The document discusses the transformation of transportation through the emergence of on-demand shuttle networks facilitated by software and smartphone apps, projecting significant growth from 2017 to 2030. It emphasizes the importance of measuring the expected lifetime value (ELTV) of users and the effectiveness of marketing campaigns in a low-margin, high-volume business model. The challenges of estimating ELTV components such as life expectancy and revenue streams are highlighted, along with the use of machine learning to improve accuracy in these measurements.

1. Quick Measurements of Long Term
Effects in a Growth Environment
April 2017 ● All Things Data
Saar Golde, Chief Data Scientist

2. Transportation is undergoing a once-in-a-century transformation
2017 -> 2030: Networks of On-Demand Shuttles
(dynamic, shared, electric, autonomous)
1900: 20mm horses and horse carriages 1900 -> 1930: 15mm Model T cars
2017: 1.2bn private cars
10mm buses

3. Via: Software for operating networks of on-demand shuttles
On-demand
Passengers book using a smartphone app
Convenient
Passengers are picked up within minutes at a
nearby corner – a “virtual bus stop”
Shared
Passengers are seamlessly matched with
others heading in the same direction
Fully Dynamic
Vehicle routes and schedules are
updated in real time
((( )))
Pick-up
Drop-off
((()))

4. Via is the world’s first on-demand shuttle network
operating at scale
shared rides since
launch (2013)
13M+
rides per week
250,000
Venture funding
$137M
members across
NYC, Chicago, DC
700,000+
Via efficiency vs
competition
3x
Major global partnerships
launching in 2017
Global

5. Economics of Ridesharing
Rapid Growth
Low Margin Repeat Business
#ATD2017

6. The Approach: use Expected Life Time Value
• Low margin and repeat business: Need to measure long term effects
• For example, life time value
• Rapid growth: most users are active
• Can only measure life time value for a small subset of users
• Quick measurement
• Can’t wait till rider’s end-of life
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The Challenge: Measuring Marketing
Campaign Effectiveness

7. Expected Life Time Value
Expected sum of (discounted) future stream of value (revenue / profit)
Three main components:
• Life expectancy (duration)
• Stream of value (amount per unit of time)
• Correlation between life expectancy and the stream of value
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8. Estimating the Effect of a Marketing
Campaign on Expected Life Time Value
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Incremental Value Added Life Expectancy Correlation B/W the two

9. Key Points for ELTV Estimation
• Control group(s) needed
• Stream of value (amount per unit of time)
• Quickest and most direct
• Life expectancy (duration)
• Slower to estimate but just as critical
• Machine learning speeds up estimates
• Correlation between life expectancy and the stream of value
• Hardest / slowest to measure
• Tricky to incorporate directly into ELTV
• When positive can be omitted to find lower bound on campaign effectiveness
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Refine&
Iterate

10. Questions ?
Comments !
Thank You!
#ATD2017