The proliferation of platform economics has led to the steady emergence of online shopping as a prominent means of consumer commerce. The impact of user-generated online comments on consumers′ decision-making and purchasing behavior is significant, as seen by the extensive reach and influence of social networks. In the realm of e-commerce, online retailers possess the ability to adaptively modify product prices based on users′ online feedback in order to maximize their income potential. The pricing of a product is a significant determinant of consumer behavior. The fluctuation of product prices has a significant impact on consumer purchasing behavior during the process of consumer consuming. In the context of multi-stage sales of new items, during the typical sales cycle, consumers acquire a certain level of product knowledge through online reviews. Subsequently, these reviews serve as reference points that influence consumers′ purchasing decisions. Towards the conclusion of the sales period, retailers engage in discounting practices as a result of multiple factors. Currently, buyers are able to access information regarding the original pricing and discounted price of a product, with these figures being influenced by factors such as the product′s price and online reviews. During the clearance phase, there is a greater likelihood of generating higher buy intention. In the realm of multi-stage sales for novel products, the influence of price discounts and online reviews on customer purchase behavior and product pricing is of significant importance. This paper employs a polynomial Logit model to develop a multi-stage dynamic pricing model that takes into account the influence of product prices and online reviews on consumer decision-making. It examines the impact of customer choice behavior on the dynamic pricing of online products, sales, and profits, specifically considering the multi-factor anchoring effect. The findings of this study offer theoretical guidance and a decision-making foundation for online retailers in their implementation of dynamic pricing strategies.Based on utility theory, the first section of this study determines the utility of consumers during regular sales periods and clearance periods. Then, in accordance with the MNL model, the ideal pricing, the highest possible sales volume, and the ideal profit are attained during various sales periods.The second section theoretically analyzes the model′s key parameters in order to produce the related managerial illumination. First off, the higher the anchoring degree, the higher the appropriate pricing is when the product praise rate exceeds the anchor point. By aggressively encouraging customers to offer high quality evaluations and expanding the display of high quality evaluations during the sales process, it can particularly increase the degree to which consumers are anchored. Second, the higher the degree of anchoring, the higher the appropriate cost is when the quantity of online reviews exceeds the anchor point. The total number of online comments represents the sales volume and popularity of the product from a side perspective in some e-commerce platforms where the sales page does not display the sales volume of the product or where the sales figure is updated once a month. Last but not least, this study examines the impact of discount intensity on product profit. The analysis demonstrates that whether it be perishable items or luxury goods, the analysis demonstrates that the greater the discount intensity, the smaller the product profit.The third section includes a numerical analysis of the model′s key parameters. First, the best pricing, sales volume, and profit are determined for various price reductions. The findings demonstrate that a small price discount technique can increase profitability while also promoting sales. Second, it examines how various favorable ratings from the first stage affected the product′s pricing, sales volume, and profit in the subsequent stages. The findings demonstrate that reviews written after the first round of sales can accurately reflect a product′s quality, and that the more positive reviews written during the first round of sales, the more profitable the entire sales cycle will be. The resilience of the optimal profit is then examined.The fourth section emphasizes the importance of management enlightenment in the retail industry. Retailers are advised to prioritize product quality, as it serves as a means to garner favorable feedback, enhance consumer trust, and establish a strong brand presence. Additionally, it is imperative for shops to engage in extensive publicity efforts during the clearance period in order to emphasize the cost benefits associated with this period and entice consumers to make purchases. Prior to the introduction of new products, it is imperative to conduct thorough market research in order to ascertain the market positioning of the said products, hence maximizing the potential for gaining a competitive edge. In conclusion, it is imperative for retailers to adopt a long-term development perspective, promptly adapt their marketing methods, enhance product quality, and refrain from prioritizing short-term gains at the expense of deceiving consumers.The conclusion section concludes by summarizing and analyzing the key model analysis and numerical simulation findings. To increase the market competitiveness of platform enterprises, online retailers should prioritize and utilize the data resources of platform users, analyze the behavioral traits of users′ decision-anchoring factors, anchoring points, and degrees, and dynamically adjust the prices of online products.