This presentation analyzed data from 200,000 Causes users to understand user types. Quantitative methods like k-means clustering and decision trees identified 6 personas. Surveys and interviews with 1,466 and 65 users provided qualitative data. The results identified six main user types of Causes: Casual Activist, Self-Assured Millennial, Practical Activist, Ambitious Activist, Organized Retiree, and Tenacious Veteran Activist. Future work will engage users through tailored approaches based on their needs and identify ideal user types.

1. Who are Causes users?
An Exploratory Analysis
Sara Vera
Data 2.0
April 30, 2013

2. In this presentation:
1. Causes Data Overview
2. Quantitative Methods
• K-means Clustering
• Decision Trees
3. Qualitative Methods
• Surveys
• Interviews
4. Results

3. Causes Data Overview
• Basic demographics from Facebook Connect
• Gender, Age, Location
• Behavioral data from Causes’ website
• Actions taken, Campaigns followed
• Surveys and Interviews
• Third party source to validate our demographic
information

4. This Research
Quantitative Analysis
• 200,000 Users on our website in the last 6 months
1. K-Means Cluster Analysis
2. Decision Trees

5. K-Means Clustering

6. Decision Trees

7. Qualitative Analysis
1. Surveys – 1,466 respondents
2. Interviews - 65 participants

8. Goals
1. Understanding how people use Causes.com
• What inspired you to use Causes?
2. Learning about campaign activity beyond Causes’ website
• How active are your friends in protests, petitions, boycotts, etc.?
3. Learning as much as possible about a wide range of topics
• First things first: I want to learn more about you! Can you describe
your “typical day” (if there is such a thing)?
• How big of a role does activism, philanthropy, or volunteering play
into your everyday life? Has that changed over time?

9. Results: Six User Personas
1. 2. 3. 4. 5. 6.

10. Future Directions
• Give a face/personality to our users
• Engage users with tailored approaches
• Identify our ideal user types and find effective ways
to engage them

11. Thank You

12. Who are Causes users?
An Exploratory Analysis
Sara Vera
Data 2.0
April 30, 2013
Hi. My name is Sara Vera and I am a data analyst at Causes, which was founded by Sean
Parker and Joe Green as the first Facebook app but recently became a separate platform
as Causes.com. We are a website that uses social networking tools for a multifaceted
approach to organizing campaigns for social change.
The purpose of the research that I’m going to explain today is to understand our users and
how to optimize the Causes platform to meet their needs -- since our overarching goal at
Causes is to mobilize people to take offline action and get involved in the issues that they
care about, whether it’s worldwide, nationwide or in their local community.
In this presentation:
1. Causes Data Overview
2. Quantitative Methods
• K-means Clustering
• Decision Trees
3. Qualitative Methods
• Surveys
• Interviews
4. Results
In this presentation, I am going to explain steps we took to create a picture of our users. I
will go over a broad description of the data, our mixed-methods approach – which began
with clustering analysis and decision trees and ended with surveys and interviews. I will
finish with a description of the resulting personality types of our users.
Data Overview
1. Basic demographics from Facebook Connect
• Gender, Age, Education
2. Behavioral data from Causes’ website
• Actions taken, Campaigns followed
3. Surveys and Interviews
4. Third party source to validate our demographic information
Causes collects broad demographic and geographic information through Facebook
Connect when users create a Causes account. Most of our quantitative information,
however, is collected from Causes’ website. We know which actions a user has taken,
which campaigns they are following, how many people they’ve recruited to join a cause
and more.

13. We supplement our quantitative information with surveys and interviews that cover a
wide range of topics from how people use Causes to how people get involved in
campaigns or volunteer activities in their local communities.
Quantitative Analysis
• 200,000 Users on our website from June to December 2012
1. K-Means Cluster Analysis
2. Decision Trees
For this research, we subset our data to 200,000 users who used Causes between June and
December 2012. From 230 variables, we derived 30 predictive variables by which to start
categorizing our users, such as age, income, education, their activity level and topical
interests in Causes campaigns.
We ran k-means clustering algorithm on our entire data set, which resulted in 6 distinct
personality types/personas/clusters.
K-means visual: This is a sample clustering with a small sample of our user base (Casual
Participants are not included in this sample because they are pretty spread out, forming a
cluster in how they are not really represented anywhere else). The bottom two clusters are
the Tenacious Veteran Activist and the Self-Assured Millennial, which exhibit drastically
different behavior than the top three clusters--that's why they're "farther" away. It's hard
to gauge distances like this, but it’s a cool and informative visualization of what our user
base looks like.

