دانلود رایگان مقاله کشف پیام از آشفته بازار کلان داده

Abstract

User-generated content, such as online product reviews, is a valuable source of consumer insight. Such unstructured big data is generated in real-time, is easily accessed, and contains messages consumers want managers to hear. Analyzing such data has potential to revolutionize market research and competitive analysis, but how can the messages be extracted? How can the vast amount of data be condensed into insights to help steer businesses’ strategy? We describe a nonproprietary technique that can be applied by anyone with statistical training. Latent Dirichlet Allocation (LDA) can analyze huge amounts of text and describe the content as focusing on unseen attributes in a specific weighting. For example, a review of a graphic novel might be analyzed to focus 70% on the storyline and 30% on the graphics. Aggregating the content from numerous consumers allows us to understand what is, collectively, on consumers’ minds, and from this we can infer what consumers care about. We can even highlight which attributes are seen positively or negatively. The value of this technique extends well beyond the CMO’s office as LDA can map the relative strategic positions of competitors where they matter most: in the minds of consumers.

5. Conclusion Firms have easy access to data regarding the performance of their products, what consumers really care about, and the strengths and weaknesses of competitors. Consumers are not shy about sharing their thoughts on any number of topics via public forums. This user-generated content contains incredible potential, but many firms don’t know how to properly tap it. We suggestthat firms consider Latent Dirichlet Allocation, a non-proprietary technique that can be applied by anyone with advanced statisticaltraining. This allows analysts to extract what consumers are thinking about from user-generated content. This technique even allows a manager to understand which attributes consumers see as positives or negatives of his/her product and competitors’ products. Such analysis can inform the firm’s strategy to better serve consumers. With the right tools, the message can be extracted from the mess of big data.