Using Artificial Intelligence to Unlock Crowdfunding Success for Small Businesses
This research addresses funding challenges for small businesses, particularly in low socio-economic areas, by providing actionable AI-driven strategies to improve crowdfunding success, though it is incremental in applying existing methods to a specific domain.
The study tackled the problem of high failure rates in small business crowdfunding campaigns by using AI to identify and optimize key factors, achieving an 81.0% prediction accuracy for outcomes and increasing funding likelihood by 11.9% through narrative enhancements.
While small businesses are increasingly turning to online crowdfunding platforms for essential funding, over 40% of these campaigns may fail to raise any money, especially those from low socio-economic areas. We utilize the latest advancements in AI technology to identify crucial factors that influence the success of crowdfunding campaigns and to improve their fundraising outcomes by strategically optimizing these factors. Our best-performing machine learning model accurately predicts the fundraising outcomes of 81.0% of campaigns, primarily based on their textual descriptions. Interpreting the machine learning model allows us to provide actionable suggestions on improving the textual description before launching a campaign. We demonstrate that by augmenting just three aspects of the narrative using a large language model, a campaign becomes more preferable to 83% human evaluators, and its likelihood of securing financial support increases by 11.9%. Our research uncovers the effective strategies for crafting descriptions for small business fundraising campaigns and opens up a new realm in integrating large language models into crowdfunding methodologies.