Optimal reserve prices in weighted GSP auctions

Most search engines use the weighted Generalized Second Price (wGSP) auction to sell keyword-based text ads, generating billions of dollars of advertising revenue every year. Designing and implementing near-optimal reserve prices for these wGSP auctions are naturally important problems for both academia and industry.In this paper, we show how to calculate and implement the near-optimal reserve price of the wGSP mechanism in realistic settings. Unlike reserve prices in standard single-item auctions, optimal reserve prices in wGSP auctions are discriminatory, different even for advertisers bidding on the same keyword. The optimal reserve price results can be extended to support CPA/CPC/CPM¹ hybrid auctions.Our simulations indicate that setting a proper reserve price will transfer some bidder utility (payoff) to auctioneer utility, resulting in higher revenue for the search engine. We describe a practical methodology to implement optimal reserve prices in production systems.     

Advertising channel selection in a segmented market

We consider a market with a finite number of segments and assume that several advertising channels are available, with different diffusion spectra and efficiencies. The problem of the choice of an advertising channel to direct the pre-launch campaign for a new product is analyzed in two steps. First, an optimal control problem is solved explicitly in order to determine the optimal advertising policy for each channel. Then a maximum profit channel is chosen. In a simulation example we consider the choice of a newspaper among six available and analyze the relations among the firm target market and the advertising channels environment which induce the optimal decision.     

基于网页查询结果的广告查询扩展研究

在计算广告学中,为用户查询返回相关的广告一直是研究的热点。然而用户的查询一般比较简短,广告的表示也局限在简短的创意和一些竞价词上,返回符合用户查询意图的广告十分困难。为了解决这个问题,该文提出利用多特征融合的方法进行广告查询扩展,先将查询输入到搜索引擎中,获得Top-k网页查询结果,将它们作为获取扩展词的外部资源,由于采用一般的特征选取方法获取扩展词采用的特征比较单一,缺乏语义信息,容易产生主题漂移现象,该文通过计算扩展词和查询词在网页查询结果中的共现度,并融合传统的TF特征和词性信息,获得与原始查询语义相关的扩展词。在真实的广告语料上的实验结果显示,基于多特征融合的选择广告扩展词的方法能有效地提高返回广告的相关性。     

The impact of context on display ad effectiveness: Automatic attitude activation and applicability

Display and search ads are the most popular Internet ad formats. Instead of being placed on search engine result pages, display ads are placed on webpages that include more actual content. In order to improve online contextual advertising, the effects of webpage content on embedded display ads must be understood. This study investigates how viewers’ attitudes toward content and the applicability of that content to the adjacent display ads impact the effectiveness of those ads. The moderating effects of viewers’ attention and need for cognition are also examined. The experimental results show that webpage content automatically activates ad evaluations, and that this effect increases when viewers pay less attention to the ad or have a high need for cognition. If the webpage content is highly applicable to the ad, improvements are seen in the attitude toward the ad and the attitude toward the brand.     

基于用户迁徙网络的广告投放策略研究

分析了目前网络广告投放领域存在的不足。使用能够体现网站间共同用户数量的用户迁徙网络作为平台,研究广告投放的网站选择策略。通过分析传统的网络广告投放问题的数学模型,发现其本质为0-1背包问题。通过实验比较,解决0-1背包问题常用的贪心算法和蚁群算法不能解决的广告受众重叠的问题;而使用用户迁徙网络的广告投放方法,在预算一定的情况下,达到广告的受众最多,广告投放的效果最优,是广告投放的最佳策略。     

Blogger-Centric Contextual Advertising

Web advertising (online advertising), a form of advertising that uses the World Wide Web to attract customers, has become one of the most commonly-used marketing channels. This paper addresses the concept of Blogger-Centric Contextual Advertising, which refers to the assignment of personal ads to any blog page, chosen in according to bloggers’ interests. As blogs become a platform for expressing personal opinions, they naturally contain various kinds of statements, including facts, comments and statements about personal interests, of both a positive and negative nature. To extend the concept behind the Long Tail theory in contextual advertising, we argue that web bloggers, as the constant visitors of their own blog-sites, could be potential consumers who will respond to ads on their own blogs. Hence, in this paper, we propose using text mining techniques to discover bloggers’ immediate personal interests in order to improve online contextual advertising. The proposed Blogger-Centric Contextual Advertising (BCCA) framework aims to combine contextual advertising matching with text mining in order to select ads that are related to personal interests as revealed in a blog and rank them according to their relevance. We validate our approach experimentally using a set of data that includes both real ads and actual blog pages. The results indicate that our proposed method could effectively identify those ads that are positively-correlated with a blogger’s personal interests.     

