Samenvatting
Samenvatting - All necessary Articles; Digital Marketing and Metrics (E_EBE3_DMM)
All articles needed to pass the exam summarized in a way that is easy to understand and memorize! Received an 8.8 for the exam.
[Meer zien]Voorbeeld 4 van de 42 pagina's
Voorbeeld 4 van de 42 pagina's
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Voorbeeld van de inhoud
Article Summary: Digital Marketing &Metrics
Rik Smits – 2023/2024
,Index
In-class articles
1. Babić Rosario, de Valck & Sotgiu (2020). Conceptualizing the electronic word-of-mouth process:
What we know and need to know about eWOM creation, exposure, and evaluation.
2. Babić Rosario, Sotgiu, De Valck & Bijmolt (2016). The effect of electronic word of mouth on sales:
A meta-analytic review of platform, product, and metric factors.
3. Bleier & Eisenbeiss (2015). Personalized online advertising effectiveness: The interplay of what,
when, and where.
4. De Haan, Wiesel & Pauwels (2016). The effectiveness of different forms of online advertising for
purchase conversion in a multiple-channel attribution framework.
5. Hanssens & Pauwels (2016). Demonstrating the value of marketing.
6. Herhausen, Kleinlercher, Verhoef, Emrich & Rudolph (2019). Loyalty formation for different
customer journey segments.
7. Lemon & Verhoef (2016). Understanding Customer Experience Throughout the Customer
Journey.
8. Liadeli, Sotgiu & Verlegh (2023). A meta-analysis of the effects of brands’ owned social media on
social media engagement and sales.
9. Reinartz, Wiegand & Imschloss (2019). The impact of digital transformation on the retailing value
chain.
10. Reinartz, Wiegand & Wichmann (2019). The Rise of Digital (Retail) Platforms.
11. Rietveld, Van Dolen, Mazloom & Worring (2020). What you feel, is what you like influence of
message appeals on customer engagement on Instagram.
12. Srinivasan, Rutz & Pauwels (2016). Paths to and off purchase: quantifying the impact of
traditional marketing and online consumer activity.
13. Wang, Guo, Susarla & Sambamurthy (2021). Online to offline: the impact of social media on
offline sales in the automobile industry.
Other reading materials
14. Akpinar & Berger (2017). Valuable Virality.
15. Borah, Banerjee, Lin, Jain & Eisingerich (2020). Improvised marketing interventions in social
media.
16. Hughes, Swaminathan & Brooks (2019). Driving brand engagement through online social
influencers: An empirical investigation of sponsored blogging campaigns.
17. Leung, Gu & Palmatier (2022). Online influencer marketing.
18. Tellis, MacInnis, Tirunillai & Zhang (2019). What drives virality (sharing) of online digital content?
The critical role of information, emotion, and brand prominence.
19. Wies, Bleier & Edeling (2023). Finding goldilocks influencers: How follower count drives social
media engagement.
,Babić Rosario et al. (2020)
This review paper discusses the concept of electronic word-of-mouth (eWOM) by providing a structured
analysis of its creation, exposure, and evaluation processes. It aims to develop a comprehensive
understanding of eWOM, proposing a framework based on consumer motivations, opportunities, and
abilities (Motivation-Opportunity-Ability framework).
Findings
Electronic word-of-mouth (eWOM) is consumer-generated, consumption-related communication that
employs digital tools and is directed primarily to other consumers.
Motivations for eWOM Creation: Includes altruism, social value, hedonic benefits, impression
management, balance restoration, and economic incentives.
Stages of eWOM:
1. eWOM Creation: Influenced by consumer motivations, opportunities (internet access, platform
availability), and abilities (product knowledge, technical skills).
o Consumer Perspective:
Motivations: Altruism, social value (belonging to a group), hedonic benefits
(enjoyment of sharing experiences), impression management (managing other
people’s views of yourself), balance restoration (venting in case of bad
experiences), and economic incentives.
Opportunities: Access to devices and the internet, low posting costs, various
eWOM formats.
Abilities: Product knowledge and technical skills.
o Marketer Perspective:
Strategies to Encourage Creation: Utilize communication, community building,
and incentives.
Examples: Amazon and Bed Bath & Beyond using emails to invite reviews,
Sephora’s community engagement, monetary and non-monetary incentives like
loyalty points.
Challenges: Addressing self-oriented motivations and ethical issues related to
incentivizing eWOM.
, 2. eWOM Exposure: Driven by motivations such as reducing uncertainty and cognitive dissonance,
and accidental exposure through network effects.
o Consumer Perspective:
Motivations: Reduce uncertainty and perceived risk, leisure activities, cognitive
dissonance reduction (reassurance from others online after use).
Opportunities: eWOM visibility, network characteristics, contagion effects.
Abilities: Internet literacy, ability to navigate eWOM formats.
o Marketer Perspective:
Strategies to Increase Exposure: Make eWOM more visible and searchable, use
traditional marketing, leverage network effects.
Examples: Displaying reviews in promotional materials, using influencers,
implementing sorting features on platforms.
Challenges: Managing the balance between visibility and information overload,
understanding cultural differences in eWOM consumption.
3. eWOM Evaluation: Based on consumer traits (need for cognition, cultural characteristics),
message characteristics (credibility, completeness), and platform features.
o Consumer Perspective:
Motivations: Susceptibility to interpersonal influence (peer pressure), need for
uniqueness (individuals with high need for uniqueness might prefer reviews that
highlight unique details), message credibility.
Opportunities: Device and platform characteristics, eWOM format and
presentation.
Abilities: Cognitive capacity, managing information overload, detecting fake
eWOM.
o Marketer Perspective:
Strategies to Facilitate Evaluation: Use of credibility markers, structured eWOM
display, sorting features.
Examples: Including status markers, helpfulness scores, sorting eWOM by
relevance.
Challenges: Facilitating the identification of fake eWOM, managing the influence
of device use on eWOM evaluation.
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