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Budget Allocation in
Online Marketing
Markus Ojala
PhD, Chief Data Scientist @ Smartly.io
April, 2018
1 billion spend
Managed yearly
Smartly.io
Facebook &
Instagram Partner
Online Marketing
Right creative To right
audience
At the right
time
What is the goal in online marketing?
Website visit
View content
Add to cart
Purchase
Usual conversion rate for ecom 1-2%
Ad/website funnel
Ad
General campaign dimensions in online marketing
General campaign dimensions in online marketing
1. Audience
General campaign dimensions in online marketing
General campaign dimensions in online marketing
2. Creative
General campaign dimensions in online marketing
General campaign dimensions in online marketing
3. Bidding
General campaign dimensions in online marketing
General campaign dimensions in online marketing
4. Budget
Budget Allocation
Allocating Budget
Modeling results per spend
Multi-Armed
Bandit
Bayesian Bandits / Thompson sampling
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
All models are wrong,
but some are useful.
Improving performance
Revenue Optimization
Moving from conversions to revenue
ROAS = revenue / cost
= revenue / conversions * conversions / cost
= revenue / conversions * 1 / CPA
ROAS = return on ad spend
CPA = cost per action
Existing model
● Lot of data
● Varies fast
● Big differences
New model
● Little data
● Varies slowly
● Small real differences
● Lot of random variation
Modeling the revenue per purchase
Revenue follows usually a long-tailed distribution, use log-normal
Multilevel
Model
Account
Campaign
Ad set
Results 1
Common case:
ad sets don’t
really differ in
rev / conv
Results 2
Campaigns
differ, ad sets
not
WORK SMARTLY
We’re looking for new Humble Hungry Hunters
to build a world-class product company.
https://www.smartly.io/careers
Markus.Ojala@smartly.io

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Budget Allocation in Online Marketing