Manufacturer defensive and offensive advertising in competing distribution channels

This paper investigates how two competing manufacturers should invest in defensive and offensive advertising in a two‐segment market and whether they should each adopt a decentralized or an integrated channel if their goal is to maximize total channel profits. We find that manufacturers in decentralized channels can exclusively undertake either of the two types of advertising or combine the two at the equilibrium. In integrated channels, they can either combine the two or exclusively undertake defensive advertising. When multiple equilibria exist, strategies that combine both types of advertising should be preferred to exclusive defensive advertising strategies, which are better than exclusive offensive advertising strategies. Also, total channel profits are higher in decentralized channels than in integrated channels when the brands are moderately or highly substitutable. Conversely, total channel profits of integrated channels are higher than those of decentralized channels in areas where the brands are relatively differentiated and the offensive advertising retaliatory capacity of the rival is stronger. Theoretical and managerial implications of these findings are discussed.     

A multiobjective approach for maximizing the reach or GRP of different brands in TV advertising

This paper focuses on a multiobjective optimization problem in TV advertising from an advertising agency's perspective, which involves deciding on which commercial breaks to air the ads of various brands to jointly maximize reach or gross rating point (GRP) for the different brands subject to budget constraints, brand competition constraints, and other scheduling constraints. We present a multiobjective integer programming formulation of this problem and develop and implement algorithms for generating provably Pareto‐optimal solutions. We also develop reduction and visualization procedures to aid a decision maker in choosing suitable subsets of the Pareto‐optimal solutions obtained. Numerical experiments on five TV advertising problems involving 20–40 objective functions and thousands of decision variables and constraints demonstrate the effectiveness of the proposed formulation and solution methods in generating Pareto‐optimal objective vectors that reflect brand priorities and that are well distributed along the Pareto front.     

Search advertising placement strategy: Exploring the efficacy of the conventional wisdom

Search advertising is one of the most important forms of electronic commerce. While click-through rates are considered a key measure of search advertising effectiveness by search providers, brand attention can also be a valuable objective. Our paper reports on an experiment that investigated how search advertisement placement affected search users’ brand recall and recognition. The results showed that semantically associated search ads generated significantly higher levels of brand attention than contextually associated ones. Significant interaction effects were found among search ad position, keyword association, and search result quality. Implications for decision makers are discussed.     

Sentiment-oriented contextual advertising

Web advertising (Online advertising), a form of advertising that uses the World Wide Web to attract customers, has become one of the world’s most important marketing channels. This paper addresses the mechanism of Content-based advertising (Contextual advertising), which refers to the assignment of relevant ads to a generic web page, e.g., a blog post. As blogs become a platform for expressing personal opinion, they naturally contain various kinds of expressions, including both facts and comments of both a positive and negative nature. Besides, in line with the major tenet of Web 2.0 (i.e., user-centric), we believe that the web-site owners would be willing to be in charge of the ads which are positively related to their contents. Hence, in this paper, we propose the utilization of sentiment detection to improve Web-based contextual advertising. The proposed sentiment-oriented contextual advertising (SOCA) framework aims to combine contextual advertising matching with sentiment analysis to select ads that are related to the positive (and neutral) aspects of a blog and rank them according to their relevance. We experimentally validate our approach using a set of data that includes both real ads and actual blog pages. The results indicate that our proposed method can effectively identify those ads that are positively correlated with the given blog pages.     