14. We then used these 6 clusters to train the random forest model to find how predictive
each variable is in identifying which cluster someone belongs in. Using the random forest
model, we found 30 variables that best predicted which cluster a user belonged to.
Decision Tree slide:
This is an example of one decision tree.
(K-means algorithm will tell us whether you’re a Self-Assured Millennial or the
Ambitious Activist, random forest will tell us how predictive a variable is in identifying
which cluster someone belongs in)
Could have done a linear regression as well, but we found random forest to be more
accurate.
Surveys
• 1,466 Survey respondents
Goals
1. Understanding use of Causes.com
• What inspired you to use Causes?
2. Campaign activity beyond Causes’ website
• How active are your friends in protests, petitions, boycotts, etc.?
Using the behavioral and demographic trends we saw through our machine learning
classification, we dug deeper into the motivations of our users through surveys and
interviews. The survey was 20 questions and we received almost 1,500 survey responses.
There were more responses in certain clusters, so we took this into consideration for
subsequent surveys to get a representative sample.
We asked:
• What inspired you to start using Causes?

15. • What do you aspire to do on Causes?
• In the past two months, have you taken action outside of Causes on something you
care about (e.g., signed or started a petition, attended a protest, donated to a
political campaign, etc.)?
• In general, to what extent do you share political and social views with your
friends?
• How active are your friends in protests, petitions, boycotts, etc.?
• What are the top three qualities that make you care about a cause?
Interviews
• 65 participants
Goals
• Learning as much as possible about a wide range of topics
• First things first: I want to learn more about you! Can you describe your
“typical day” (if there is such a thing)?
• How big of a role does activism, philanthropy, or volunteering play into
your everyday life? Has that changed over time?
Users indicated on the survey itself whether they’d be interested in participating in an
interview. We conducted 65 interviews of 3 – 5 questions that lasted 30-45 minutes with
approximately 10 people from each cluster. We spent several weeks walking through the
notes, using design thinking methodology, and highlighting major themes and differences
across clusters.
Results: Explain the variables on the left …
%"of"Total"Causes"Population 39% 14% 13% 11% 10% 8%
Age 46 38 25 59 68 35
Female 23% 41% 43% 52% 78% 52%
Income 45A55K 55A65K 35A45K 85A100K 20A35K 55A65K
College"Educated 42% 55% 73% 61% 34% 62%
#"of"Friends"on"Causes 74 294 278 195 359 102
#"of"Invites"sent 157 254 86 104 943 95
#"of"Actions"Taken 10 25 8 19 42 19
Days"Since"Last"Action 16 30 49 4 2 10
#"of"Actions"in"each"category:
"""Animal"Rights 0.53 0.72 0.98 1.04 2.95 0.23
"""Envronment 0.32 0.98 1.02 1.05 0.95 0.85
"""Health 0.75 0.12 0.35 0.82 0.23 0.96
"""Women's"Rights 0.75 0.82 0.54 0.49 0.32 0.34
Casual"
Activist
Self7Assured"
Millenial
Practical"
Activist
Ambitious"
Activist
Organized"
Retiree
Tenacious""
Activist

16. “The ambitious activist” is in his mid-forties, and wants to make a bigger impact on the
world than he has so far. He’s passionate, talkative, and enthusiastic about sharing his
newfound passion with as many people as possible.
“The practical activist” is in his late thirties, he has focused ideas on how he can best
affect change in the world and he seeks to find a soapbox where he can share his ideas
with an audience. Sites like Causes are supplements to his offline activism, not a
substitute. He’s frustrated by the number of inefficiencies he sees in the lack of
collaboration amongst organizations running different campaigns all focused on a shared
goal.
“The self-assured millennial” is in his mid-twenties, he is a recent grad with his
Bachelor’s degree who is thinking about signing up for graduate school. As with many in
their mid-twenties, he is self-confident and believes that he can play an integral part in
changing the world around him. It can be difficult for him to pledge allegiance to just one
campaign or organization - if he sees injustice, he wants to get involved, no matter the
context.
“The organized retiree” has recently retired after a successful career and is not ready to
slow down. As a practiced organizer, she approaches her work methodically: she
researches legislation, educates herself and stays active through leadership roles in local
organizations. She is interested in pushing her own definition of what it means to
organize effectively, and is curious to see how her own efforts stacks up against others.
“The tenacious veteran activist”: Although she is retired and has a couple health
problems that keep her mostly homebound, her enthusiasm for change is as prevalent as
ever. She’s been involved in campaigns for social change throughout her life; a lack of
mobility has driven her to participate now online. Even though taking action on sites like
Causes is not necessarily something she enjoys, she does view her involvement as
important and meaningful.
“The casual participant”: While she would by no means identify herself as an activist,
she does recognize the flaws and frustrations in the world around her. She occasionally
visits sites like Causes through invites from her friends, but does not feel any loyalty to
the campaigns in which she participates. Her busy and successful professional life in
addition to her uncertainty about online action attribute to sporadic participation.
Future Directions
• Ask “What are their needs?” and structure our product roadmap accordingly
• Engage users with tailored approaches
• Identify our ideal user types and find ways to better engage them