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ONLINE CONSUMER PSYCHOLOGY

Jacob L. Orquin, Ph.D.

Department of Business Administration

Aarhus University

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LEARNING OBJECTIVES

Understand how to:

Create trust

Persuade customers

Create loyalty

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MATCHING GOALS

Change users or change website?

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TRUST

Why is trust important to online marketing?

Can we imagine economic transactions without trust?

How do they take place?

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TRUST AND ECONOMIC EXCHANGES

So what’s the value of trust in e-commerce?

• Low degrees of trust are detrimental to economic exchanges

• Increased levels of trust are associated with a higher conversion rate

• Increased levels of trust are associated with satisfaction and loyalty

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TRUST AND ECONOMIC GROWTH

Denmark is not part of the study, but is probably somewhere near to

Norway (NOR)

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INTERPERSONAL TRUST ACROSS NATIONS

Denmark is not part of this graph but it’s up here!

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TRUST

A (very) simple model of trust (Sultan et al 2002)

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TRUST SEALS

Trust seals has been used to incease consumer confidence in e-commerce

since the earliest days of online shopping but the documented effect is

quite modest.

According to Sultan et al. (2002) trust seals only account for 0.2 % of

explained variance in trust!

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TRUST SEALS

Secific e-commece vendors claim to have improven conversion rates for

new visitors with up til 7 % using trust seals.

Screenshot from billigvoks.dk

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FACTORS PREDICTING TRUST

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PREDICTORS (CONT)

Percent of respondents who self

motivatedly commented on

certain website characteristics

influencing website credibility.

(Fogg et al. 2003)

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PERSUASION

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ELABORATION LIKELIHOOD MODEL

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PERSUASION STRATEGIES

Cialdini identifies 6 compliance strategies

• Reciprocity

• Commitment and Consistency

• Social Proof

• Authority

• Liking

• Scarcity

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RECIPROCITY

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COMMITMENT AND CONSISTENCY

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SOCIAL PROOF

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AUTHORITY

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LIKING

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SCARCITY

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LOYALTY

Why is loyalty important to online marketing?

What difference does it make if have to attract new customer for every

sale we make?

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RETENTION IS (VERY) PROFITABLE!

A 10 % change in repeat

customer conversion leads to a

10 % change in net present value

Agrawal et al (2001) E-

performance

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LOYALTY AND SATISFACTION

The apostle model

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WOM AND SATISFACTION

There is a U-shaped relation between satisfaction and WOM

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WORD OF MOUTH

WOM: contributes with 30 % of customers and has no specific budget

allocation!

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SO WHAT’S THE POINT?

Customer satisfaction is a strong predictor both of WOM and

loyalty.

Among online marketing initiatives WOM and loyalty have

the highest ROI.

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WOM AND LOYALTY

Carpenter (2005) Consumer shopping value, satisfaction, and loyalty for

retail apparel brands

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ANTECEDENTS TO E-SATISFACTION

The Szymanski & Hise (2000) model was tested and re-examined in 2004.

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CORRELATIONS WITH CONVENIENCE

Results from Szymanski & Hise (2000) seem to focus on general aspects of

e-commerce:

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E-SATISFACTION AFFECTS RETENTION AND CONVERSION

Bansal et al (2004) Relating e-satisfaction to behavioral outcomes

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ANTECEDENTS TO E-SATISFACTION

Results from Bansal et al (2004) Relating e-satisfaction to behavioral

outcomes

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MODERATORS OF E-SATISFACTION

Yes, e-satisfaction does affect e-loyalty …

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ONLINE VS. OFFLINE

Satisfaction has an even stronger impact on loyalty online than offline!

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FACTORS AFFECTING LOYALTY

Borrowed from Reibstein (2002).

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TOUCH POINT ANALYSIS

Mapping customer touch points: satisfaction can be replaced with

performance for fast benchmarking

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GATHER YOUR DATA

Gathering questionnaire data is practically free. What matters is integrating

the data sources

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SURVEY SOCIAL MEDIA

Get direct input on what you have

done right and wrong!

Complaint about support center

Complaint about broad band service

Complaint about support center

Ok delivery but bad support

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OTHER WEB 2.0 TOOLS

What are they talking about and how much are they talking?

Social media monitoring: Buzzmetrics, Cymphony, Google blogsearch,

Blogpulse.com

Facebook Lexicon Google blogsearch Blogpulse.com

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INTEGRATE THE DATA!

Measure and integrate data sources. There are no universal truths so

always check what works on your website.

E-Satisfaction web analytics pipeline metrics

Is there any correlation between the data?

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DEVELOPING E-SATISFACTION

Setting expectations: do you deliver what your market communication

promised?

Website characteristics: how is your websites’s ease of use,

content/information, price, and product selection doing?

Customer service: check your support, delivery, and complaints.

e-CRM applications: there are no killer apps! Feinberg & Kadam (2002)

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CONTACT

Jacob L Orquin, Ph.D.

Department of Business Administration

Aarhus University

E-mail: jalo@asb.dk

Check out my company:

www.userpilot.dk