Impact of query intent and search context on clickthrough behavior in sponsored search

Implicit feedback techniques may be used for query intent detection, taking advantage of user behavior to understand their interests and preferences. In sponsored search, a primary concern is the user’s interest in purchasing or utilizing a commercial service, or what is called online commercial intent. In this paper, we develop a methodology for employing the content of search engine result pages (SERPs), along with the information obtained from query strings, to study characteristics of query intent, with a particular focus on sponsored search. Our work represents a step toward the development and evaluation of an ontology for commercial search, considering queries that reference specific products, brands, and retailers. Characteristics of query categories are studied with respect to aggregated user clickthrough behavior on advertising links. We present a model for clickthrough behavior that considers the influence of such factors as the location of ads and the rank of ads, along with query category. We evaluate our work using a large corpus of clickthrough data obtained from a major commercial search engine. In addition, the impact of query intent is studied on clickthrough rate, where a baseline model and the query intent model are compared for the purpose of calculating an expected ad clickthrough rate. Our findings suggest that query-based features, along with the content of SERPs, are effective in detecting query intent. Factors such as query category, the rank of an ad, and the total number of ads displayed on a result page relate to the context of the ad, rather than its content. We demonstrate that these context-related factors can have a major influence on expected clickthrough rate, suggesting that these factors should be taken into consideration when the performance of an ad is evaluated.     

基于模糊优化的关键词广告预算分配策略

针对单搜索引擎,研究了广告主竞投多个关键词时的广告时序预算分配策略,在总预算限制下建立了以最大化广告收益、最小化无效点击为双目标的单引擎多关键词广告时序预算分配模型,并给出了模糊优化双目标预算分配模型的解法。通过验证,该预算分配模型对广告主在单搜索引擎上竞投多个关键词广告时起着策略性指导作用。     

Web页面信息的视觉搜索行为特征的研究

网页是非常重要的人机界面,网页信息如何有效、合理地布局以引导人们的视觉行为,进而提高视觉搜索效率是网页设计者重点考虑的问题。从认知科学角度研究人们在Web页面上进行设计视觉信息搜索时的视觉行为特性,同时探讨浮动广告对于视觉搜索行为的影响。实验结果显示:无论是否有浮动广告,Web页面周边区域的注视时间和注视次数都显著大于中心区域。实验结果表明,Web页面视觉性搜索信息时,更多地注视周边区域,呈现视觉搜索的周边特性;而浮动广告对于视觉搜索行为没有显著影响。实验结果说明:(1)从视觉搜索角度来看,对于具有超级链接性质的标题信息,放置在周边区域比在中心区域更有利于人们的视觉搜索行为;(2)浮动广告的广告效应不明显。     

试论现代平面广告设计中的色彩应用

平面广告就形式而言,是现代传递信息的重要方式,是广告主与受众间的媒介．从设计的角度来看,它包含着文案、图形、线条、色彩、编排等要素。其中色彩作为平面广告中必不可少的一部分,对增强广告表现力、表达广告内容、吸引目标群体有着至关重要的作用。色彩设计亦成为平面广告设计师的震要研究领域。文章阐述了色彩在平面广告设计中的囊要性,随后分析色彩的心理感受和象征意义两个层面的应用方向,进一步总结平面广告设计中色彩应用基本方法。     

基于淘宝直通车的竞价决策系统的研究与设计

电子商务蓬勃发展的大环境下,广告主具有强烈的电商广告投放意愿,显然他们并未达到电商广告的核心业务SEM （搜索引擎营销优化）的专业要求。所以广告主希望借助第三方工具来进行搜索引擎广告投放的一站式服务来满足其业务需求。基于此,本文将提供一整套的竞价词托管式服务的解决方案。以淘宝直通车这一全新的搜索竞价模式作为研究对象,从语义抽取、关键词扩展、竞价词生成、模型化出价、广告效果正向反馈监控模型几方面进行分析和统计,为直通车广告主提供最优投放策略整体解决方案。第一阶段针对商品信息进行数据挖掘,实现关键词推荐引擎。第二阶段实现投放优化模块,实施定价策略,建立的点击量与PPC（“平均点击花费”）模型,实现在预算资金的约束下对不同竞价组合进行ROI（投入产出比）最大化的投资决策。以实际效果改善直通车竞价搜索用户体验。     

