Data Scientists Need not apply

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Data scientists need not apply: How anyone can do game analysis Casual Connect, November 2014 @allisonbilas | [email protected]

Transcript of Data Scientists Need not apply

Data scientists need not apply:How anyone can do game analysis

Casual Connect, November 2014

@allisonbilas | [email protected]

Using data to understand your players and monetizers.

Analyst

Jr. Producer Producer Monetization Mgr.

Developer Senior PM

Descriptive Exploratory Inferential Predictive Causal

Quantitatively describing data

Looking for previously unknown

relationships in data

Testing theories with a sample of

data

Analyzing current events to predict

future events

Measuring what happens to one

variable when you change another

Distribution; 5-number summary;

Before/after

Directionality; Visualizations

Regression models; Chi squared

Modeling, machine learning, data

miningA/B testing

OBSERVE EXPERIMENT

Descriptive Exploratory Inferential Predictive Causal

Quantitatively describing data

Looking for previously unknown

relationships in data

Testing theories with a sample of

data

Analyzing current events to predict

future events

Measuring what happens to one

variable when you change another

Distribution; 5-number summary;

Before/after

Directionality; Visualizations

Regression models; Chi squared

Modeling, machine learning, data

miningA/B testing

“EASY”

‣ Quantitatively describing data

‣ Distribution of data; 5-number summary; Outliers

Score Percentiles by Boost Used

0

28

56

84

112

140

10. 25. Median 75. 90. 99.

Valentine WinterPrism RubyBlaze BurstStone No Boost

Descriptive

‣ Looking for previously unknown relationships in data

‣ Visualizations are key component

ExploratoryMonetizers by Amount Spent per Customer

0

1,000

2,000

3,000

4,000

$0 - $5 $5 -$10 $10 - $25 $25 - $60 $60 - $280 $280 - $2975

Total Bookings by Amount Spent per Customer

$0

$25,000

$50,000

$75,000

$100,000

$0 - $5 $5 -$10 $10 - $25 $25 - $60 $60 - $280 $280 - $2975

4% 6%

16%

22%

35%

17%

34%

18%24%

15%

9%

1%

‣ Measuring uncertainty in analysis

‣ Linear regression; Chi squaredInferential

Three Big Questions

INSTALLS How many people have installed my

game?

DAU How many people are

playing my game?

REVENUE How much money is my game generating?

Acquisition Engagement Monetization

Really good analysis…

Revenue declined by $2K (-5%) week-over-week after the re-engagement campaign ended.

This was caused by a 3% decline in DAU, which in turn reduced the number of monetizers by 3%.

Those that did spend continued to spend at the same ARPPU of $7.29.

Reporting Analysis

DAU = 1.25M

Revenue = $41.4K

ARPPU = $7.29

Conversion = 0.45%

Revenue declined by $2K (-5%) week-over-week after the re-engagement campaign ended.

This was caused by a 3% decline in DAU, which in turn reduced the number of monetizers by 3%.

Those that did spend continued to spend at the same ARPPU of $7.29.

Reporting Analysis

DAU = 1.25M

Revenue = $41.4K

ARPPU = $7.29

Conversion = 0.45%

Revenue declined by $2K (-5%) week-over-week after the re-engagement campaign ended.

This was caused by a 3% decline in DAU, which in turn reduced the number of monetizers by 3%.

Those that did spend continued to spend at the same ARPPU of $7.29.

Reporting Analysis

DAU = 1.25M

Revenue = $41.4K

ARPPU = $7.29

Conversion = 0.45%

Revenue declined by $2K (-5%) week-over-week after the re-engagement campaign ended.

This was caused by a 3% decline in DAU, which in turn reduced the number of monetizers by 3%.

Those that did spend continued to spend at the same ARPPU of $7.29.

Reporting Analysis

DAU = 1.25M

Revenue = $41.4K

ARPPU = $7.29

Conversion = 0.45%

DAU = 1.25M

Revenue = $41.4K

ARPPU = $7.29

Conversion = 0.45%

Revenue declined by $2K (-5%) week-over-week after the re-engagement campaign ended.

This was caused by a 3% decline in DAU, which in turn reduced the number of monetizers by 3%.

Those that did spend continued to spend at the same ARPPU of $7.29.

Reporting Analysis

‣ Continue to use push notifications to re-engage users and support DAU

‣ Prioritize dev work for daily prizes to increase return rates

‣ Consider creating a high priced gem package to increase ARPPU

Recommendations

You do see, you just don’t observe.

Sherlock H.

Allison Bilas, VP of Product

@allisonbilas

[email protected]

Additional Reading: https://bitly.com/bundles/sparklingallison/

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