Group presentation for Big Data and Analytics class on the Hopper airline booking and prediction app. Goal was to underline what they were doing and create a live discussion on other use-cases for similar technology.

1. Hopper
Amanda Back I Sara Betancur I Jorge Campos I Saad Haider | Iku Hirosaki | Grigorios Nikolaou I Mercedes Rodenas
Using Big Data to make this big world,
a little smaller.

2. What is Hopper?
An intelligent and user-friendly Travel App

3. The Model
Data mining Custom machine
learning algorithm
Create effective
farecasting

4. So what does that look like?
Graph 1

5. The main 3 variables in consideration
When? Where? How far in
advance?

6. When you are going
Graph 2

7. When and Where you are going
Graph 3

8. When, Where, and How far
in advance?
Graph 4

9. Algorithms in use
Ripple
Down
Rule
Learner
Logistic
Regression
Linear
SVM
70%
Accuracy
95%
Accuracy
Hopper’s
Algorithm
Source: http://cs229.stanford.edu/proj2012/Papadakis-PredictingAirfarePrices.pdf

10. The Value of Using the Model
For customers For Hopper

11. How could we improve Hopper?
Feature
improvements
Destinations
you might also
like...
Hawaii
Venice
Customer Behavior mapping and
targeted marketing

12. Who else can benefit from using the same model?

14. Conclusion
Data has an overwhelming effect on our everyday actions, as individuals and businesses.
With the right business-thinking and marketing,
Big Data can make this big world, a little smaller.

15. Sources
Surry, Patrick. (2015). How the bunny saves you money. Retrieved from:
http://www.hopper.com/research/bunny-saves-money/
Papadakis, Manolis. (2012) Predicting Airfare Prices. Retrieved from:
http://cs229.stanford.edu/proj2012/Papadakis-PredictingAirfarePrices.pdf