GameSense: game-like in-image advertising

Considering the continuously increasing availability and accessibility of multimedia contents via social networking sites, our research addresses how to monetize the social multimedia contents with an efficient advertising approach. This paper presents a novel game-like advertising system called GameSense, which is driven by the compelling contents of online images. The contextually relevant ads (i.e., product logos) are embedded at appropriate positions within the online games, which are created on the basis of online images. The ads are selected based on multimodal relevance, i.e. text relevance, user relevance and visual content similarity. The game is able to provide viewers rich experience and thus promotes the embedded ads to provide more effective advertising. GameSense represents one of the first attempts toward effective online mashup applications which connect a photo-sharing site with an advertising agency. The effectiveness of GameSense is evaluated over a large-scale real world image set.     

Vertical cooperative advertising in a retailer duopoly

This paper focuses on optimal pricing and advertising decisions within a two-echelon distribution channel, which consists of one manufacturer and two competing retailers. Assuming an inter-echelon Stackelberg equilibrium, where the manufacturer obtains channel leadership, we compare two different forms of retailer behavior: non-cooperative (Horizontal Nash) and cooperative (Cooperation). While the consumer demand depends both on retail price and advertising, the manufacturer can offer a vertical cooperative advertising program to increase the advertising efforts of his retailers. In order to derive a logically consistent price demand function, we deduce our demand function from the consumers’ utility function. Numerical examples lead to the following main findings: (i) consumers can benefit from retailer-competition, as it reduces retail price; (ii) the manufacturer’s participation in retailers’ advertising will be the highest when there is strong competition and no Cooperation; (iii) a Cooperation does not always yield higher profits for the retailers, but can also produce better results for the manufacturer.     

Pricing strategy in a dual-channel and remanufacturing supply chain system

This article addresses the pricing strategy problems in a supply chain system where the manufacturer sells original products and remanufactured products via indirect retailer channels and direct Internet channels. Due to the complexity of that system, agent technologies that provide a new way for analysing complex systems are used for modelling. Meanwhile, in order to reduce the computational load of searching procedure for optimal prices and profits, a learning search algorithm is designed and implemented within the multi-agent supply chain model. The simulation results show that the proposed model can find out optimal prices of original products and remanufactured products in both channels, which lead to optimal profits of the manufacturer and the retailer. It is also found that the optimal profits are increased by introducing direct channel and remanufacturing. Furthermore, the effect of customer preference, direct channel cost and remanufactured unit cost on optimal prices and profits are examined.     

On Kalman filtering over fading wireless channels with controlled transmission powers

We study stochastic stability of centralized Kalman filtering for linear time-varying systems equipped with wireless sensors. Transmission is over fading channels where variable channel gains are counteracted by power control to alleviate the effects of packet drops. We establish sufficient conditions for the expected value of the Kalman filter covariance matrix to be exponentially bounded in norm. The conditions obtained are then used to formulate stabilizing power control policies which minimize the total sensor power budget. In deriving the optimal power control laws, both statistical channel information and full channel information are considered. The effect of system instability on the power budget is also investigated for both these cases.     

Coordinating two-period ordering and advertising policies in a dynamic market with stochastic demand

In this paper, we study the optimal two-stage advertising and ordering policies and the channel coordination issues in a supply chain composed of one manufacturer and one retailer. The manufacturer sells a short-life-cycle product through the retailer facing stochastic demand in dynamic markets characterised by price declines and product obsolescence. Following a two-period newsvendor framework, we develop two members’ optimal ordering and advertising models under both the centralised and decentralised settings, and present the closed-form solutions to the developed models as well. Moreover, we design a two-period revenue-sharing contract, and develop sufficient conditions such that the channel coordination can be achieved and a win–win outcome can be guaranteed. Our analysis suggests that the centralised decision creates an incentive for the retailer to increase the advertising investments in two periods and put the purchase forward, but the decentralised decision mechanism forces the retailer to decrease the advertising investments in two periods and postpone/reduce its purchase in the first period. This phenomenon becomes more evident when demand variability is high.