–9. (https://hbr.org/2013/04/using-the-crowd-as-an-innovation-partner)
Hofstetter, Reto, Suleiman Aryobsei, and Andreas Herrmann (2017), “Rethinking Crowdsourcing,” Harvard Business Review, (November–December), 19–22. (https://hbr.org/2017/11/rethinking-crowdsourcing)
Hofstetter, Reto, Darren W. Dahl, Suleiman Aryobsei, and Andreas Herrmann (2021), “Constraining Ideas: How Seeing Ideas of Others Harms Creativity in Open Innovation,” Journal of Marketing Research, 58(1), 95–114. (https://doi.org/10.1177/0022243720964429)
Kohler, Thomas (2015), “Crowdsourcing-Based Business Models: How to Create and Capture Value,” California Management Review, 57/4 (Summer), 63–84. (https://doi.org/10.1525/cmr.2015.57.4.63)
Nishikawa, Hidehiko, Martin Schreier, Christoph Fuchs, and Susumu Ogawa (2017), “The Value of Marketing Crowdsourced New Products as Such: Evidence from Two Randomized Field Experiments,” Journal of Marketing Research, 54(4), 525–539. (https://doi.org/10.1509/jmr.15.0244)
Ramamurti, Ravi (2020), “Global Crowdsourcing Can Help the U.S. Beat the Pandemic,” Harvard Business Review, (October). (https://hbr.org/2020/10/global-crowdsourcing-can-help-the-u-s-beat-the-pandemic)
Song, Xiaobing, Jihye Jung, and Yinlong Zhang (2021), “Consumers’ Preference for User-Designed Versus Designer-Designed Products: The Moderating Role of Power Distance Belief,” Journal of Marketing Research, 58(1), 163–181. (https://doi.org/10.1177/0022243720972702)
Stephen, Andrew T., Peter P. Zubcsek, and Jacob Goldenberg (2016), “Lower Connectivity is Better: The Effects of Network Structure on Redundancy of Ideas and Customer Innovativeness in Interdependent Ideation Tasks,” Journal of Marketing Research, 53(2), 263–279. (https://doi.org/10.1509/jmr.13.0127)
Verhoef, Peter C., Jenny van Doorn, and Sander F.M. Beckers (2013), “Understand the Perils of Co-Creation,” Harvard Business Review, 91(9), 28. (https://hbr.org/2013/09/understand-the-perils-of-co-creation)