Search engine marketing (SEM) has become an important strategic tool for online destination marketing. Because of the dynamic relationships among travelers as information searchers, search engines, ...and the online tourism domain, the authors argue that a new dynamic model must be developed that captures these relationships to better inform SEM practices. The goals of this paper are twofold: (1) to synthesize research related to SEM in tourism and related fields and (2) to present a model that describes the evolving dynamics in search engine marketing. The implications of the model for tourism marketing and research are discussed.
Sponsored search is an online advertising channel that has gained momentum worldwide. The key challenge is deciding on the types of keywords to bid on and matching options to utilise for the ...keywords. In this paper, we address this problem by providing a broad analysis on how the various traffic search metrics (length, CTR, average cost per click (CPC), average position, and quality score) influence the bidding results as the keyword matching option becomes broader, that is, from exact, to phrase to broad. Drawing on the shopping goals theory, we also establish the profile of the metrics associated with a more focused search intent across the matching options. Using a random sample of keywords selected from 9 640 keywords that online advertisers have bid on, spanning a variety of markets, the results indicate that as the matching option becomes narrower, that is, from broad to exact, the keyword traffic metrics increase in general, except for cost, which does not differ significantly across the matching options. Longer keywords, which are typically associated with a more focussed search intent, generate more clicks and have a higher quality measure on average across all matching options. The longer keywords are cheaper for the exact match option, but more expensive for the other matching options. The results are inconclusive with regard to the position that longer keywords occupy on a results page across the matching options. Thus, the narrower matching options and longer keywords matching those that a customer would typically use to search for a company's goods and services need to be targeted to ensure higher visits to a company's website.
Objective
Local authority-led online campaigns offer the possibility of targeted health promotion to connect local services and residents. This study assesses the evidence for medium (e.g., ...click-trhoughs) and high (off-line behaviour change) levels of public engagement with four local authority-led campaigns across a variety of public health promotions (sexual health, weight loss, and vaccination), online marketing approaches (social media marketing, search engine marketing, and programmatic marketing) and target demographics (language, gender, age, income, ethnicity) undertaken by a London borough local authority.
Methods
Employing quasi-experimental and observational study designs, engagement with local health services during the course of the campaigns was evaluated. The first three campaigns were evaluated based on an interrupted time series model of intervention assessment comparing outcome variables of interest during the campaign to periods before and after the campaign period. The results of the fourth campaign, an observational case-study, are discussed using descriptive statistics only.
Results
The analyses of the high engagement data for two of the three campaigns statistically assessed clearly supported the effectiveness of the campaigns. While the effect of high engagement could not be determined in the other two campaigns, they provide data that may be useful in online campaign design.
Conclusions
The evidence assessed in this study across a variety of platforms, health promotion initiatives, and population targets suggests that local authority-led online marketing campaigns for health promotion may be useful for increasing participation in public health programmes.
Despite its importance for both e-commerce and traditional offline vendors, managing paid search campaigns is often based on trial and error. In particular, neither research nor practice has ...extensively addressed identifying relevant keywords and setting appropriate matching options. The authors develop a model based on a keyword's intrinsic and extrinsic information content to shed light on how keyword characteristics affect campaign performance. Intrinsic information includes linguistic aspects and user- and content-related features, which can be indirectly changed through extrinsic information such as matching options. Using an advertiser-level data set from multiple industries, this study evaluates the impact of these criteria on click-through and conversion rates. The authors find that the query variation index, which measures whether a keyword contains sufficient information to identify a user's information need correctly, is an effective predictor of keyword performance. Moreover, they show that the relationship between two of the main predictors, namely, query variation and advertiser names, and a keyword's performance is moderated by the advertiser's choice of matching options.
•We develop a theoretical model for managing paid search campaigns.•The model covers linguistic, user-, and content-related aspects.•We propose the query variation index (QVI) as a new indicator.•QVI indicates whether a keyword allows identification of a user's information need.•QVI turns out to be a very good predictor for keyword performance.
