Dealing with Interdependencies and Uncertainty in Multi-Channel Advertising Campaigns Optimization

Nuara²,

Romano³

et al. 2022

Preprint

Self Cite

In online marketing, the advertisers' goal is usually a tradeoff between achieving high volumes and high profitability. The companies' business units customarily address this tradeoff by maximizing the volumes while guaranteeing a lower bound to the Return On Investment (ROI). Technically speaking, such a task can be naturally modeled as a combinatorial optimization problem subject to ROI and budget constraints to be solved online since the parameter values are uncertain and need to be estimated during the sequential arrival of data. In this picture, the uncertainty over the constraints' parameters plays a crucial role. Indeed, these constraints can be arbitrarily violated during the learning process due to an uncontrolled algorithms' exploration, and such violations represent one of the major obstacles to the adoption of automatic techniques in real-world applications as often considered unacceptable risks by the advertisers. Thus, to make humans trust online learning tools, controlling the algorithms' exploration so as to mitigate the risk and provide safety guarantees during the entire learning process is of paramount importance. In this paper, we study the nature of both the optimization and learning problems. In particular, when focusing on the optimization problem without uncertainty, we show that it is inapproximable within any factor unless P = NP, and we provide a pseudo-polynomial-time

Section: Related Workmentioning

confidence: 99%

Safe Online Bid Optimization with Return-On-Investment and Budget Constraints subject to Uncertainty

Nuara²,

Romano³

et al. 2022

Preprint

Self Cite

“…Most of the economic reports forecast that artificial intelligence (AI) will unlock up to 12 trillion USD per year worldwide by the next decade, and almost half of this amount will derive from the marketing&sales area (see, e.g., (Chui et al 2018)). In particular, AI is playing a crucial role to tackle various problems, including, e.g., auction design (Bachrach et al 2014), the automation of advertisers' budget (Nuara et al 2018) and bidding strategies (He et al 2013), and the optimization of conversion funnels (Nuara et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Efficiency of Ad Auctions with Price Displaying

Ferraioli²,

Gatti³

et al. 2022

Preprint

Self Cite

Most of the economic reports forecast that almost half of the worldwide market value unlocked by AI over the next decade (up to 6 trillion USD per year) will be in marketing&sales. In particular, AI will enable the optimization of more and more intricate economic settings, in which multiple different activities need to be jointly automated. This is the case of, e.g., Google Hotel Ads and Tripadvisor, where auctions are used to display ads of similar products or services together with their prices. As in classical ad auctions, the ads are ranked depending on the advertisers' bids, whereas, differently from classical settings, ads are displayed together with their prices, so as to provide a direct comparison among them. This dramatically affects users' behavior, as well as the properties of ad auctions. We show that, in such settings, social welfare maximization can be achieved by means of a direct-revelation mechanism that jointly optimizes, in polynomial time, the ads allocation and the advertisers' prices to be displayed with them. However, in practice it is unlikely that advertisers allow the mechanism to choose prices on their behalf. Indeed, in commonly-adopted mechanisms, ads allocation and price optimization are decoupled, so that the advertisers optimize prices and bids, while the mechanism does so for the allocation, once prices and bids are given. We investigate how this decoupling affects the efficiency of mechanisms. In particular, we study the Price of Anarchy (PoA) and the Price of Stability (PoS) of indirect-revelation mechanisms with both VCG and GSP payments, showing that the PoS for the revenue may be unbounded even with two slots, and the PoA for the social welfare may be as large as the number of slots. Nevertheless, we show that, under some assumptions, simple modifications to the indirect-revelation mechanism with VCG payments achieve a PoS of 1 for the revenue.

Section: Introductionmentioning

confidence: 99%

Efficiency of Ad Auctions with Price Displaying

Ferraioli²,

Gatti³

et al. 2022

AAAI

Self Cite

Most economic reports suggest that almost half of the market value unlocked by artificial intelligence (AI) by the next decade (about 9 trillion USD per year) will be in marketing&sales. In particular, AI will allow the optimization of more and more intricate economic settings in which multiple different activities can be automated jointly. A relatively recent example is that one of ad auctions in which similar products or services are displayed together with their price, thus merging advertising and pricing in a unique website. This is the case, e.g., of Google Hotel Ads and TripAdvisor. More precisely, as in a classical ad auction, the ranking of the ads depends on the advertisers' bids, while, differently from classical ad auctions, the price is displayed together with the ad, so as to provide a direct comparison among the prices and thus dramatically affect the behavior of the users. This paper investigates how displaying prices and ads together conditions the properties of the main economic mechanisms such as VCG and GSP. Initially, we focus on the direct-revelation mechanism, showing that prices are chosen by the mechanisms once given the advertisers' reports. We also provide an efficient algorithm to compute the optimal allocation given the private information reported by the advertisers. Then, with both VCG and GSP payments, we show the inefficiency in terms of Price of Anarchy (PoA) and Stability (PoS) over the social welfare and mechanism's revenue when the advertisers choose the prices. The main results show that, with both VCG and GSP, PoS over the revenue may be unbounded even with two slots, while PoA over the social welfare may be as large as the number of slots. Finally, we show that, under some assumptions, simple modifications to VCG and GSP allow us to obtain a better PoS over the revenue.