The “X+1+X” policy in the national natural gas industry has positioned the price of natural gas as a crucial factor for the development of the downstream customer market. The sales segment, which is directly exposed to market competition, heavily relies on this pricing strategy. In response to the shortcomings of the ladder gas price settlement contract signed between the natural gas sales company and downstream customers, which does not fully consider the customers' gas purchasing ability in the process of formulation, this paper analyzes the impact of customer volume-price relationship on the ladder price, and establishes a natural gas volume-price coupled nonlinear sales optimization model of the natural gas supply chain. The model takes the maximum total benefit of the natural gas sales company as the objective function, and takes the gas volume of each link in the natural gas supply chain, the natural gas supply and sales volume as well as the customers' ladder prices as the decision variables. The constraints of the model include the upper and lower limits of the gas volume of each link, pricing adjustment space constraints for each customer, the node flow balance constraints, the constraints of customers' volume-price relationship, the constraints of the ladder price, the constraints of the type of different customer, etc. The proposed complex mixed-integer quadratic optimization model is solved using the spatial branch and bound algorithm in the GUROBI solver. This method is applied to a large-scale multi-gas source and multi-customer supply and demand system (including 10 gas sources and 121 customers) within a provincial network. Remarkably, the computation time does not exceed 5 seconds, demonstrating the high efficiency of the model and algorithms. When compared to the current sales situation with a fixed ladder pricing scheme, the optimized sales volume and gas price scheme for each customer resulted in a total benefit increase of 17.2%. This significant improvement underscores the effectiveness of the proposed model. Importantly, the model and algorithm developed in this paper can be applied to a variety of customer types, ensuring that the interests of both customers and natural gas sales companies are considered. The model has shown promising application effects and can be used to recommend price adjustment plans in cases of price reconsideration between natural gas sales companies and downstream customers, and provides a solid foundation for natural gas sales companies to formulate more effective and beneficial ladder gas price sales schemes.