This Small Business Innovation Research (SBIR) Phase II project addresses the challenges for entities seeking to derive reliable and actionable information from enormous quantities of online "chatter" (online content from a variety of sources such as blogs, industry-focused sites, and media-generated material). Phase II will focus on technical objectives that will enhance the quality and reliability of the information produced by the ChatterSpike concept researched in Phase I. These objectives fall into three categories: data cleansing, context analysis, and basic commercial readiness. Their achievement will require the design, development and implementation of novel, niche-focused algorithms that will enable the mining and evaluation of thousands of online sources and the production of data with quantifiable quality metrics relating to authority, reliability, influence, and sentiment. The resulting product will algorithmically determine and quantitatively measure and evaluate these parameters in real time as it mines online sources for data, validating its conclusions and re-validating them every time it performs a retrieval operation.
By focusing on specific industry niches, the technology produced will enable the production of automated, highly tailored, detailed reports with a high degree of quantitatively-confirmed reliability. This capability will result from the creation of novel algorithms designed to exploit cutting-edge theoretical approaches to extracting, validating, and evaluating information from a multiplicity of online sources. These reports will be superior to the manual reports produced by currently available technologies and approaches. In addition, if successful, the technology will have significant societal benefit. Companies will be able to react more quickly to meet consumer demands and to correct negative trends in consumer opinions. The technology will also be able to detect trends reliably at a very early stage; in some cases weeks or months before they become obvious and are detected by other methods.
RewardSnapâ€™s Phase II SBIR project focused on the investigation and implementation of consumer enablement with regard to the retail industry. Specifically, RewardSnapâ€™s research included the implementation of retail reward/loyalty card barcode display, as well as input of barcode numbers via camera scanning, on mobile smartphone devices – primarily iPhone. Additionally, opportunities to aggregate and deliver digitized coupons and special offers within a consolidated application were investigated and implemented. This research culminated in commercialization of an iPhone application in August 2010. The application focused on key areas of organizing retailer incentives, reward/loyalty cards, collecting consumer feedback via simple survey capabilities plus voice, image, and text data, as well as customer service assisting consumers in both locating and contacting retailer locations. As the research progressed, RewardSnap iterated its product based on user feedback and analysis of user behavior patterns within the application. User focus shifted toward special offers and deals, and RewardSnap responded with additional innovation toward the ability to for users to input and rate deals provided by retailers as well as those discovered by fellow users. This crowd-sourcing concept allows the community to organize the deals within RewardSnap based on their popularity and "how good the deal is". Ultimately, the implementation of location based criteria, allowing for presentation of highly relevant deals made the application even more valuable. The Phase II research and commercialization was conducted successfully, showing the ability to capture and manage consumer-focused retail information and incentives, specifically reward/loyalty barcodes and other related information to allow consumers to more effectively manage their savings opportunities. Beyond the Phase II project, RewardSnap continues to iterate the product based on user feedback.