cross channel attribution overview feb 2010

[x+1] AttributionFebruary 2010

Proprietary and Confidential

• Forrester recently recognized our attribution modeling capabilities, which ensure we optimize to the right measures

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“[x+1] impressed us with its full service offering which includes some of the richest algorithmic analytics of the group”


Different questions at different “scopes” of attribution

Display plan optimization

Cross digital channel optimization

Online/offline optimization






Assign “credit” to display networks and properties on your media plan in order to evaluate performance, or pay CPA bounties.






Assign “credit” to online tactics..search, display, affiliates and social, in order to allocate budget more effectively.






Optimize marketing investment and mix, by understanding interaction and synergy between online and offline tactics


Attribution Analysis Support

• Cross channel user interaction / conversion path data enablement

• Placebo analysis• Remarketing attribution analysis• Offline conversion integration• Custom marketing mix modeling


DATA / REPORTING ENABLEMENT: All user level interaction data across online channels available for analysis

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Cross-channel reporting includes:• % of unique converters seen in each channel by conversion type• # of click and display events by channel leading to a conversion event• Drill downs by different timelags (1 day, 1 week, etc.) • Optional data transfer for more in-depth sequencing analysis

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PLACEBO ANALYSIS Case Study 1: Cross channel analysis for Financial Services client

Background:• Financial services firm was interested in understanding the true view through

impact of brand vs. performance display advertising. Last click/view attribution was not telling the true story.

A better approach:• A Test/Control campaign was executed, including brand and performance

advertising.• Using ad server log file data – cross channel overlap reporting helped shed light

on the paths that led to conversion.

Results:• Display ads drove significant view through conversion for as much as 21 days

after exposure.• Performance ads drove a significant impact on conversions typically credited to

Search.

A new way to view the data drove marketing spend changes!


PI Lift for Performance & Brand Ads over Placebo

PI Lift % = (Display Application Rate % - Placebo Application Rate %) / Placebo Application Rate %

• Performance ads drive 8x more PI applications than the Placebo ads on the same day as exposure

• For days 1-16 after exposure, Performance ads drive about 3x more applications than Placebo and Brand ads drive about 2x more applications than Placebo

• Performance and Brand ad performance converges closer in application rate after day 16


Cross-channel placebo analysis

CJ LF Listing_Site SEM0.0%

5.0%

10.0%

15.0%

20.0%

9.3%8.0%

6.6% 6.1%

9.8% 9.5% 9.1%

19.1%

3.5% 3.2% 2.9% 2.6%

[x+1]-Brand [x+1]-Performance [x+1]-Placebo

Attributed Channel

% Appliers Seeing Impressions By

Channel

Leap Frog results are estimates


OFFLINE DATA INTEGRATION enables true business value analysis


Display Optimization: Avoid “false Darwinism”

• The default “last click/last view” approach creates incentives for bad behavior by all on the plan.

• Properties compete for “credit” by bombarding the remarketing pool…and are dis-incented to BUILD the remarketing pool.

• Networks and portals have learned to “game the system”, using a variety of tactics to set the last cookie…tactics that do not drive sales.

Most of the time, clients and agencies get it wrong


Remarketing analysis

SiteReach

(Unique Users)

1 2-3 4-5 6-8 9-12 13+ SiteReach

(Unique Users)

1 2-3 4-5 6-8 9-12 13+

Yahoo! Finance 32,465,678 32% 13% 5% 2% 9% 39% Yahoo! Finance 6,493,136 16% 10% 10% 9% 18% 37%MSN Homepage 27,595,826 43% 26% 15% 9% 4% 2% MSN Homepage 5,519,165 19% 14% 14% 13% 15% 25%AOL Finance 23,456,452 27% 18% 11% 7% 17% 20% AOL Finance 4,691,290 12% 11% 11% 10% 22% 33%Exchange 21,037,089 52% 22% 9% 4% 7% 7% Exchange 4,207,418 26% 26% 16% 9% 9% 14%Weather.com 19,937,985 32% 21% 14% 9% 14% 11% Weather.com 3,987,597 11% 10% 10% 9% 24% 35%Casale Media 16,947,287 48% 21% 9% 4% 9% 10% Casale Media 3,389,457 6% 8% 10% 13% 24% 39%Audience Science 11,149,657 24% 21% 18% 15% 11% 11% Audience Science 2,229,931 4% 6% 9% 14% 20% 47%Yahoo! BT Segment 5,909,318 31% 20% 12% 8% 16% 13% Yahoo! BT Segment 1,181,864 12% 11% 11% 10% 16% 39%CNN 3,131,939 36% 11% 10% 17% 13% 13% CNN 626,388 13% 12% 12% 11% 13% 39%Forbes 1,659,928 42% 13% 11% 14% 8% 12% Forbes 331,986 15% 14% 14% 13% 22% 22%TOTAL CAMPAIGN 37% 19% 11% 7% 10% 16% TOTAL CAMPAIGN 15% 13% 11% 11% 18% 32%

OVERALL (EXCLUDING REMARKETING) FREQUENCY REPORT REMARKETING FREQUENCY REPORT% OF SITE IMPRESSIONS IN USER FREQUENCY

CATEGORY USER FREQUENCY CATEGORY

Report Uses• Assess the relative attribution credit of conversions by site.• Assess the effectiveness of the site to generate conversions on a weighted basis.


Converter Overlap

SiteAttributed

Conversions% Conversions

Exclusive to site% Imps for

Converters to site% Conversions

Attributed% Converter Impressions

% Campaign Impressions

IndexWeighted

ConversionsAttribution Weighting

Yahoo! Finance 154 40% 81% 19.1% 17.5% 25.5% 69% 141 92%MSN Homepage 138 35% 75% 17.1% 18.8% 16.3% 115% 152 110%AOL Finance 117 56% 68% 14.5% 9.5% 9.2% 103% 77 65%Exchange 105 32% 56% 13.0% 19.3% 11.2% 172% 156 148%Weather.com 100 80% 74% 12.3% 13.4% 10.5% 128% 108 109%Casale Media 85 45% 91% 10.5% 8.8% 9.3% 94% 71 84%Audience Science 56 12% 52% 6.9% 4.8% 11.9% 40% 39 70%Yahoo! BT Segment 30 45% 65% 3.7% 4.8% 4.8% 100% 39 131%CNN 16 12% 56% 1.9% 1.7% 0.8% 213% 14 88%Forbes 8 50% 72% 1.0% 1.4% 0.6% 233% 11 136%

Overall Post-Impression Converter Report

Report Uses• Assess the relative attribution credit of conversions by site.• Assess the effectiveness of the site to generate conversions on a weighted basis.


Case Study 2 – Attribution for multistage conversion process

Background:• Entertainment company, sales funnel starts with a free

trial and ends with a paid subscription.• As company tried to scale campaign, cost per sale was

increasing, with little subscription growth.

Dynamics:• To scale the campaign, client added CPA deals to plan. • CPA providers bombarded the remarketing pool,

gaining credit for last view. