2. Who Am I
Software Engineer and Game Developer for 5 years.
Developed Dragon Cubes along with other team members
Developed Bubble Cubes
Currently developing Casino Slots
3. Who Am I
Also currently taking Masters of Science in Computer Science in DLSU.
5. Machine Learning
Field of study that gives the computer the ability to learn and
recognize patterns.
Image R G B Name
A 255 255 255 Animal
B 255 0 0 Animal
C 132 122 230 Plant
D 89 134 200 Plant
Training Dataset Machine Learning
Algorithm Prediction Model/s
Animal? Plant?
6. Supervised Learning
The class to predict is explicitly
given in the dataset
TRAINING
DATASET
Image R G B Name
A 255 255 255 Animal
B 255 0 0 Animal
C 132 122 230 Plant
D 89 134 200 Plant
7. Supervised Learning
Prediction model attempts to predict the missing class value
TRAINING
DATASET
NEW/UNSEEN
DATASET
Image R G B Name
A 255 255 255 Animal
B 255 0 0 Animal
C 132 122 230 Plant
D 89 134 200 Plant
Image R G B Name
E 0 0 255 ??
F 255 0 0 ??
G 0 122 125 ??
H 98 7 2 ??
8. Data Mining
• Extract patterns or provide insights from a
complex dataset.
• Borrows techniques from machine learning and
statistics.
9. Data Mining
• Patterns should be:
• Non-trivial (not normally extracted in an SQL
statement)
• Unknown
• Unexpected
• Potentially useful
• Actionable
10. Why Data Mining?
Drowning in data but starved for knowledge
Unstructured data, or knowledge is deeply buried.
11. Predicting Daily Active Users for Match-3
Mobile Games
Application of supervised learning for Dragon Cubes and Jungle Cubes
17. Dataset Overview
• Two match-3 games
• JNC generating
revenue
• DNC does not
• Both games only differ in
game mechanics.
18. General Methodology of Data Mining*
*How I performed data mining on our data
*For supervised learning. Unsupervised learning use subjective evaluation to determine reliability of model.
Dataset
Feature Selection
Refined
Dataset
Machine Learning
Prediction Models
Model A Model B
Model C Model D
Unseen
Data
Predicted
Result
Accuracy
Measure
19. Features in Dataset
Users are reached via advertising channels
MKTExpenses This is the total amount of marketing expenses, in USD,
spent to advertise the game.
A high marketing expense means more advertising
channels have been used to target more potential
users to install the game.
20. Advertising amount per user per
country*
● Users are reached via advertising channels.
*Market insight taken from Chartboost: http://tinyurl.com/charboost
21. Features in Dataset
How many users discovered our app on a given date?
Install Date Calendar date of installation.
Cohort Size Refers to the total amount of users who have
installed the application on the given install date.
Session Count Refers to the total amount of play sessions on a
given install date.
22. Features in Dataset
How long do players play the game?
AvgSessionSeconds The arithmetic mean of the total amount of time
users spend in the game
MedianSessionSeconds Session length value where half of the sessions are
longer, and half are shorter.
25. Features in Dataset
How many users are engaged?
ActiveUsers This refers to the total amount of unique users who
spent considerable time in the game given a certain
date.
ActiveUsersDay7 This is similar to the ActiveUsers variable but offset
7 days after the install date. This is the variable to
be predicted.
26. Features in Dataset
Screen that triggers the
events
LevelPlayedEvents
LevelSuccessEvents
LevelFailedEvents
30. Correlation Analysis
Measure relationship of two variables.
As X grows, how fast Y grows/declines?
Range (-1.0 to +1.0)
0.0 means no relationship at all.
+1.0 strong positive relationship
-1.0 strong negative relationship
51. Interpretations
Using results from M5Base.
*More details available at: http://www.dlsu.edu.ph/conferences/dlsu-research-congress-proceedings/2016/GRC/GRC-HCT-I-001.pdf
54. Interpretations
JNC and DNC have almost the same total advertising expense. But
DNC did not gain enough daily active users.
Positive correlation summary JNC DAU-Day7 DNC DAU-Day7
MKTExpenses High Low
SessionCount High Low
SessionLength High Low
55. Interpretations
Based from our study, we propose a finding that MKTExpenses gets high
correlation with DAU-Day7 once the game has enough enjoyable content
to keep users engaged.
Ensure high
session
length
Promote
replayability
SessionLength
affects
SessionCount
affects
Satisfies
business
requirements?
Increase
advertising
campaigns
MKTExpenses
affects
DAU
DAU-Day7
influences
56. Conclusion
Did our study correctly predicted the fate of JNC and DNC?
Yes. Jungle Cubes has gained over 1M downloads as
of October 2016 and is still profitable.
Dragon Cubes was pulled out of the market last
September 2016.
57. We thank you Jakob Lykkegaard Pedersen and
Thomas Andreasen for allowing us to use the
dataset for Jungle Cubes and Dragon Cubes. We
would also like to give thanks to Suhana Chooli,
the marketing manager of Playlab Inc., which
provided the details about the marketing
expenses.
Thank you for listening!