This document provides an overview of bringing a company's programmatic advertising efforts in-house. It introduces the author and their experience, outlines the reasons for bringing programmatic in-house including greater control and lower costs. It describes how the in-house team was structured initially and how it has grown, and compares in-house efforts to working with a managed service partner. It also highlights some programmatic creative innovations the team has implemented, the importance of bid modeling, and what they hope to achieve in the future including more automation.

1. Bringing Programmatic
In-House
Jonathan Lau
Programmatic Lead

2. | 2
Summary
Who am I?
Why In-house?
Team Structure
In-house vs Managed
Programmatic Creative Innovations
Bid Models
What’s Next?

3. Who am I?

4. | 4
7-years in performance marketing
4-years leading teams
Father of two
Husband of one
Enjoys lifting heavy things
Quick Intro of Myself

5. | 5
Why
In-house?

6. | 6
We do not want to be chauffeured. We want to learn to
drive ourselves.
● Belief that Programmatic is an enormous growth
opportunity
● Lower marketing cost over time
● We want to diversify from black box, platform
partners
● In-house and managed partners are not mutually
exclusive
Investing in Our Future

7. | 7
Think and answer each of the following:
● What are your goals and how much time will it take
to achieve them (It’s going to take time)
● Monetary Investment (Initial sunk costs)
● Proper resource management
● Performance expectations (No immediate results)
● DON’T DO TOO MUCH!!!
Setting clear expectations

8. Team
Structure

9. | 9
Who We Started With
Dan Morris
(Mad Scientist)
● Cooks up new
ideas, creative
concepts
● Programmatic
strategist
Alexa Wieczorek
(Ops Ninja)
● Campaign
management
● Programmatic
strategist
Jon Lau
(The Dude)
● Team Lead
● Resource
scavenger
● Budget/Goal
Management

10. | 10
Our Current Team (I wish we had this when we started)
Dan Morris
(Mad Scientist)
● Cooks up new ideas,
creative concepts
● Programmatic strategist
Alexa Wieczorek
(Ops Ninja)
● Campaign management
● Programmatic strategist
Jon Lau
(The Dude)
● Team Lead
● Resource scavenger
● Overhead
Nick Olmanson
(Data Scientist)
● Focus on training bid
algo
● Build data pipeline for
our bid engine
Web Developer/Coder
● Build dynamic ad concepts
● Debug and deploy
iterations
Lauren Skarup
(Baby Ops Ninja)
● Second Ops person as we
scale our channel

11. | 11
In-house vs
Managed

12. | 12
Amazing Partner
Room for customization
Constant communication
and feedback loop
Provided crucial insights
when we first started
Scale as you grow
Working with a White-Label Bidder

13. | 13
Managed DSP CPM $4.76
In House DSP CPM $15.58
● Significantly lower CPM, but questionable inventory
● In-house efforts drove higher user quality and coming in with a lower CPA
Over 3x Lower CPM
In-house vs Managed DSP CPMs

14. Programmatic
Creative
Innovations

15. | 15
Dynamic Ads
Scratch
Card
320x50
Expandable
Drive higher
intent
Drive higher
quality
Create a
different user
ad experience
Multi-Sport
Live Lines

16. | 16
Funnel Optimizations
Current
Refreshed
Default
Prelim data
shows
+61% CTI
Conversion
*
Refreshed
Slots

17. | 17
Bid Models

18. | 18
What We Learned
Do not overcomplicate your approach when building
your bid model.
● Start with something simple and layer features
over time
● Training the bid model takes time and money to
achieve significant learning
● Capitalize on your learnings and iterate
accordingly (Even if it means reverting backwards)
● Does not replace a human touch

19. What’s Next

20. | 20
Our Wishlist for the Future
● Automation
● User LAL Modeling
● Dynamic Ad creation engine
● Retargeting

21. Questions?