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.     

Responses to an advergaming campaign on a mobile social networking site: An initial research report

Advergames are a form of branded entertainment that feature advertising messages, logos, and trade characters in a game format. This paper reports a preliminary examination on the effects of an advergame on perceived brand value in a context of mobile social networking sites (SNSs). Drawn upon categorization theory, the study posits that, while mobile SNS engagement stimulates electronic word-of-mouth (eWOM) intention among game players, perceived brand-game fit also drives eWOM intention, which in turn positively affects perceived brand value. Furthermore, perceived brand-game fit is contemplated to be a direct driver of perceived brand value. A research model is validated by a large-scale online survey. Using a real promotional campaign for a popular consumer good (Procter & Gamble’s Pringles), the authors create an advergame for one of the most popular mobile SNSs in Japan. The results from structural equation modeling corroborate all hypothesized relationships. This article closes with some theoretical and managerial implications, as well as recognition of important limitations.     

Modeling the clickstream across multiple online advertising channels using a binary logit with Bayesian mixture of normals

The evaluation of online marketing activities using standalone metrics does not explain the development of consumer behavior over time, although it is of primary importance to allocate and optimize financial resources among multiple advertising channels. We develop a binary logit model with a Bayesian mixture approach to demonstrate consumer clickstreams across multiple online advertising channels. Therefore, a detailed user-level dataset from a large financial service provider is analyzed. We find both differences in the effects of repeated advertisement exposure across multiple types of display advertising as well as positive effects of interaction between display and paid search advertising influencing consumer click probabilities. We identify two consumer types with different levels of susceptibility to online advertising (resistant vs. susceptible consumers) and show that the knowledge of consumers individual click probabilities can support companies in managing display advertising campaigns.     

An app a day keeps a customer connected: Explicating loyalty to brands and branded applications through the lens of affordance and service-dominant logic

The rise of mobile apps is compelling ambitious companies to rush to market their own branded apps in hopes of building customers’ brand loyalty. By applying service-dominant logic, the lens of affordance, and two brand perceptions (brand competence and brand warmth), this study explores critical determinants of app continuance intention and brand loyalty among app users. Five affordances of branded apps are linked to value-in-use, which contributes both directly and indirectly to the two loyalty-related outcomes, through either brand competence or brand warmth. Data collected from 634 app users support all proposed hypotheses. Theoretical and practical implications are discussed.     

A cross-industry analysis of the spillover effect in paid search advertising

For the management of paid search advertising campaigns, metrics collected at keyword-level are often used in practice whereas the users’ search process is of secondary importance and thus wholly or partially neglected. In contrast to brand-related keywords (“T-mobile contract”), general keywords, often referred to as generic (“mobile phone contract”), seem at first glance to be economically unattractive. Extending the approach of Rutz and Bucklin, Journal of Marketing Research, 48(1):87–102 (2011), we investigate the role of generic search activities in paid search advertising across industries using dynamic linear models (DLM). The so-called spillover effect, i. e. the increase in brand-related awareness effected by displaying ads for generic keywords, is investigated by both analyzing individual consumer behavior on the basis of keyword-level data and linking findings on keyword- with findings on individual user-level data. We show that the spillover effect varies across industries and that its consideration, for example for the mobile phone provider investigated here, decreases KPIs such as the cost per order up to 42 %.     

产品包装与品牌推广分析

品牌如同人一样,拥有性格特征。有关品牌特征方面的研究已经证明了其对消费者自我表达,消费者行为和品牌忠诚度所具有的影响力。产品怎样从包装上抓住用户的心理及想要表达的情感特征并成功推广品牌成为现今无论是设计师还是设计企业都不可忽视的问题。     

Consumer attitudes toward blogger’s sponsored recommendations and purchase intention: The effect of sponsorship type,product type,and brand awareness

Sponsored recommendation blog posts, a form of online consumer review, are blog articles written by bloggers who receive benefits from sponsoring marketers to review and promote products on their personal blog. Because national regulations require that marketer sponsorship must be revealed in the blog post, sponsored recommendation posts can no longer conceal their marketing intent. Consumer’s attitudes toward sponsored recommendation posts are thus a vital issue in assessing the effectiveness of the advertisement. This study uses a 2(sponsorship type) × 2(product type) × 2(brand awareness) experimental design and a total of 613 valid samples to examine consumer attitudes toward sponsored recommendation posts and purchase intention. The results show that when products recommended in blog posts are search goods or have high brand awareness, consumers have highly positive attitudes toward sponsored recommendation posts, which improves purchase intention. The directly-monetary/indirect-monetary benefits received by the bloggers have no significant effect on readership attitudes. Using these features in blog writings appears to improve online readers’ trust toward and the credibility of sponsored recommendation posts and thus can be a vital online marketing tool for marketers.     

