NETNOGRAPHY:

OVERVIEW & HOW-TO

Anferny Chen & Hiro Sudo Feb 2012

We will help you understand…

AGENDA What is ‘netnography’

How great it is

How it works

Our first netnography experience

Takeaways

What is ‘netnography’

Internet + Ethnography

Ethnography

• Understand culture of

a community

• Qualitative method

• Field study

(Wikipedia)

How does Ethnography work?

Planning Where to go? How long?

Entrée Know the players Learn culture/

rituals

Data Collection

Observation Interview/

Questionnaire

Analysis Skills Experience

Reporting Academic Conference

Ethnography for Marketing Research

Knowing consumer culture provides insights about…

• Why people buy (Needs)

• How people like us (Brand perception)

• Who customers are (Segments)

• Why people choose us (Competition)

• How people respond to our ads (ROI)

Great hints for better

managerial decisions

Ethnography vs Well-known methods

Artificial

Outsider observation

Mostly numeric data

1 perspective/time

Natural

Immersive

Descriptive

Multi-method

Adaptable

Well-known methods Ethnography

A window into the realities: In-depth insight

Netnography: Online Ethnography

Technology makes ethnography…

• More cost-effective

• Less painstaking (automatically logged)

• Less obtrusive (more natural)

• Less time-consuming (geography)

• Accessible to various groups

• Able to observe the past

How does it work?

Planning

Entrée

Data Collection

Analysis

Reporting

Example Case: Listerine

Planning Entrée Data

Collection Analysis Reporting

Objective : Identify Listerine’s brand personality

Key Question : Where Listerine consumers gather?

What brand meanings has?

Target Group : Blogs such as Lost in Laundry

Planning Entrée Data

Collection Analysis Reporting

You need to…

• Know the culture of the community

• Behave as a community member

• Be accepted/credited by the community

Don’t forget that…

• This is not an interrogation

• Someone might have done the same research

• The community knows much more than you do

Entrée Failure (to an activist group)

A young researcher R.K.:

I am a professor at XX University…interested in finding out more about individual’s involvement in boycotts… This might help make your activities maximally effective… Thank you very much for your participation in this ‘cyber-interview’

Sincerely,

A member:

This is fishy!! Everyone, let’s

“BOYCOTT THIS RESEARCH”!!!!!

Entrée Failure (to an activist group)

A young researcher R.K.:

I am a professor at XX University…interested in finding out more about individual’s involvement in boycotts… This might help make your activities maximally effective… Thank you very much for your participation in this ‘cyber-interview’

Sincerely,

A member:

This is fishy!! Everyone, let’s

“BOYCOTT THIS RESEARCH”!!!!!

My force was not strong enough…

Communication with members, not the website

Planning Entrée Data

Collection Analysis Reporting

• Copy from pre-existing communications

• Cultural baseline info

• Copy & Paste or Archival Software e.g. Quotations

Archival Data

• Filter data by direct communications

• Objective-related info,

• Communal Interaction (postings) or Interviews (e-mail) e.g. Answer to specific questions

Elicited Data

• Record what you sensed/felt during the online experience

• Deeper insight into the culture,

• Note-taking e.g. Context (shocked by an event)

Fieldnote Data

Planning Entrée Data

Collection Analysis Reporting

“Generally, the idea of Listerine gives me the shivers. I think of the old school original flavor that my grandpa used to use and want to run screaming.”

“Grandpa always made me gargle with Listerine when I had a little cough or cold. Grandpa soaked his feet in Listerine. Coming up close for a hug, my Grandpa would always have the slight lingering scent of Listerine about him. ”

Archival Data Example: Listerine

• The brand is rooted in nostalgia

• Implications about limitations and

opportunities (such as new geriatric lines).

Planning Entrée Data

Collection Analysis Reporting

“Generally, the idea of Listerine gives me the shivers. I think of the old school original flavor that my grandpa used to use and want to run screaming.”

“Grandpa always made me gargle with Listerine when I had a little cough or cold. Grandpa soaked his feet in Listerine. Coming up close for a hug, my Grandpa would always have the slight lingering scent of Listerine about him. ”

Archival Data Example: Listerine

• The brand is rooted in nostalgia

• Implications about limitations and

opportunities (such as new geriatric lines).

Planning Entrée Data

Collection Analysis Reporting

• Star Trek “was the symbol of a world where there was no racism, poverty, deformity, idiotic nationalism, or political injustice … we fen [plural for fan] have put much of our energy into it, and into making the world a little more like the Federation which we admire so much” (e‐mail interview).

• “At its simplest, what Star Trek means to me—and, I think, to many fans—is possibility. … People do want to live in the Trek universe” (e‐mail interview).

