This document discusses using event prospecting to better target users. It begins with introducing the speaker and their background. It then discusses the goal of studying events to influence desired user behaviors. It provides examples of how Facebook has used event prospecting. The document outlines methods for event prospecting including defining user segments, gathering data, and correlation, inflection point, and decision tree analysis. It discusses applications like targeting quality users, activating power users, retaining users, making more money, and preventing undesirable behaviors. It also covers challenges and lessons learned from applying event prospecting via user acquisition.

1. Custo m Eve nts Pro spe cting
W i n n i n g w i t h T a r g e t i n g i n t h e
D a t a G o l d R u s h

2. • Intro
• Methods
• Applications
• Challenges
A G E N D A

3. I N T R O

4. • Senior marketer (8 years ASO, PPC, Paid Social)
• Author/Speaker (300+ blog posts, Advanced ASO Book, AGS & ASO Conferences)
• True Data Nerd
G A B E K W A K Y I
C E O & C O - F O U N D E R , I N C I P I A & X Y L A
UA, ASO, Creative,
Analyticsagency
AdvancedASO
conference
MobileanalyticsSaaS platform

5. To influence the future
W H AT I S T H E G O A L O F
S T U D Y I N G E V E N T S ?

6. F A C E B O O K E X A M P L E
Example #1 of Facebook
using event prospecting
on the path to $500 billion
valuation

7. M E T H O D S

8. • Define the user behavior you want to influence to segment users
• Boolean (user is a power user/not)
• Segments (minnows / dolphins / whales in revenue generation)
• Model-based (LTV)
• Cohort users to remove time influence
• Gather the data
• User ID
• Acquisition date
• Event timestamp
• Revenue
P R E P A R AT I O N

9. S T E P 1 : C O R R E L AT I O N /
R E G R E S S I O N
Goal: identify which
events are most
correlated with
desired behavior
Raise confidence in
which event most
influences the desired
outcome (e.g. app
opens)

10. S T E P 2 : I N F L E C T I O N P O I N T
Goal: use the 1st derivative
of the smoothed line to
identify the point of
diminishing returns (i.e.
maximum value) within a
single event
Raise confidence in how
many instances of that
event most influences the
desired outcome (e.g. 34
app opens)

11. S T E P 3 : D E C I S I O N T R E E /
R A N D O M F O R E S T
Goal: identify which
combination of
events is correlated
with the desired
behavior
Raise confidence
that other events
are not
influencing the
desired outcome
(e.g. 22 app opens
AND 3 key actions
per app open)

12. A P P L I C AT I O N S

13. 100% of users
50% of users
5% of users
.5% of
users
TA R G E T I N G Q U A L I T Y U S E R S
Goal: balance desired
behavior confidence vs
feasibility/economy of
reach

14. 100% of users
50% of users
5% of users
.5% of
users
TA R G E T I N G Q U A L I T Y U S E R S
Goal: prospect events
to use in custom
event optimized
advertising
campaigns

15. A C T I V AT I N G P O W E R U S E R S
Source: https://andrewchen.co/power-user-curve/
Goal: identify which behaviors predict that a user will
become a power user
What events
are missing in
this cohort?
What events are
present in this
cohort?

16. R E TA I N I N G U S E R S V I A K E Y B E H A V I O R S
Example #2 of Facebook
using event prospecting
on the path to $500 billion
valuation

17. R E TA I N I N G U S E R S V I A K E Y B E H A V I O R S

18. M A K I N G M O R E M O N E Y V I A K E Y F E AT U R E S
Example #3 of Facebook
using event prospecting
on the path to $500 billion
valuation

19. P R E V E N T I N G U N D E S I R A B L E B E H A V I O R S
Goal: Prospect events
with a negative impact
on your bottom line
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
0 1 2 3 4 5 6 7 8 9 10 10+ 100+ 300+
User profit vs churn likelihood by hours of content
cosumed per month
company profit per user Churn Likelihood

20. P R E D I C T I N G P R O F I T S
Goal: Prospect events
which predict users will
ultimately convert from
trial to subscription

21. • Providing inputs
• Data Locker
• Master API
• Protect 360
• People-based
attribution
• Deploying outputs
• Ad channels
(campaign targets,
exclusions,
lookalikes,
remarketing)
H O W A P P S F LY E R F I T S

22. E V E N T P R O S P E C T I N G
A P P L I C AT I O N I D E A S
Event correlation:
• Use in-app messaging to
activate on key event in first
session
• Prime users with ad creative
to activate key event
• Use onboarding flow to
informusers thatthey can
unlock new value after
activating a key event
Inflection point:
• Use push notification to
driveusers to inflection
count
• Use gameification mechanics
to drive users to inflection
count
• Use tooltip/onboarding to
driveusers to inflection
count
• Use inflection of average
purchasepricevs LTV to
optimize pricing
Decision tree:
• Split test event mix
lookalikes
• Targetmix event-optimized
campaigns
• Set rewarded ad/video
payoutto the right mix
• Offer freebies/incentives to
reach the right mix

23. 1. Overlap of events can cause
cannibalization (assessed based
on depth)
2. Events too deep in the funnel
(<1%) do not work well
3. Events located within the first 3
days work best
4. UAC > Facebook for custom
events
5. Optimizing for custom events can
work, at scale
A P P LY I N G E V E N T
P R O S P E C T I N G V I A U A
L E S S O N S L E A R N E D
0.844
22.806
3.782
12.488
4.501
0.000
5.000
10.000
15.000
20.000
25.000
Event 1 Event 2 Event 3 Event 4 Event 5
Averageoccurrencein days after install
Event 1: good
(low
confidence?)
Event 2: too
deep
Event 3:
nearly right
Event 5: too
close to
event 3
Event 4: too
deep

24. • Ensure that events & desired outcomes are
independent / not correlated (e.g. purchases and
ARPU)
• Selecting the right model (e.g. normal/not data
distribution OR monetization model)
• Cost to leverage the data (product vs advertising vs
push notification)
• Transferring findings from the lab into the real
world (Hawthorne effect)
C H A L L E N G E S

25. T H A N K Y O U
L E T ’ S C O N N E C T
P R O J E C T S @ I N C I P I A . C O
I N C I P I A . C O
@ I N C I P I A
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