1. Enhancing the digital experience at the Smithsonian
MCDP Non-Profit Challenge
Alexa Arboleda, Natasha Koduri, Ruta patel, and Rachel Snyder

2. LANDSCAPE
ANALYSIS
Alexa Presents

3. SMALL DONATION BUTTON ON WEBSITE
Donations At National
museum of natural history (NMNH)
SMALL DONATION BUTTON ON WEBSITE
Alexa Presents
Source:

4. successful case study MET APP LAUNCHED IN SEPTEMBER 2014
USED 1.9 MILLION TIMES IN FIRST 21 MONTHS
APP FEATURES INCLUDE INTERACTIVE MAPS, EXHIBIT RECOMMEDATIONS, AND DONATION LINKS
Alexa Presents
Source:

5. Donor and Non-Donor Demographics at NMnH
Alexa Presents

6. Nmnh demographic snapshot Analysis based on a sample of 5,000 visitors in 2016 surveyed as they visited the museum desk.
Sample dataset Shows nmnh museum attendees, on average, are: 
Middle age
AVERAGE AGE: 38.3 YEARS OLD
White
74% ARE WHITE
Educated
88% ARE AT LEAST COLLEGE EDUCATED
Live in US
90% live Domestically 
Alexa Presents

7. Demographic Analysis: donation patterns donation amounts by age group and method of donation for past donors only are broken out below.
Ages 30 – 59 donate the most ($) overall
Most of these donations are occurring on non-mobile platforms
Teens and year olds have larger % of donations via mobile
Alexa Presents

8. Non-Donor attitudes toward technology out of the 5,000 visitors, 60
Non-Donor attitudes toward technology out of the 5,000 visitors, 60.6% (3030) responded they have not donated to the museum in the past.
Out of the 3,030
non-donors:
70% used phone in interactive museum exhibit
56% would like supplemental info on museum exhibits 
63% used phone to make payment in past year
Alexa Presents
POTENTIAL OPPORTUNITY FOR INCREASED USE OF MOBILE APP

9. SI Museum Attendance
NMNH makes up ALMOST 25% of total SI visits over the past 6 years
Ideal Pilot site for click to donate application
Alexa Presents

10. Viability of click-to-donate app
Findings reveal success of click-to-donate-app at the nmnh:
Opportunity to pilot to a critical mass of people and make a significant difference in the Smithsonian’s Volume of donations
Patterns of mobile phone usage among non-donors suggesting an increased user base for the app
Trends across age groups regarding donation amount and method highlight potential for increased donations with mobile platform
Alexa Presents

11. Data Limitations
SAMPLE MAY NOT BE REPRESENTATIVE OF POPULATION BASED ON SURVEY METHODOLOGY
BIASED SURVEY METHODOLOGY: CONVENIENCE SAMPLING AND NOT RANDOM
MONTH TO MONTH DATA NOT AVAILABLE FOR MUSEUM TRAFFIC
Alexa Presents

12. COST MODEL
Alexa Presents

13. Model the cost projection model simulates various payback scenarios to determine the most likely payback period.
Project Cost Breakdown
Total project cost: $417,418
At month 7: SI owes $229,580
Remaining cost*: $247,469
*Includes month 8 labor charges
Simulated Model Inputs
# of monthly visitors
Average donation amount
% of donations Accenture receives
Rachel Presents

14. assumptions SAMPLE IS REpRESENTATIVE OF THE POPULATION
ANNUAL Historical data is used to determine the expected number of annual visitors
Donations STAY CONSTANT ACROSS THE ENTIRE PROJECT PERIOD and do not account for seasonality.
Average donation is used as an input as donations vary by age distribution
77% OF si VISITORS OWN SMARTPHONES
POPULARITY OF APP Stays CONSTANT
Rachel Presents

15. demo
Rachel Presents

16. Projections The most likely scenario:
After generating 1,000 different scenarios:
The likelihood that the payback period is less than 3 months is 62.8%.
The likelihood that the payback period is less than 12 months is 75.9%.
The most likely scenario:
after 8.98 months, 100% of the donations collected via the mobile app will go to the Smithsonian institute.
Factors that must be present:
- 638k visitors per month
- $5 average donation among donors
- Accenture receives 3.0% of donations
Rachel Presents

17. Next steps: analysis
Conduct a Controlled survey analysis for a more representative sample and refined data analysis.
Collect monthly museum attendance data to enable advanced forecasting techniques that include seasonality components.
Utilize advanced analytical modeling to determine the likelihood of an individual to donate.

18. Sources Lee W. Wilson, Natural history Museum background picture