Converting Web Site Visitors into Buyers

Nathan EarlPromotion Management

11/09/2009

Risk

“Using the internet involves a leap of faith. We type our credit cards numbers and other personal information in order to make a purchase over the Internet and trust that this information will not be used in unauthorized fraudulent ways” (Bargh and McKenna 2004)

RISK

Often times the Risk is high enough to keep online buyers from making online purchases

This avoidance has led experts to speculate that the immediate threat to e-commerce is consumers’ perception of RISK

Firms Respond to Threat

• Investing in Web site security

• Technology to protect consumers’ identity and personal & financial information

– By 2005, Web site security was a multibillion dollar industry

Consumers Want More

In spite of high investment in Web site security, Marketers still face challenge of convincing consumers of their firm’s trustworthiness

TRUST

• Establishing TRUST in a computer-mediated environment has proven to be very difficult

• A major challenge is discovering what the consumers’ perception / measure of TRUST actually is

Ways to Establish Trust

• Privacy Statements

• Security Statements

• High-Investment Web sites

Research

A recent large-scale study show indicate that despite consumers’ claims that privacy and security policies/statements are important for establishing credibility, consumers refer, instead, to a Web site’s “surface elements”, such as DESIGN

Article

Converting Web Site Visitors into Buyers: How Web Site Investment Increases Consumer Trusting Beliefs and Online Purchase IntentionsAnn E. Schlosser, Tiffany Barnett White and Susan M. Lloyd (2006). Journal of Marketing. Vol 70. p. 133-148

Investigating the impact on Web site design investments on consumers’ trusting beliefs and online purchase intentions

Conceptual Framework

• Authors developed a conceptual framework for understanding how “marketing signals” influence consumers’ trust in e-commerce settings– Marketing signals: Observable actions that

help explain the unobservable• Example—price reduction, advertising expenditures• Example—investing in high-end Web sites to help

convey the firm’s trustworthiness (unobservable)

Signals

Different “signals” can influence different PERCEPTIONS of the firms trustworthiness

This PERCEPTIONS has a direct correlation to the consumer making the actual purchase

Effects of Perceptions

The effects vary according to the purpose of the consumer visiting the firm’s site

• Searching• Browsing

Trust

• “Willingness to rely on an exchange partner in whom one has confidence”

• “Generalized expectancy held by an individual that the word, promise, oral or” written statement of another individual or group can be relied upon”

• “A belief in a person’s competence to perform a specific task under specific circumstances”

Trusting Beliefs

Cognitive Aspects

• Ability

• Benevolence

• Integrity

Represent a “sentiment or expectation about trustworthiness”

Ability

• Ability beliefs reflect the consumer’s confidence that the firm has the skills necessary to perform the job

Benevolence

• Benevolence beliefs reflect confidence that the firm has a positive orientation toward its consumers beyond an “egocentric profit motive”

Integrity

• Integrity beliefs reflect confidence that the firm adheres to a set of moral principles or professional standards that guide its interactions with customers

Trusting Intentions

“Represent a willingness to make oneself vulnerable to another in the presence of RISK”

PURCHASE INTENTION

Searchers

The consumers who “search” for product information

Searchers think about and are persuaded more by product information and have a higher visitor-to-buyer ratio

Findings

• 1st Study—Online purchase intentions depended more on their beliefs about the firm’s Ability rather than Benevolence or Integrity

– Ability is the belief most relevant to Performance

Findings

• 2nd Study—Privacy and Security statements communicated a firm’s benevolence and integrity, but not ability

– High End Web sites did not convey benevolence or integrity beliefs

Findings

• 3rd Study—Web site investment and Ability on online purchase intentions are specific to “searchers” and not “browsers”

• “Browsers”—benevolence and integrity were more important

Findings

• 4th Study—The higher the RISK perceived by the consumer, the more they relied on Ability beliefs

Conclusion

• Web site investment influences searchers’ intentions to buy online by influencing one component of trusting beliefs—Ability, versus Benevolence and Integrity

• Investment in High End Web sites is warranted if the majority of your visitors are “searchers”

Conclusion

• The higher the RISK perceived by the consumer, the more they rely on Ability beliefs– These beliefs are successfully conveyed to the

consumer by the firm through effective “signaling”, like high investment Web sites

Works Cited

Ann E. Schlosser, T. B. (2006). Converting Web Site Visitors into Buyers: How Web Site Investment Increases Consumer Trusting Beliefs and Online Purchase Intentions. Journal of Marketing , 133-148.Hoffman, D. L. (1996). Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations. Journal of Marketing , 50-68.Kim, P. H. (2004). Removing the Shadow of Suspicion: The Effects of Apology Versus Denial for Repairing Competence versus Integrity-Based Trust Violations. Journal of Applied Psychology , 104-118.Kumar, N. L.-B. (1995). The Effects of Supplier Fairness on Vulnerable Resellers. Journal of Marketing Research ,

54-65.Moorman, C. R. (1993). Factors Affecting Trust in Market Research Relationships. Journal of Marketing , 81-101.Naquin, C. E. (2003). Online Bargaining and Interpersonal Trust. Journal of Applied Psychology , 113-120.

Paul Herbig, J. M. (1994). Marketing signals in industrial markets. Industrial Management and Data Systems , 16-21.Sitkin, S. B. (1993). Explaining the Limited Effectiveness of Legalistic 'Remedies' for Trust/Distrust. Organization

Science , 367-92.Sobel, M. (1982). Asymptotic Intervals for Indirect Effects in Structural Equation Models. SanFrancisco: Jossey-Bass.