Predicting user response to sponsored advertising on social media via the technology acceptance model

Sponsored advertising has generated strong advertising revenues for Facebook in recent years. As sponsored ads are built on an interactive platform that could be seen as invasive to user privacy, the growth of this advertising platform has important implications for consumers, and advertisers alike. As little research is available on consumer response to sponsored advertising as an interactive technology innovation, the current study assesses the effects of user perceptions of privacy risk, intrusiveness concerns and utilities of sponsored advertising on consumer attitudes and purchase intent. Testing a model derived form the technology acceptance model (TAM), the study found that privacy and intrusiveness concerns are both valid antecedent variables to perceived usefulness but not perceived ease of use of sponsored advertising. While both antecedent variables also influence consumer attitudes toward sponsored advertising, only privacy concerns have an impact product purchase intentions. The hypothesized relations between perceived usefulness, ease of use, attitudes and purchase intentions were also validated.     

Power of consumers using social media: Examining the influences of brand-related user-generated content on Facebook

This study examined the influences of positive brand-related user-generated content (UGC)¹ shared via Facebook on consumer response. The model tested was derived from the S–O–R consumer response model (Mehrabian & Russell, 1974) that depicts the effects of environmental/informational stimuli on consumer response. Specific research objectives were to investigate whether brand-related UGC acts as a stimulus to activate consumer behavior in relation to brand and examine the processes by which brand-related UGC influences consumer behavior. Using the S–O–R model, brand-related UGC was treated as stimulus, pleasure and arousal as emotional responses, and perceived information quality as cognitive response. Information pass-along, impulse buying, future-purchase intention, and brand engagement were treated as behavioral responses. Participants (n = 533) resided in the U.S. and had a Facebook account. Mock Facebook fan pages including brand-related UGC were developed as visual stimuli and presented via an online self-administered questionnaire. SEM was used to analyze the data. Brand-related UGC activated consumers' emotional and cognitive responses. Emotional and cognitive responses significantly influenced behavioral responses. Positive brand-related UGC exerts a significant influence on brand as it provokes consumers’ eWOM behavior, brand engagement, and potential brand sales.     

基于用户日志挖掘的搜索引擎广告效果分析

随着搜索引擎市场的飞速发展,竞价排名广告以其有效、低风险、灵活等特点逐渐受到中小企业用户的青睐,成为搜索引擎稳定的收益增长点。然而竞价排名广告是否会影响用户体验,从而削弱其宣传效果并且影响用户对于搜索引擎的忠实度成为了企业及搜索引擎所担忧的问题。该文从网络用户日志中挖掘出网络用户对于广告的实际交互行为,并给出了各大搜索引擎竞价排名广告方面的统计数据。对于企业用户如何更有效地利用竞价排名广告以及搜索引擎如何平衡广告的经济效益和用户体验之间的关系都有较高的指导意义。     

Efficient and effective similarity search over probabilistic data based on Earth Mover’s Distance

Advances in geographical tracking, multimedia processing, information extraction, and sensor networks have created a deluge of probabilistic data. While similarity search is an important tool to support the manipulation of probabilistic data, it raises new challenges to traditional relational databases. The problem stems from the limited effectiveness of the distance metrics employed by existing database systems. On the other hand, several more complicated distance operators have proven their values for better distinguishing ability in specific probabilistic domains. In this paper, we discuss the similarity search problem with respect to Earth Mover’s Distance (EMD). EMD is the most successful distance metric for probability distribution comparison but is an expensive operator as it has cubic time complexity. We present a new database indexing approach to answer EMD-based similarity queries, including range queries and k-nearest neighbor queries on probabilistic data. Our solution utilizes primal-dual theory from linear programming and employs a group of B ⁺ trees for effective candidate pruning. We also apply our filtering technique to the processing of continuous similarity queries, especially with applications to frame copy detection in real-time videos. Extensive experiments show that our proposals dramatically improve the usefulness and scalability of probabilistic data management.     

