Using online search data to forecast new product sales
نویسندگان
چکیده
Title of Dissertation: USING ONLINE SEARCH DATA TO FORECAST NEW PRODUCT SALES Gauri M. Kulkarni, Doctor of Philosophy, 2010 Dissertation directed by: Professor P.K. Kannan and Professor Wendy W. Moe Department of Marketing This dissertation focuses on online search as a measure of consumer interest. Internet use is at an all-time high in the United States, and according to the Pew Internet & American Life Project, 91% of Internet users use search engines to find information. Consumers’ choices of search terms are not well understood. However, we argue that people will focus their searches on terms that are of interest to them. As such, data on the search terms used can provide valuable measures and indicators of consumer interest in a market. This can be particularly valuable to managers in search of tools to gauge potential product interest in a new product launch. In this research, we develop a model of pre-launch search activity. We find search term usage to follow rather predictable patterns in the pre-launch and post-launch periods. As such, we extend our pre-launch search model to link pre-release search behavior to releaseweek sales – providing a very valuable forecasting tool. We illustrate this approach in the context of motion pictures. Our modeling framework links search activity to sales and incorporates product characteristics. Our results indicate consistent patterns of search over time and systematic relationships between search volume, sales, and product attributes. We extend our model by studying the role of advertising. This allows us to better understand the relationship between advertising and online search activity and also allows us to compare the forecasting performances of each of the two approaches. We find that search data offers significant forecasting power in opening-weekend box-office revenues. We further find that advertising, combined with search data, offers improved forecasting ability. USING ONLINE SEARCH DATA TO FORECAST NEW PRODUCT SALES
منابع مشابه
The Value of Online Product Buzz in Sales Forecasting
Online product buzz refers to an online expression of interest in a product, such as online product reviews, blog posts and search trends. We study how well online buzz predicts actual sales across different phases in the product lifecycle. Using data from smartphone sales of a Dutch online retailer, we demonstrate a 28% overall increase in forecasting accuracy when measures of online product b...
متن کاملSales Forecast in E-commerce using Convolutional Neural Network
Sales forecast is an essential task in E-commerce and has a crucial impact on making informed business decisions. It can help us to manage the workforce, cash flow and resources such as optimizing the supply chain of manufacturers etc. Sales forecast is a challenging problem in that sales is affected by many factors including promotion activities, price changes, and user preferences etc. Tradit...
متن کاملSales Forecast of Dual-Channel Supply Chain based on Improved Bass and SVM Model
As the increasingly fierce competition, more and more manufacturers have started to sell products through online channels apart from traditional retail channel. Meanwhile, increased competition has significantly shortened the product life cycle, which makes sales forecast meaningful. Taking lack of historical record into account, the sales forecast model based on historical sales data based on ...
متن کاملForecast Model for Box-office Revenue of Motion Pictures
The main objective of the paper is to develop an econometric model to forecast box-office revenue of motion pictures. Considering the importance demand for new products, marketing researches have developed various demand forecasting models. However, these models forecast future demands based on either several months of initial sales data after new product introduction or the survey data on cust...
متن کاملAdministering and Capitalizing on Product Sampling in an Online Context
Product sampling, a promotional tactic long employed by brands looking to enter a new market, release a new product, or increase existing sales, has recently been applied in the online context. This seems a viable strategy given the Internet’s capability to reach a wide audience and track consumer responses. Furthermore, firms may acquire product consumption experience information from the cons...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Decision Support Systems
دوره 52 شماره
صفحات -
تاریخ انتشار 2012