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Programmatic 2.0
Optimization for the Next Generation of
Digital Advertising
VP, Enterprise
Joe Luchs
1994
The Genesis of Digital Advertising
44% CTR!
2000
Ad Networks Take Shape
2007
The Advent of Programmatic
2013
Mobile Breaks $10B
2016
Video Breaks $10B
2016 2017 2018 2019 2020
$25.91
$36.31
$47.37
$57.35
$68.87
+47.1%
+40.2%
+30.5%
+21.1%
+20.1%
“Programmatic is Eating the World”
Today
Video Audio Display Mobile
Digital OOH CTV / OTT Linear Native
And It’s Only Getting More Complex
Optimization:
The Key to Success in the
New Era of Programmatic
op·ti·mi·za·tion
/ˌäptəməˈzāSHən,ˌäptəˌmīˈzāSHən/
noun
“Finding an alternative with the most cost
effective or highest achievable performance
under the given constraints, by maximizing
desired factors and minimizing undesired ones.”
So Why is Optimization
So Important?
Business Outcomes > Proxy Metrics
Incrementality
ROAS
The Value of Optimization
1
2
3
1
Outcomes > Proxies
Optimize Towards True Goals
CTR / VCR
Viewability/
Time-in-view
CPA / CPI
ROAS / LTV / OFFLINE
INCREMENTALITY
2
Drive Incremental Performance
Don’t Pay For Organic Actions
A B
3
ROAS
Show Me the Money
=
Precision Results
The Way Forward:
A New Approach to Optimization
The Optimization Landscape
Standard
Strategies
Shared optimization
algorithms that are
great for upper-funnel
The Optimization Landscape
Standard
Strategies
Bid
Modifiers
Adjust bids against
any RTB input to
drive results
Shared optimization
algorithms that are
great for upper-funnel
Standard
Strategies
Get all the features
of a traditional DSP
on Day 1
Bid
Modifiers
Adjust bids against
any RTB input to
drive results
Bring Your Own
Algorithm
Upload multivariate
models directly to
the bidder
The Optimization Landscape
Nothing Exists in a Vacuum
The Importance of Multivariate Modeling
Key Factors that Power Optimization
The who, the where, the when, and the $$$
User
Data
T H E W H O
How valuable are
your customers?
Inventory
Factors
T H E W H E R E
How valuable is
the inventory?
Time
Decay
T H E W H E N
How long
has it been?
Price
Data
T H E $ $ $
How much is every
impression worth?
User Classification:
"Good"
Bidding Strategy:
Bid always
Users as Segments
User Classification:
"Bad"
Bidding Strategy:
Bid never
Users as Scores
User Classification:
Score 1.67 for
offer ABC
Bidding Strategy:
Increase bid
by 67%
User Classification:
Score 0.21 for
offer ABC
Bidding Strategy:
Decrease bid
by 79%
VS.
Platform Exchange domain value
iOS Rubicon nytimes.com 1.50
iOS Index cnn.com 2.50
Android Pubmatic cnn.co.uk 3.50
... ... ...
Android AdX axios.com 4.50
Multivariate Inventory Factors
Set bid prices based on a specific, verified inventory source
Time Matters!
Adjust your bid price based on engagement recency
Visited 5 minutes ago
Increase
Bid Price by
48%
=
Time Decay Bidding StrategyUser
Visited 2 days ago
Decrease
Bid Price by
23%
=
Real World Example
3.1 X
User is worth
average.
A user with 3 past purchases
just put $150 worth of goods in
their shopping cart
2.4 X
Recency is worth
average.
This same user appears
in a programmatic
auction 7 minutes later
1.1X
Site/Exchange/OS
combo is worth
average.
They appear on a low quality
site, in an urban geolocation,
on an iOS device
0.062%
Likelihood of
for conversion.
Based on historical data, a
$6.24 bid is warranted.
Auction-Level
Data
First-Party
Data
Real-World
Insights
● Wins
● Bids
● Conversions
Collect & Model Data
Combine data sets and build
multivariate models to predict
optimal bid price
Traffic Campaigns
Get results
Upload Model
Upload your
model
Create a
Feedback
Loop
Programmatic is More Complex Than Ever
Great Data and Optimization is Key
Flexible Tech Can Help You Win
Key Takeaways
1
2
3
Thank You!

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Programmatic 2.0 - Optimization for Next Generation of Digital Advertising

Notas do Editor

  1. Welcome to Tahoe everyone. I’m excited to be kicking off our content this week with a presentation on prgorammatic 2.0 and optimization for the next generation of digital advertising. Worth noting that I’m the opening act for Evan from T-Mobile who will be covering AdTech 2.0, so make sure you stick around for the headliner next.
  2. My name is Joe Luchs and I lead the enterprise team over at Beeswax, working directly with marketers that want to maximize their transparency and control over their programmatic advertising. While transparency and control have become buzzwords in the industry, Beeswax specifically focus on replicating the functionality of owning your own tech stack, which ushers in many new possibilites for those that want true ownership without having to build from scratch. Now before we dive into our topic for today, optimization in the programmatic 2.0 world, it’s worth a quick look back at the evolution of adtech.
  3. In 1994 the first digital display ad was served by AT&T on hotwired.com. Today this would likely be considered clickbait, but back in the day, all was fair game. Anyone know what the CTR was? If you guessed 44%, you’re spot on. You’d also be correct in estimating that this is about 440x the current average industry CTR.
  4. As digital advertising grew, ad networks came into the picture to aggregate inventory and sell it to agencies and marketers and help them scale.
  5. However, greater efficiencies could be gained through an auction model, and thus the advent of programmatic. Programmatic took off and a whole ecosystem of DSP, SSP’s, data platforms, etc… launched in the next 5 years.
  6. In 2013 we finally hit the year of mobile after more than one false start. Now mobile makes up over half of digital ad spend.
  7. In 2016, video finally broke 10B, and now makes up about a quarter of digital spend, and is rapidly growing.
  8. And backing out to the bigger picture, programmatic is eating the world. By the end of 2020, over 90% of digital ads will be transacted programmatically, with global spend approaching $150B.
  9. And the world is only getting more complex. With 8 major formats and many more sub-formats, programmatic is evolving at a rapid pace, and the buying technology is racing to keep up. SO why the history lesson? Well the reality is that most major platforms today were built for programmatic 1.0. Trying to retrofit their tech into the modern programmatic ecosystem is hard. And one of the hardest parts about it is optimization.
  10. We at Beeswax believe that in the massive, complex, omni-channel modern marketing ecosystem, having the right optimization strategy is the key to success.
  11. So let’s define optimization
  12. Well let’s start with the foundation that 95% of programmatic stacks are the same. Features like exchange integrations, budgeting, frequency capping, and so forth are commodities. So how does one differentiate themselves. 1) Data 2) Optimization. Today we’re going to focus on optimization.
  13. A/B Testing Graphic Uber and Pandora Examples Analogy of overpaying for something, or paying for something thats free
  14. Many articles about our challenges Fraud Viewability Hidden Fees Bid caching Data sharing Can be distilled into a broader theme