How to select search keywords for online advertising depending on consumer involvement: An empirical investigation

In paid search advertising on Internet, advertisers bid for specific keywords. Consumer involvement affects a consumer’s purchase intention. However, there has been no research on selecting keywords in paid search advertising depending on consumer involvement from the advertisers’ perspective. Our paper investigates the effects of several factors including impressions, click-through rate, conversion rate, the number of competitors and the quantity of online customer reviews on the performance of individual keywords. Our analysis shows that regardless of consumer involvement, the conversion rate and the number of reviews significantly affect to the performance of individual keywords but the click-through rate does not. In addition, the effects of impressions and the number of competitors partially exist depending on consumer involvement. This study provides managerial insights into paid search advertising and can give some assumptions in the theoretical modeling literature for allocating advertising budgets.     

Voronoi-based range and continuous range query processing in mobile databases

With the wide availability of mobile devices (smart phones, iPhones, etc.), mobile location-based queries are increasingly in demand. One of the most frequent queries is range search which returns objects of interest within a pre-defined area. Most of the existing methods are based on the road network expansion method – expanding all nodes (intersections and objects) and computing the distance of each node to the query point. Since road networks are extremely complex, node expansion approaches are inefficient. In this paper, we propose a method, Voronoi Range Search (VRS) based on the Voronoi diagram, to process range search queries efficiently and accurately by partitioning the road networks to some special polygons. Then we further propose Voronoi Continuous Range (VCR) to satisfy the requirement for continuous range search queries (moving queries) based on VRS. Our empirical experiments show that VRS and VCR surpass all their rivals for both static and moving queries.     

国际变色龙品牌的商业广告表现研究——以日化行业为例

广告作为一种传播符号,对于品牌塑造是至关重要的,但同时也有文化与地域的差别。在日化行业,一些外国日用个人护理产品品牌呈现出了强大的变色龙效应,使所有消费群体都受到了影响。针对这一现象,本文主要从广告人物形象、广告情感因素、广告表现元素三个方面对这些国际变色龙品牌的商业广告表现进行了分析研究,以从中找出国际品牌实现其本土化变色龙效应的一些可借鉴经验。     

Distributed text search using suffix arrays

Text search is a classical problem in Computer Science, with many data-intensive applications. For this problem, suffix arrays are among the most widely known and used data structures, enabling fast searches for phrases, terms, substrings and regular expressions in large texts. Potential application domains for these operations include large-scale search services, such as Web search engines, where it is necessary to efficiently process intensive-traffic streams of on-line queries. This paper proposes strategies to enable such services by means of suffix arrays. We introduce techniques for deploying suffix arrays on clusters of distributed-memory processors and then study the processing of multiple queries on the distributed data structure. Even though the cost of individual search operations in sequential (non-distributed) suffix arrays is low in practice, the problem of processing multiple queries on distributed-memory systems, so that hardware resources are used efficiently, is relevant to services aimed at achieving high query throughput at low operational costs. Our theoretical and experimental performance studies show that our proposals are suitable solutions for building efficient and scalable on-line search services based on suffix arrays.     

A Comparison of Lucene Search Queries Evolved as Text Classifiers

ABSTRACT

In this article, we use a genetic algorithm to evolve seven different types of Lucene search query with the objective of generating accurate and readable text classifiers. We compare the effectiveness of each of the different types of query using three commonly used text datasets. We vary the number of words available for classification and compare results for 4, 8, and 16 words per category. The generated queries can also be viewed as labels for the categories and there is a benefit to a human analyst in being able to read and tune the classifier. The evolved queries also provide an explanation of the classification process. We consider the consistency of the classifiers and compare their performance on categories of different complexities. Finally, various approaches to the analysis of the results are briefly explored.     

Personalized query suggestion diversification in information retrieval

Query suggestions help users refine their queries after they input an initial query.Previous work on query suggestion has mainly concentrated on approaches that are similarity-based or context-based,developing models that either focus on adapting to a specific user(personalization)or on diversifying query aspects in order to maximize the probability of the user being satisfied(diversification).We consider the task of generating query suggestions that are both personalized and diversified.We propose a personalized query suggestion diversification(PQSD)model,where a user's long-term search behavior is injected into a basic greedy query suggestion diversification model that considers a user's search context in their current session.Query aspects are identified through clicked documents based on the open directory project(ODP)with a latent dirichlet allocation(LDA)topic model.We quantify the improvement of our proposed PQSD model against a state-of-the-art baseline using the public america online(AOL)query log and show that it beats the baseline in terms of metrics used in query suggestion ranking and diversification.The experimental results show that PQSD achieves its best performance when only queries with clicked documents are taken as search context rather than all queries,especially when more query suggestions are returned in the list.