EX.1.2. Adobe Portfolio Based Optimation

© 2011 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.

Adobe’s Portfolio Based Optimization


Goal of this presentation

To understand how Adobe is integrated with an advertisers Online Marketing efforts How we track information on the cost side

How we track information on the revenue side

To understand Adobe’s Portfolio Based Optimization How we use all the information for Optimization

The famous Portfolio Theory Approach

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CAPTURING INFORMATION

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The Optimizer loves data!


Capturing Information on the Cost Side

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When someone clicks on an ad…

…they are directed to the Adobe server which captures information regarding the click…(called the Redirect)A cookie is dropped on the user at this time

...they are then directed to the landing page associated with that ad.


Capturing Information on the Revenue Side

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After the Redirect, the user is then directed to the advertisers landing page.

Once the user lands on the advertisers landing page, we can capture as much or as little as the advertiser wants us to. This information is captured by the Conversion Pixel

- Capture page views- Capture click outs to other sites - Capture conversion amounts- ….

The metrics being captured on the advertisers website are called Transaction Properties.

All transaction properties can be reported on. However only the most important transaction properties are part of the Objective for a Portfolio (i.e. these are the properties that we maximize/optimize)


Linking Cost and Revenue

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Search Engine/NetworkCost Side

Advertisers WebsiteRevenue Side

Captured via Click Tracking

(Redirect)

Captured via Conversion

Pixel

Adobe Servers

Adobe tracks the user throughout the funnel: from click to conversion.

The advertiser can define the Objective of their online marketing campaigns (e.g. maximize revenue, maximize email sign ups etc.).

Adobe now has information on keywords/ads (also called Bid Units) that are driving the Objective more than others.

The Technology will start bidding up the bid units that contribute more to the Objective.

* A Bit Unit is defined as the final entity on which we place bids. Definition of Bid Units across various channels are covered in later chapters.


Example

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Keyword Conversions in last 30 days Objective = Revenue Objective = Email Sign ups

Travel to FinlandRevenue = 10Orders = 1Email signups= 9

Cheap TicketsRevenue = 100Orders = 10Email signups = 5

Airfare to FinlandRevenue = 1000Orders = 1Email signups= 1

This keyword will be bid down as its not contributing as much as the other keywords to revenue

This keyword will be bid up since its contributing to revenue. But it wont be bid up as much as the 3rd keyword

This keyword will get the highest bid as it is contributing the maximum to generating revenue

This keyword will be bid up as it is contributing the maximum to generating email sign ups

This keyword will be bid up as it is contributing email sign ups, but not as much as the 1st keyword.

This keyword will be bid down as its not contributing as much to the Objective (email sign ups)

The Optimizer will determine which bid units are good (i.e. lead to the Objective) and bid them up.

If the Objective changes, a keyword that was defined as “good” may no longer be a good one to bid up. A new set of bid units that maximize the new Objective will now be bid up.

Thus with every change we make, the Adobe Technology will have a new set of decisions it needs to make.


Effortless bidding on millions of keywords

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The example of bidding 3 bid units is fairly easy to solve – because there are only 3 bid units!

But when we have thousands of Bid Units* to analyze, with multiple metrics in the Objective, that is when the Adobe Portfolio based Optimization can scale and intelligently compute bids for every Bid Unit.

The Optimizer comes up with a Bid Landscape for every single Bid Unit. This is basically the performance potential for every Bid Unit.

Even if a Bid Unit has not seen a certain position/bid, based on performance at different levels the technology can extrapolate performance at different levels.

* A Bid Unit is defined as the final entity on which we place bids. Definition of Bid Units across various channels are covered in later chapters.


Understanding the Portfolio Theory Approach

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Portfolio Theory Simplified

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Every advertiser has an Objective for their online marketing efforts

When Adobe sets bids, it works on maximizing the Objective that’s set for the Portfolio.

It sets bids for each keyword based on:

1. The historical performance of a bid unit

If a bid unit has performed well in the recent past (given the Portfolio Objective), it will be bid up

2. The opportunity cost of bidding on one bid unit vs. another

There will always be some budget constraint associated with a Portfolio

If we set a high bid on one of the bid units, we are taking away money from the other bid units in the Portfolio.

Given the Objective, the Portfolio Theory Approach will look at all the bid units in a Portfolio and set bids accordingly (not look at each bid unit in isolation)


Rules Based Bidding

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In the example of Rules Based Bidding (i.e. not the Portfolio Theory Approach), the advertiser wants to maximize leads but keep the cost of a new lead below $2

With the rules based approach, every keyword is inspected in isolation and the bids are set.

With this approach, the advertiser gets 25 new advertisers while maintaining a $2 cost per new advertiser


Portfolio Based Approach

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With the Portfolio Theory Approach, models are built for each bid unit. The bidding decisions are made on individual bid units taking into account the effect of that decision on all other bid units.

In this example the technology would actual make the opposite decision to the Rules based approach.

The $2 CPA business goal is still maintained but we have 30 orders with the Portfolio Theory Approach.


Data Collection

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Portfolio based bidding requires some data on bid units in a Portfolio to be able to analyze their performance at different bids and positions. This helps to predict their future performance.

The MORE the historical data points for bid units ….the more accurate the forecasts made by the Adobe Technology…the better the bidding decisions made by the Adobe Technology…the smoother the performance right after Launch

We recommend a small Data Collection period (generally up to 2 weeks) for every new Portfolio before the Optimizer starts setting bids.

After a period of Data Collection, the Portfolio status can then be changed to “Optimized”. (i.e. the Optimizer will set bids for all the bid units in the Portfolio)

This is called the Launch of a Portfolio.
