1. National Domestic Violence Hotline
Yan Gao
Jina Kang
Rebecca Lawrence
Wade Treichler
INF 385T - Visualization

2. National Domestic Violence Hotline
• Founded in 1996 as part of the Violence Against Women Act
(VAWA)
• National call center for victims of domestic violence
• Provides counseling, referrals to local programs
• 24/7 Operation with phone, web-chat and text messaging
(SMS)

3. Prevalence
• 1 in 4 women (24.3%) and 1 in 7 men (13.8%) aged 18 and older in
the United States have been the victim of severe physical violence by
an intimate partner in their lifetime.
• 1 in 3 teens will experience dating abuse.
• The costs of domestic violence and related issues exceed $5.8 billion
each year, nearly $4.1 billion of which is for direct medical and
mental health care services.
• Nearly 8 million days of unpaid work are lost each year due to
domestic violence issues—the equivalent of 32,000 full time jobs.

4. Call Volume – 2013
• Three millionth call was taken last year
• Calls received - 264,415
• Chats received - 55,610
• Texts received - 11,053
• Total contacts - 331,078
Over the last 18 years, 3.4 million people have received much-needed
advocacy from NDVH around issues of domestic and dating violence.

5. Abandonment Rate
Defined As:
Calls on hold that hang-up
Chats requested that go answered
SMS Unresponded
Estimates for 2013 abandonment: +70,000

6. Data
Phone System
Data includes:
• date and time
• call duration
• answered status
• agent statistics
• level of service

7. Data
Chat System
Data includes:
• chat requests
• operator-engaged chats
• chats started
• abandoned chats
• average wait time
• average wait time to abandoned
• maximum wait time
• maximum wait time to abandoned

8. Data
Intake Application
NDVH has a custom-built platform (commonly called the Caller App) that acts as both an
intake and referral platform.
Reporting data includes:
• varied demographic information
• situational components specific to each call
• frequency data on the resources provided

9. Data
Social and Web Reach
Data is manually integrated into a spreadsheet on a monthly basis and includes:
• Google analytics
• Facebook insights
• Sprout Social
For the purposed of this project we can access either the aggregated data or the primary
sources.

10. Possible Project Questions
• How do denied-service patterns correlate to client demographics and
situational elements?
• Can these correlations help management and staff to predict
significant fluctuations in service requests?
• How do fluctuations in service requests compare across different
media systems and platforms?
• Can wait-time aggregations be used to identify key duration windows
for likely abandonment?