Crowdfunding and the dynamics behind it have dynamically evolved year-over-year. It is difficult for researchers to study crowdfunding and have the ability to suggest recommendations that will hold valid for more than 6 to 12 months.
A prominent example of this is the most funded project at the time of the paper written by Mitra & Gilbert (2014) – the Pebble Watch. I won’t go deep into how Pebble achieved this success, especially since it seems that it is the only crowdfunding project that deserves attention and is repeatedly mentioned across the body of research on crowdfunding. Rather, I’d like to point out a couple developments that have occurred since the year that this paper was published (2014):
1) Pebble went from a valuation of $740 million to less than $40 million
2) There is no more technical support for Pebble, since it’s assets have been acquired by Fitbit.
3) in 2016, Filippo Loretti (the most funded watch project currently) was funded 480.000% while Fitbit was funded “only” 100.000%
This points to two important insights: (1) Having a successful Kickstarter does not guarantee a brand’s success (even in the example of the most funded Kickstarter project which authors present in their introduction as the “status quo”) and (2) There other more interesting numbers that might hint towards why a project is setup in a way towards funding success.
In their paper, Mitra & Gilbert (2014) focus on a particular interest component of Kickstarter campaigns – the phrases used on the project’s page (independent variable) and how it affects a project being successfully funded (dependent binary variable). After presenting past research that has confirmed variables such as including a video (which is now mandatory on Kickstarter) or the size one’s social network having an effect on success of a crowdfunding campaign, the authors delve into exploring whether and how particular language used affects a project’s campaign on crowdfunding platforms.
Below is a breakdown of the strengths and weaknesses of this paper:
First, the authors used a very clear method in identifying which phrases from Kickstarter pages would be assessed. By removing “niche” phrases that were often category-specofic, Mitra & Gilbert were able to compile a list of common general phrases and measure their effect on a project (not) being fully funded.
Second, to avoid the potential distorting effects of confounding variables, the authors included a large variety of control variables – namely 59 Kickstarter variables that were identified as possible predictors of funding. This then allows the authors to identify whether there is a direct correlation between phrases used in Kickstarter campaigns and their eventual funding success.
Third, using big data methodology, the authors engaged in creating a predictive model – one that does not over-fit to the data (since there is a large data set). Using a ten fold cross validation method and expanding the features list until there is no more substantial gain in the explanatory power, they were able to effectively asses the impact of the independent variables on the binary dependent variable.
First, based on the industry observers, the author believes that there will be several crowdfunding sites that will emerge and join ones that are already on the internet. However, such a statement does not say much about the competitive environment of these platforms and that although copycat businesses will evolve, eventually only a one or two will be “prominent,” similarly to what has occurred in the space of social media. To fix this, the authors should focus more on explaining why new emerging crowdfunding sites will be relevant to the space of crowdfunding.
Second, the authors used a binary response variable for their dependent variable. Although this is interesting in general, it does not explore the phenomenon of over funded projects (and how much they got over funded). This particularly related to the aforementioned comparison of Pebble and Filippo Loretti. To fix this, the author could have included % funded as a moderating or mediating variable.
One of the key takeaways from the paper by Mitra & Gilbert (2014) is that reciprocity – the tendency to return a favor after receiving one – plays an important role in persuading potential backers to support a project. Phrases such as mention your, also receive two, we can afford are all examples of reciprocity in action within projects. Other important categorizations of phrases that were found by the authors include scarcity, social proof, social identity, liking and authority.
The theoretical implications of the paper predominantly affect two bodies of research: emerging studies on crowdfunding platforms & computerized text analysis on drawing inferences from real-world examples (in this case, Kickstarter). However, the authors go on explaining that they do not claim the results to fully explain a guaranteed success of a Kickstarter project. They suggest that there is much more research required into additional attributes such as project categories, no. of project updates and pledge levels. Additionally, I would add the following to the list: percentage funded, type of reward stacking, type of video content & presence of voice over in video content, social media advertising (predominantly on Facebook) and the presence of crowdfunding-specific social media agencies (such as Jeloop or The Crowd Mafia) that have a incredibly strong effect on how much a successful project gets funded over the desired goal.
Gurman, M., & Zaleski, O. (2016, December 7). Fitbit Buys Software Assets From Smartwatch Startup Pebble. Retrieved from Bloomberg: https://www.bloomberg.com/news/articles/2016-12-07/pebble-said-to-discuss-selling-software-assets-to-fitbit
Matas, D. &. (2017, March 05). Redefining Luxury Watches – Filippo Loreti. Retrieved from Kickstarter: https://www.kickstarter.com/projects/2050848594/redefining-italian-luxury-watches-filippo-loreti?ref=nav_search
Mitra, T., & Gilbert, E. (2014, February). The language that gets people to give: Phrases that predict success on kickstarter. In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing (pp. 49-61). ACM.
Unsplash. (2016, March 05). Pexels. Retrieved from Pexels: https://www.pexels.com/photo/please-relax-steal-dance-flirt-smoke-wonder-feel-24897/