Empirical Research Of Network Sales Promotion Effects Based On Semi-parametric Model

In this information period, the internet becomes more widespread in recent years, more and more enterprises began to realize the importance of electronic commerce and build their online stores actively to preemptive network market. Sales Promotion as a short-term Promotion are widely used by vast network marketers, thus online stores have sprung up, in order to capture the e-commerce market and win business opportunities. Temporary promotional activities can be effective in the short term to stimulate consumer demand, increase sales, helping companies to maximize their profits. However, its negative effects cannot be ignored, such as frequent promotions may reduce the price sensitivity of consumer, decrease the brand loyalty, inappropriate promotion can also do harm to the brand image, and seriously hindered the development of enterprises. Also the Internet customer are different from the traditional store, if we just apply traditional store sales promotion strategy directly, we cannot achieve the expected promotion effect, but spend a lot of material and financial resources. Thus, this paper aims at studying the network businesses how to choose the appropriate promotion strategy, and how to choose the frequency and magnitude of the promotion activities. Through the quantitative evaluation of network promotion effect, the influence factors and its impact on product sales, network businesses can adjust the promotion strategy according to the feedback of the analysis.In this paper, the semi-parametric model is used for studies; we express sales as the sum of a nonparametric function of discount variables and a linear function of other predictors. The indicator variables represent promotional strategies(include "Free Product","seckill" and "Sweepstakes"), weekly and holiday effects, the online customer reviews. All data set are from Jingdong, contains4brands of mobile phone and4brands of personal computer. We verified the threshold and saturation effects for both own-and cross-item temporary price cuts, and the result also show how sales respond to own and other items price discounts (flexible interaction effects). In a separate analysis, we show how the shape of the deal effect curve depends on own-item promotional strategies. Combined with the actual situation and use the consumer behavior theory to analysis the effects of business promotion, the optimal promotional strategies are made for network marketers to achieve the anticipated promotion goals.