With the increased digital usage, web visibility has become critically essential for organizations when catering to a larger audience. This visibility on the web is directly related to web searches ...on search engines which is often governed by search engine optimization techniques liked link building and link farming amongst others. The current study identifies metrics for segregating websites for the purpose of link building for search engine optimization as it is important to invest resources in the right website sources. These metrics are further used for detecting websites outliers for effective optimization and subsequent search engine marketing. Two case studies of knowledge management portals from different domains are used having 1682 and 1070 websites respectively for validation of the proposed approach. The study evolutionary intelligence by proposing a k-means chaotic firefly algorithm coupled with k-nearest neighbor outlier detection for solving the problem. Factors like Page Rank, Page Authority, Domain Authority, Alexa Rank, Social Shares, Google Index and Domain Age emerge significant in the process. Further, the proposed chaotic firefly variants are compared to K-Means integrated firefly algorithm, bat algorithm and cuckoo search algorithm for accuracy and convergence showing comparable accuracy. Findings indicate that the convergence speeds are higher for proposed chaotic firefly approach for tuning absorption and attractiveness coefficients resulting in faster search for optimal cluster centroids. The proposed approach contributes both theoretically and methodologically in the domain of vendor selection for identifying genuine websites for avoiding investment on untrustworthy websites.
We study optimal bidding strategies for advertisers in sponsored search auctions. In general, these auctions are run as variants of second-price auctions but have been shown to be incentive ...incompatible. Thus, advertisers have to be strategic about bidding. Uncertainty in the decision-making environment, budget constraints, and the presence of a large portfolio of keywords makes the bid optimization problem nontrivial. We present an analytical model to compute the optimal bids for keywords in an advertiser's portfolio. To validate our approach, we estimate the parameters of the model using data from an advertiser's sponsored search campaign and use the bids proposed by the model in a field experiment. The results of the field implementation show that the proposed bidding technique is very effective in practice. We extend our model to account for interactions between keywords, in the form of positive spillovers from generic keywords into branded keywords. The spillovers are estimated using a dynamic linear model framework and are used to jointly optimize the bids of the keywords using an approximate dynamic programming approach. Accounting for the interaction between keywords leads to an additional improvement in the campaign performance.
Ultrahigh dimensional data with both categorical responses and categorical covariates are frequently encountered in the analysis of big data, for which feature screening has become an indispensable ...statistical tool. We propose a Pearson chi-square based feature screening procedure for categorical response with ultrahigh dimensional categorical covariates. The proposed procedure can be directly applied for detection of important interaction effects. We further show that the proposed procedure possesses screening consistency property in the terminology of Fan and Lv (2008). We investigate the finite sample performance of the proposed procedure by Monte Carlo simulation studies and illustrate the proposed method by two empirical datasets.
Digital Marketing in the Business Environment Ištvanić, Marin; Crnjac Milić, Dominika; Krpić, Zdravko
International journal of electrical and computer engineering systems,
12/2017, Letnik:
8, Številka:
2
Journal Article, Web Resource
Recenzirano
Odprti dostop
Promotion of products has become an increasingly important component in the new digital age, mostly thanks to digital marketing. The traditional form of marketing is lagging behind digital marketing, ...which offers users new opportunities like personalized messages or answers to a search query. There are several ways to advertise on the internet, and in this paper, ways and tools will be presented that allow digital advertising as well as their advantages and disadvantages. Specifically, search engine optimization, search engine marketing, display advertising, social networking marketing and e-mail marketing will be discussed. Also, the goal of the paper is to enable more efficient creation and implementation of similar contents in new business environments through an insight into internet advertising, social and business networks
Intra-site search engines (ISEs) dedicated to private electronic markets have become popular with the fast-growing electronic markets. Among several research facets regarding the advertising services ...of ISEs, we focus on how to optimise the ISE-based advertising market mechanism by improving the pricing model. The widely adopted pricing scheme, Flat Fee (FF), fails to differentiate ISE advertising services among subscribers. Such inefficiency results in the loss of the subscribers and the decline of the provider's revenue. We design an advanced pricing scheme, three-part tariff pricing with performance relevant adjustments (3PT+), implemented by a two-period contract, to match the differentiated ISE service consumption among subscribers. The mathematical analyses of the advertiser's VaR model and ISE provider's revenue optimisation model show that the 3PT+ pricing scheme is superior to the FF pricing scheme as the former can attract more advertisers and retain most of them in the ISE services. The experimental results from the Monte Carlo simulation further support the theoretic derivation.
This paper explores the relationship of search engine marketing, financing ability and e-commerce firm performance by the empirical research on China's B2C e-commerce firms. Results show that search ...engine marketing and business model has a strong positive relation with firm performance while financing ability has a negative effect on firm performance. It verifies the low returns to inputs in e-commerce and enlightens the managers should concentrate on business model innovation and consumer relation management.
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