verticalization as applied to advertising as an enterprise system

Verticalization As Applied To Advertising As An Enterprise System

San Diego, California. Sept 2012. Edward Montes

Digilant is an independent marketing technology company that provides marketers with a platform to support the entire media buy –from planning through execution, measurement and optimization– with ultimate precision and transparency.

Advertising As An Enterprise System

An Enterprise System represents a cross-functional, integrated information system, used by organizations to support business processes and provide an underlying platform for data integration

Generic Systems

• Systems are complex, tend to be comprehensive, tightly integrated software consisting of business process or logic that is hard-coded into the system

• “One Process Fits All”• Options:

1) Reconfigure the system or 2)re-engineer the process to fit the system

• One Process Fits All Approach Destroys Competitive Advantage

Vertical Strategy

• A strategy aimed at minimizing the gap between practiced processes and system embedded processes

• Specialized software for specific verticals where industry-specific processes are embedded into the system from the design stage

• Better Tailoring Products To Practices

Today’s Truisms

• Too Many Choices

• Competition Is Fierce

• Black Box Mentality

• No Material Difference between Targeting and Valuation

• Optimization is the equivalent of winning in a specific attribution model

Simple Methodology

One day attribution:

The process takes one day of clicks /conversions and 45 days of preivous impressions/clicks and marks each event with their corresponding weights according to the attribution models.

The process is then applied for each day with at least 45 previous days of data.

0 0 0 1 0 1 0 1 1 0 Target

I I I C I I I C I C ConvTime

45 days of imp / click Day of

execution

More Methodology

Day of

execution

45 days of imp / click

Time

45 extra day to check if

impression/ click is a zero

Period with full information about target

The first 45 don’t have all the possible events that could have caused the conversion / click, and the

last 45 don’t have the conversions / clicks needed.

Click and Conversion Models: Predictors

A number of target based predictors exist for each model:

Target is computed in previous days of the events selected in the sample aggregating by:

Geo

Url-domain Hierarchy (Url is used if it has enough data, domain is used otherwise)

Two different depths are used to capture short-term and long-term effects:

2 previous days (one predictor for geo and one for url-domain hierarchy)

20 previous days (one predictor for geo and one for url-domain hierarchy)

Time

Day of sample20 days aggregation

2 days

aggregation

Parameter DF Estimate StandardError

WaldChi-Square

Pr > ChiSq StandardizedEstimate

Exp(Est)

Intercept 1 1.1078 0.0506 478.76 <.0001   3.028

W_BROWSER 1 -0.4926 0.0215 525.30 <.0001 -0.1128 0.611

W_GMTGCL2 1 -0.3585 0.0502 50.95 <.0001 -0.0279 0.699

W_UMTGCL2 1 -0.1537 0.0191 64.38 <.0001 -0.0527 0.858

W_UMTGCL20 1 -0.7971 0.0162 2419.47 <.0001 -0.3329 0.451

W_USERLANGUAGE 1 -0.1040 0.0385 7.30 0.0069 -0.0111 0.901

W_VISIBILITY 1 -0.6253 0.0375 278.16 <.0001 -0.0707 0.535

Modelling Results: CPG Click Attribution

Target based predictor by URL-DOMAIN hierarchy for target [TARGET] and depth [DEPTH]

Modelling Results: CPG LCLI Attribution

Parameter DF Estimate StandardError

WaldChi-Square

Pr > ChiSq StandardizedEstimate

Exp(Est)

Intercept 1 1.8535 0.0542 1168.69 <.0001   6.382

W_BROWSER 1 -0.4581 0.0271 285.51 <.0001 -0.0801 0.632

W_CREATIVECATEGORY 1 -0.8896 0.0485 336.64 <.0001 -0.0734 0.411

W_GMTGCOLCLIWOR2 1 -0.7736 0.0221 1224.56 <.0001 -0.2827 0.461

W_GMTGCOLCLIWOR20 1 -0.1514 0.0244 38.63 <.0001 -0.0468 0.859

W_GOOGLEMAINVERTICAL 1 -0.2587 0.0506 26.19 <.0001 -0.0258 0.772

W_UMTGCOLCLIWOR2 1 -0.0458 0.0240 3.65 0.0561 -0.0103 0.955

W_UMTGCOLCLIWOR20 1 -0.7822 0.0182 1850.60 <.0001 -0.2404 0.457

W_VISIBILITY 1 -0.2508 0.0568 19.49 <.0001 -0.0202 0.778

20 Day surfing behavior still strongest predictor but 2 Day GEO importance jumps dramatically

Targeting vs. Valuation

• Understanding the most important predictors of performance allows you to target to desired outcome

• Understanding most important predictors of price, in conjunction with target, creates efficiency

We believe the future of Advertising Technology is to allow for Customization At Scale:

Your Data

Your Inventory

Your Algorithm.

For more information, please contact: info@digilant.comOr visit our website www.digilant.com