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Multi Armed Banditsand
Optimized Online Marketing2015-11-02 Metrics Monday
Markus OjalaChief Data Scientist, PhDTwitter: @MarkusOjala
Data Scientist (n.):
Person who is better at statistics than any software engineer and better at software engineering than any statistician.
@josh_wills
• Native targeting screenshot
Nativetargeting
Look-a-like
CPCTo get likes, comments, shares or clicks, go with this option
CPMWorks best with highly targeted audiences
CPAWorks with mobile app installs, page likes, offer claims, and link clicks
oCPMMinimum 25 daily conversions! For large audiences.
Facebook Bidding 101
Different bid types might mean different audiences!
• eCPM bid = CPC bid * eCTR • Thus, the higher the eCTR, the
more likely it is the ad will win the auction
• On the other hand, if the ad is bidding CPM, then the system will optimise for the cheapest impressions rather than clicks.
Cheapest clicks (high eCTR)
Cheapest actions (high eCVR)
Cheapest impressions
Bid goal
DynamicProduct Ads
DynamicProduct Ads
Multi-‐Armed Bandit
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%
Probability matching strategiesAka: 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
2
4
5
6
1
3
adset601418845233060141911355306016218626130601621862633060141884519306014191135130
conversions8572 611 2 4
impressions141776134935 12178 27076 6520 15433
cr0.00059953730.00053359020.00049269170.00040626380.00030674850.0002591849
budget.prop0.463920.131480.204820.056780.117540.02546
0
2000
4000
6000
0.0000 0.0005 0.0010 0.0015cr.sample
dens
ity
adset601419113553060141911351306014188451930601418845233060162186261306016218626330
Scale rate: 0.01Few conversions
2
4
5
6
1
3
adset601418845233060141911355306016218626130601621862633060141884519306014191135130
conversions848723 60107 22 45
impressions14177641349349 121784 270757 65200 154330
cr0.00059812490.00053581390.00049267560.00039518830.00033742330.0002915830
budget.prop0.927300.014280.056660.000000.001760.00000
0
5000
10000
15000
20000
2e−04 4e−04 6e−04 8e−04cr.sample
dens
ity
adset601419113553060141911351306014188451930601418845233060162186261306016218626330
Scale rate: 0.1Some conversions
2
4
5
6
1
3
adset601418845233060141911355306016218626130601621862633060141884519306014191135130
conversions84757229 5951067 219 446
impressions1417764313493491 1217837 2707574 652005 1543296
cr0.00059777210.00053573980.00048857110.00039407970.00033588700.0002889919
budget.prop100000
0
20000
40000
60000
3e−04 4e−04 5e−04 6e−04cr.sample
dens
ity
adset601419113553060141911351306014188451930601418845233060162186261306016218626330
Scale rate: 1Many conversions
2
4
5
6
1
3
adset601418845233060141911355306016218626130601621862633060141884519306014191135130
conversions7627565061 5355 9603 1971 4014
impressions127598787121441419 10960533 24368166 5868045 13889664
cr0.00059777210.00053573980.00048857110.00039407970.00033588700.0002889919
budget.prop100000
0
50000
100000
150000
200000
3e−04 4e−04 5e−04 6e−04cr.sample
dens
ity
adset601419113553060141911351306014188451930601418845233060162186261306016218626330
Scale rate: 9A lot of conversions
More dimensions
Conversion price, Revenue, ProfitBudget change limits
Control only on budget levelTime variation
Optimization goalMultilevel modelling
• Roadmap
R vs Python
OpenCPU Pandas, Flask
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