Big Data For the Little PeopleGuy TomerChief Marketing and Business Development OfficerTabTale

2

About Me – Knowing the Audience

9 YO6 YO XX YO

Coming Soon

3

About TabTale• Top 10 Mobile Game publisher WW (AppAnnie)

• Reached 1B downloads in March, and counting

4

Developing your own system is complex, start by looking for

(COPPA compliant) existing solutions

Existing Tools – Google Play A/B TestingThe difference in some cases is huge (40%)!

Even short description test can make a difference

Google Play A/B Testing – Short Description

Existing Tools – Flurry Limited Version

Tag your apps as directed at Children and still get most of the great features.

Price change effectfrom $4.99 to $7.99in our 3D care lineMoving average of revenue perdownloadSignificant increase

Existing Tools – Price Testing

9

Building Your Own COPPA - compliant BI &

Analytics System – If; What; How

High Level Kids Privacy and Analytics

COPPA - Do Not Collect and Track!But….• Aggregated data collected anonymously is not a

problem (e.g. groups A/B testing)• Collection of PII (personal identifier information)

for the support for of internal operations including app analytics is allowed!

Aggregate non Personal Data from Partners• GEO level data• Can extrapolate usage

from ad impressions• Can leverage session

data from some of the providers

• Apple & Google provide most high level data

• Can be done with AppAnnie or similar.

Stores

Ad Networks

Aggregated BI

Others

High Level Guidelines for Collecting User Data

• Collect only the ID (e.g. IDFA/Android ID)• Use for support for internal operations only. Never

share!• Mind Security • Be able to delete any user record• Retain the data only for reasonable time• Be clear in your privacy policy

13

Tech Tip – Log only Encrypted PII• Full data deletion of a user upon request• SecurityThe trick: Don’t save records with the PII use encrypted PII PII Table

PII Encrypted PII

Delete mydaughter’sdata now!

14

Usage And Operations Analysis Examples

Findings in Kids apps• 73% of the purchases occur in the first 24 hours

• 60% of the purchases in the 1st session85% of the purchases within the 1st 3 sessions

• Users purchase later in apps built chronologically

• 50% of the users purchase after 15 min play

 

Usage Analysis – Purchase Time

Usage time and In-App purchases were not affected (changes are  statistically insignificant)Rewarded Videos added 12-14% to total revenue

Usage Analysis – Use Rewarded Videos?

Find where the kids spend most of their time within your app and spend your developers’ time there as well.

Usage Analysis – Scene Performance

Our dress-up scenes include tons of categories and items that cost money, time and app weight.What’s the optimal number of categories?What’s the optimal number of items?

Usage Analysis – Optimizing Dress Up Scenes

Adding more than the optimum does not increase usage time or revenues:5 categories 8 items per category

Usage Analysis – Optimizing Dress Up Scenes

Time based waitGrinding based locked – play other scene

 

Usage Analysis – Grinding Vs. Time Based Lock

Grinding works better in terms of number of scene entries

Usage Analysis – Grinding Vs. Time Based Lock

Popup overlay OR Full screen

 

Usage Analysis – Paint Scene UX

Separate scenes worked almost 2X better in terms of usage duration in multiple apps

Usage Analysis – Paint Scene UX Results

24

Questions?

Don’t Mess With Me!