Abstract:

As technology advances and the economy experiences rapid growth， the internet advertising has witnessed an unprecedented boom. Guaranteed display advertising plays a significant role in internet advertising. A successful display ad must not only offer a wide range of presentation styles but should also aim for widespread exposure. However， guaranteed delivery strategy is influenced by various factors， with the greatest challenge being the uncertainty in the online behavior of internet users. In this context， the study of guaranteed display ad delivery strategy that considers uncertainty holds practical significance. Additionally， strategy is typically determined before the arrival of internet users and advertising placements， and the effectiveness of strategy can be validated through the recourse of performance. Therefore， adopting a two-stage model to address guaranteed display ad delivery issues provides more valuable guidance. In the realm of display advertising， the publisher owns advertising platforms， where advertisers represent products. When users browse the publisher's website， impressions （random variable） are generated， with each impression corresponding to an opportunity for a user to view an ad on the webpage. As users browse web pages， the publisher can categorize them into different segments based on characteristics. Once the publisher identifies the specific target segments of advertisers， ads on ad slots can be automatically loaded and displayed to users with different characteristics. Regarding guaranteed delivery， the publisher signs contracts with advertisers in which advertisers require demands， target segments and specific period. The contract also specifies penalties for shortage and excess of demand. Based on this， a two-stage distributionally robust model is formulated from the perspective of the publisher with the objective of maximizing overall revenue， in which the mean and variance of impression supply as the only known distribution information. The objective function consists of two parts： the fairness of allocation in the first stage and the publisher's expected revenue in the second stage. To better solve the proposed model， a cutting-plane algorithm is designed. Experimental results compared with the benchmark model（Sample Average Approximation - SAA） demonstrates the delivery strategy based on the method proposed in this paper effectively mitigates the interference caused by uncertainty and exhibits robustness. At the same time， some management insights are provided for the publisher.

Key words: targeted display advertising, guaranteed delivery, two-stage, distributionally robust optimization