Quick Measurements of Long Term Effects in a Growth Environment Ridesharing is a quickly growing, low margin business where repeat usage and habit formation is key. That means that marketing efforts need to be measured by their impact on user lifetime value, rather than any immediate outcome. Saar Golde, thee Chief Data Scientist at Via, will review best practices for measuring campaign outcomes in a framework that revolves around user lifetime value: how to measure the effect of personalized, targeted campaigns on the different components of user lifetime value, user churn and user revenue stream, and how to do that in an environment of rapid growth.

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
#ATD2017
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
#ATD2017

8. Estimating the Effect of a Marketing
Campaign on Expected Life Time Value
#ATD2017
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
#ATD2017
Refine&
Iterate

10. Questions ?
Comments !
Thank You!
#ATD2017