Elicited Data Example: Why people like Star trek

• Utopian nature is the reason

• “Fen” implies established

culture of this community

Planning Entrée Data

Collection Analysis Reporting

• ”…I kept observational fieldnotes about my changing coffee habits, about conversations and meals at friends’ and families’ homes, about my shopping ventures, about my trips to Starbucks…”

• “Data about the effect that the community had on my entire social experience…” Rob Kozinets

Fieldnote Example: coffee connoisseur community

• Now you know the needs &

wants of the target segment

• You became a part of it

Planning Entrée Data

Collection Analysis Reporting

You need to…

• Clarify strategic implications

• Assume managers don’t understand jargons

• Be convincing with solid evidence & logics

Ethical Concern

You need to…

• Be respectful (introduce yourself, ask permission)

• Be legal (terms of use, human rights)

The Netnography Experience

Objective: Examine if the SMM Facebook page is enhancing peer-learning

Audiences: Online communities at Schulich, IMBA’12, GBC and SMM

Time Frame: Jan 18th to Feb 8th

Approaches:

Quantitative: Gathering the posts and replies info

Qualitative: Surveying the identified candidates to explore the depth of analysis and potential recommendation

Communities Background

IMBA’12: Small community provides interactive activities

outside of class

SMM: Mixed of small & large

community that aims to provide

interactive learning

GBC: Large community serves for information &

students interaction

Schulich Communities

SMM FB Activities: Jan 18th to Feb 8th

0

2

4

6

8

10

12

14

16

Posts

Replies

IMBA’12

Reply rate: 85%

Reply-to-post ratio: 5.07

Devotee: 3 out of 5 identified

Insider: 0 out of 5 identified

Tourist: 73% Mingler: 2 out of 5

identified

E-Tribal

Total # of members: 45

GBC

• Reply rate: 25%

• Reply-to-post ratio: 2.22

Devotee: 2 out of 6 identified

Insider: 0 out of 6 identified

Tourist: 94% Mingler: 4 out of 6

identified

E-Tribal

• Total # of members: 682

• % of one-time posters:

79%

SMM

• Reply rate: 49%

• Reply-to-post ratio: 1.42

Devotee: 3 out of 6 identified

Insider: 1 out of 6 identified

Tourist: 87% Mingler: 2 out of 6

identified

E-Tribal

• Total # of members: 346

• % of one-time posters:

60%

Highlights

* 85% reply rate

* 5.07 R/OP ratio

* A space for class and fun activities

* 49% reply rate

* 1.42 R/OP ratio

* A learning space or reporting duty?

* 25% reply rate

* 2.22 R/OP ratio

* Information space with sub-group

activities

Schulich Communities

Next Step

“There are lies, damn lies and statistics”

Questionnaires for qualitative analysis

Q1. Motivation for posting/ replying

Q2. What kind of contents you are likely to post or

reply to

Q3. What would motivate you to post/reply more.

Sample Archival Data Analysis (SMM)

Our guest today mentioned Don Tapscott - CBC Radio 1 has

broadcast 3 of a 4 part series, with the 4th next Sunday. All

available as podcasts

Linking the in-class activity with external resource. This post

provides the additional learning opportunity and resource for

other students

Sample Elicited Data Analysis (SMM)

A1 (motivation to post). I like to voice my opinion and engage

in a debate with my peers on certain topics. Plus we also

receive class participation marks for posting.

A2 (content). I like to reply to controversial topics the most.

A3 (motivation to post more). If more of my classmates replied

to my posts to further debate. And if some of the topics posted

were more controversial.

Controversial topic gets people interacting. Class-participation

mark is the incentive but getting more people involved would

generate the true motivation the peer-learning and interaction.

The Result?

To Be Continued!

Conclusion

Research Experience

• Being an anonymous is challenging for conducting

netnography research (lack of responce)

• Selection process (for identifying targets) takes time

• Need guidance and tools to stay objective

Learning Experience

• The mixed use of qualitative vs quantitative: one gets the

direction and another helps exploring the depth

• It’s fun and the observation is extensive, because there are

different angles to take and response extends the learning

Contributors

Sai Ra

Alyssa Fearon

Charmainne King

Pratysh D

Satyameet Ahuja

And many others

Alex Athanasopoulos

Sudeep Garg

Farhang

Suzanne Pragg

Norman Wong

Alex Wolf

Shaun Charles

Yvonne Chang

Sandeep Nath

Meggie Lee

Derek Lud

Brian Inigues

Social Media Marketing GBC & IMBA

QUESTIONS??

Thank you very much for listening