Service online search ads: from a consumer journey view

Ming Cheng, Chris K. Anderson, Zhen Zhu, S. Chan Choi

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Purpose: This study aims to address the following research questions: Do the two types of service firms (individual or aggregator) have similar competitiveness on online search ads? How should the two types of service firms select optimal branded keywords to improve search performance? In addition, how do consumers’ search queries influence the service search performance of the two types of service firms? Design/methodology/approach: In this study, the authors conduct an empirical analysis by building a two-stage choice modeling on the process of search engine ranking and consumer click-through decisions. The authors estimate the parameter coefficients and test the hypotheses using maximum likelihood estimation in the logistic regression model. Findings: The empirical findings suggest that consumer response rates are highly dependent upon three aspects (service types, branded keyword strategy and consumer search query). First, the authors found that service aggregators receive greater consumer responses than individual service providers. Second, depending upon the various branded keyword strategies (e.g. generic vs branded, “within-type” vs “cross-type”) implemented by service aggregators or individual firms, the expected consumer responses could be quite different. Finally, customer’s search query, being either generic or branded, also has direct effect and interactive effect with service type on how consumers would response to the sponsored ads in the service search process. Research limitations/implications: The limitation of the research is twofold. First, conversion rate is not considered in the model estimation due to the nature of the data set. Second, the discussion about the keywords selection strategies is focusing on the hospitality industry. Future research shall further validate the generalizability into other industries. Practical implications: First, given this competitive advantage, service aggregators should take an aggressive approach to adopting paid search strategy in acquiring new users and enhance its brand salience in the service ecosystem. Second, when considering other competitor’s brand names to include, if a firm is a service provider (e.g. hotel), a strategy that can help it receive higher consumer response would be to use “within-type” rather than “cross-type” branded keyword strategy. If a firm is a service aggregator, a better branded keyword strategy would be to use “across-type” instead of “within-type” approach. In addition, given that consumer’s brand awareness can influence the effectiveness of branded keyword strategy, online service search should target consumers in earlier stages of a decision journey. Social implications: The authors believe their theoretical framework can provide actionable solutions to service firms to ease customer’s search process, increase customer’s stickiness using search engines and add value to the customer relationships with all services entities within the digital ecosystem. Originality/value: This study is the first to expand online search marketing into granule examinations (main and interactive effects of three key factors) in the service search domain. First, the authors differentiate service firms into two categories – online travel aggregators and individual hotels in the model. Second, the authors introduce two sets of new classifications of branded keywords for online service search research (i.e. own versus other brand and “cross-type” versus “within-type” branded keywords). Third, this study integrates service consumers’ search word specificity into the conceptual framework which is often missing in previous online search research.

Original languageAmerican English
Pages (from-to)126-141
Number of pages16
JournalJournal of Services Marketing
Issue number2
StatePublished - Mar 13 2018

ASJC Scopus subject areas

  • Marketing


  • Consumer decision journey
  • Consumer search query
  • Keywords branding
  • Logistic regression
  • Search online search
  • Service aggregator


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