Deep dive to optimized online marketing in Facebook. Explaining both current optimization features in Facebook as well as optimization built by Smartly.io on top of Facebook. Metrics Monday, 2015-11-02

1. Multi Armed Bandits
and
Optimized Online Marketing
2015-11-02 Metrics Monday
Markus Ojala
Chief Data Scientist, PhD
Twitter: @MarkusOjala

2. Data
Scientist
(n.):
Person
who
is
better
at
statistics
than
any
software
engineer
and
better
at
software
engineering
than
any
statistician.
@josh_wills

3. • Native
targeting
screenshot
Native
targeting

4. Look-a-like

5. CPC
To get likes, comments, shares or
clicks, go with this option
CPM
Works best with highly targeted
audiences
CPA
Works with mobile app installs, page
likes, offer claims, and link clicks
oCPM
Minimum 25 daily conversions! For
large audiences.
Facebook Bidding 101
nces!
bid = CPC bid * eCTR
the higher the eCTR, the
ikely it is the ad will win
ction
e other hand, if the ad is
ng CPM, then the system
ptimise for the cheapest
ssions rather than clicks.
Cheapest clicks
(high eCTR)
Cheapest
actions
(high eCVR)
Cheapest
impressions
Bid
goal

6. Dynamic
Product Ads
Dynamic
Product Ads

7. Multi-­‐Armed
Bandit

8. Adset Conversions Impressions Conversion
rate
1 848 1 417
764 0.060%
2 723 1 349
349 0.054%
3 60 121 784 0.049%
4 107 270 757 0.040%
5 22 65 200 0.034%
6 45 154 330 0.029%

9. Probability
matching
strategies
Aka:
Thompson
sampling
or
Bayesian
Bandits
The
number
of
pulls
for
a
given
lever
should
match
its
actual
probability
of
being
the
optimal
lever
Sample
from
the
posterior
for
the
mean
of
each
lever
p(λ |
X)
=
Gamma(conv +
prior_conv,
impr +
prior_impr)
Prior,
Posterior,
Binomial,
Poisson,
Beta,
Gamma

10. 2
4
5
6
1
3
adset
6014188452330
6014191135530
6016218626130
6016218626330
6014188451930
6014191135130
conversions
85
72
6
11
2
4
impressions
141776
134935
12178
27076
6520
15433
cr
0.0005995373
0.0005335902
0.0004926917
0.0004062638
0.0003067485
0.0002591849
budget.prop
0.46392
0.13148
0.20482
0.05678
0.11754
0.02546
0
2000
4000
6000
0.0000 0.0005 0.0010 0.0015
cr.sample
density
adset
6014191135530
6014191135130
6014188451930
6014188452330
6016218626130
6016218626330
Scale rate: 0.01
Few
conversions

11. 2
4
5
6
1
3
adset
6014188452330
6014191135530
6016218626130
6016218626330
6014188451930
6014191135130
conversions
848
723
60
107
22
45
impressions
1417764
1349349
121784
270757
65200
154330
cr
0.0005981249
0.0005358139
0.0004926756
0.0003951883
0.0003374233
0.0002915830
budget.prop
0.92730
0.01428
0.05666
0.00000
0.00176
0.00000
0
5000
10000
15000
20000
2e−04 4e−04 6e−04 8e−04
cr.sample
density
adset
6014191135530
6014191135130
6014188451930
6014188452330
6016218626130
6016218626330
Scale rate: 0.1
Some
conversions

12. 2
4
5
6
1
3
adset
6014188452330
6014191135530
6016218626130
6016218626330
6014188451930
6014191135130
conversions
8475
7229
595
1067
219
446
impressions
14177643
13493491
1217837
2707574
652005
1543296
cr
0.0005977721
0.0005357398
0.0004885711
0.0003940797
0.0003358870
0.0002889919
budget.prop
1
0
0
0
0
0
0
20000
40000
60000
3e−04 4e−04 5e−04 6e−04
cr.sample
density
adset
6014191135530
6014191135130
6014188451930
6014188452330
6016218626130
6016218626330
Scale rate: 1
Many
conversions

13. 2
4
5
6
1
3
adset
6014188452330
6014191135530
6016218626130
6016218626330
6014188451930
6014191135130
conversions
76275
65061
5355
9603
1971
4014
impressions
127598787
121441419
10960533
24368166
5868045
13889664
cr
0.0005977721
0.0005357398
0.0004885711
0.0003940797
0.0003358870
0.0002889919
budget.prop
1
0
0
0
0
0
0
50000
100000
150000
200000
3e−04 4e−04 5e−04 6e−04
cr.sample
density
adset
6014191135530
6014191135130
6014188451930
6014188452330
6016218626130
6016218626330
Scale rate: 9A
lot
of
conversions

14. More
dimensions
Conversion
price,
Revenue,
Profit
Budget
change
limits
Control
only
on
budget
level
Time
variation
Optimization
goal
Multilevel
modelling

17. • Roadmap

18. R
vs
Python
OpenCPU Pandas,
Flask

19. We serve the 100+ most
advanced performance
marketers in the world
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Track
Are
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http://fasttrack.herokuapp.com

20. Thank you.
Markus.Ojala@smartly.io
Twitter: @MarkusOjala