SYSTEMS FOR APPLYING QUANTITATIVE MARKETING RESEARCH PRINCIPLES TO QUALITATIVE INTERNET DATA

摘要

An online marketing research system is provided that allows users to monitor the sentiment of their brand via existing data on the internet. Users identify the specific brand and competitive brands in which they are interested. After selecting one of the system's sampling methods, or creating a sampling method unique to their needs, the internet crawler is sent out to select according to the plan a specified number of sentiments. The engine cleans the results of poor quality data such as astro-turfing and re-blogging. The sentiments are then scored using the system's sentiment engine, and further cleaned with the hate and profanity engine. The system's crawling engine also gathers data for competitive brands within the same subcategory, category and industry as well as a variety of unrelated brands. Clients use the system's engine interface to visualize the data in an appealing qualitative format. In addition, they use the system's interactive sentiment modeler to gain more detailed and quantified insights into the data. The interactive sentiment modeler interface allows users to select the types of charts, the constructs, and timelines that are important to them. Users can also select which competitive brands they wish to monitor, as well as which norms they are interested in. When users are satisfied with the charts they have viewed and prepared, they can share, save, and print their results, or set up automated alerts that will inform them when online sentiment has changed.