Presentation at AMA Conference August 2013 in Boston

1. Customer Services in Social Media Channels:
An Empirical Analysis
AMA Summer Marketing Educator Conference | Boston | August 11th 2013
Alexander Rossmann | Professor for Marketing and Sales | Reutlingen University

2. Page  2
Social Media and Marketing
 Web 2.0 / Social Media describe
a general shift in the use of the internet.
 Key characteristics:
Digital media, interaction, user generated
content, users as prosumers, connected
customer, social networks.
 Social Media is not only Facebook.
 Firms struggle in order to evaluate
the value of social media for marketing.
 Theory of market orientation
→ interaction orientation → engagement.
(Kumar et al. 2012).
 User engagement drives value,
firms foster marketing strategies in order
to engage customers and employees.

3. Page  3
Engaging Customers in the Corporate Value Chain:
Potential Pathways
 New Product Development.
 Open Innovation,
Crowdsourcing.
 Test of Products and Services.
 Branding, Word-of-Mouth Communication.
 Customer Services,
Complaint Management.
 Self Services, Peer-to-Peer Services,
Contact Avoidance.
 etc.

4. Page  4
Social Media versus Hotline:
Differences in Customer Service Design
Third-Party
Visibility
Service
Design
Level of
Standardization
Role of
Service Agents
Hotline Social Media
closed shop open
time lagged real time
high
anonymous public
low

5. Page  5
Social Media in the Service-Value-Chain
Customer
Complaint
Service
Reaction
Perceived
Service Quality
Customer
Satisfaction
Word-of-Mouth
Communication
= Engagement
= Reach
= Service Knowledge

6. Page  6
The Ultimate Goal …
The ultimate goal of service strategies in social media channels
is to turn complainers into fans.

7. Page  7
Relevant Issues for Service Research
 Dimensions of service quality.
 Impact of service quality
on customer satisfaction.
 Impact of customer satisfaction
on firm performance.
 Contact avoidance, cost reduction,
optimal service level.
 Word-of-Mouth communication,
effect of positive service experiences.
 Service design and service interaction.
 Scalability of service capacity.
 Employee effects in different channels.

8. Page  8
Research Questions
 How should customer service quality in
social media channels be conceptualized
on multiple levels?
 Which aspects of customer service quality
are important in enhancing customer
satisfaction?
 What outcomes are effected by customer
service quality and customer satisfaction?
 How effective are customer services
delivered through social media channels
(as compared to customer services
delivered through other channels)?

9. Page  9
Theoretical Background
Distributive
Justice
Procedural
Justice
Interactional
Justice
 While early papers on post-complaint behavior center on fairness in general
(Blodgett, Hill, and Tax 1997; Goodwin and Ross 1989), it is now quite agreed
that customers perceive fairness in three dimensions.
 The distinctness of the three justice dimensions has recently been called
into question (Gelbrich and Roschk 2012). Davidow (2003) and Liao (2007)
report on high correlations between the three justice dimensions.

10. Page  10
Conceptual Framework
Customer Effort
Customer
Satisfaction
Customer
Loyalty
Procedural
Quality
Quality of
Interaction
Fairness
Quality of Solutions
Word of Mouth
Cross-Sell
Preferences
Perceived
Service Quality
Customer
Satisfaction
Outcomes
H3
H4
H5
H2
H6
H7
H8
H1 (-)

11. Page  11
Context & Empirical Analysis

12. Page  12
Methods
 Customer services at Telekom are delivered through traditional channels
(hotline, email, letter) and through social media like Facebook and Twitter.
 Two different samples:
Sample A = Traditional Channel (hotline)
Sample B = Social Media (facebook, twitter)
 Complaining customers were interviewed immediately
after a service experience in different channels.
 Questionnaire was developed on the same procedures as were recommended
by Churchill (1979) and Gerbing & Anderson (1988).
 Pretest involving 186 customers was conducted. With a view to eliminating items with
low loadings or high cross loadings, the measures for each construct were scanned
for evidence of validity and reliability.
 Final sample:
220 customers from sample A
220 customers from sample B

13. Page  13
Results of CFA,
Structural Path Model
 Unidimensionality and convergent validity of the constructs were examined
by confirmatory factor analysis (CFA) performed on both samples using LISREL.
 All items load on their respective constructs at the 0.01 level,
demonstrating satisfactory convergent validity (Anderson and Gerbing 1988).
 To assess the discriminant validity of the constructs, a model constraining the
correlation between a pair of constructs to 1 was compared with an unconstrained
model (Bagozzi, Yi, and Phillips 1991).
 After the measurement models were deemed acceptable,
we estimated a structural path model to test the depicted hypotheses.
 A chi-square difference test reveals that a model with direct effects (direct paths from
the antecedent variables to the three target variables) does not have significantly
better fit indexes than our full mediation model (Bagozzi and Yi 1988).
 Additionally, we applied an established multigroup method to analyze the differences
between both samples according to our research model. Therefore, we used an
extended LISREL model with mean structures (Jöreskog and Sörbom 1996).

14. Page  14
Results of Multigroup Analysis
Fit Indixes:
χ2(618) = 992.40, CFI= .984; NFI= .964; RMSEA = .053
Hn
H1
H2
H3
H4
H5
H6
H7
H8
Effect
Customer Effort → CS
Procedural Quality → CS
Quality of Interaction → CS
Fairness → CS
Quality of Solutions → CS
CS → Customer Loyalty
CS → Word of Mouth
CS → Cross-Sell Preferences
Hotline
-.19
.23
n.s.
.21
.46
.55
.24
.68
SoMe
-.28
.29
.26
.17
.19
.94
.72
.59

15. Page  15
Implications
 Quality of interaction and the reduction of
customer efforts are especially important
in services delivered through social media.
 Key predictor of customer satisfaction
in the hotline channel is the quality of
service solutions.
 Word of mouth communication is
particularly relevant for customer services
delivered through social media, whereas
the same effect is considerably weaker for
traditional hotline services.
 Customer satisfaction created in social
media impacts significantly stronger on
customer loyalty.

16. Page  16
Calculating the Return on Social Media:
Integrating SEM and Analytical CRM Data
Cost of Service
Costs per service contact via social media are
significantly higher (compared to hotline), but
service agents in social media need fewer
contacts per service case.
Service Quality
Customers report a significantly higher
service quality in social media channels.
Customer Effects
Service quality improvements lead to a strong
reduction of the firms churn rate and a
significant increase in WOM communication.

17. Page  17
Further Research Directions
 Scalability of service capacity
in social media channels.
 Peer-to-Peer services, integration of third
party resources in the service process.
 Employee effects in different channels.
 Moderating effects
(e.g. role of different service cases).
 Theory of customer and employee
engagement in the service process.

18. Page  18
Thank you!

19. Page  19
Contact Information
Alexander Rossmann
Reutlingen University
Professor for Business Administration
Alteburgstrasse 150
72762 Reutlingen | Germany
mobile: +49 (172) 711 20 60
skype: alexander.rossmann
alexander.rossmann@reutlingen-university.de

20. Customer Services in Social Media Channels:
An Empirical Analysis
AMA Summer Marketing Educator Conference | Boston | August 11th 2013
Alexander Rossmann | Professor for Marketing and Sales | Reutlingen University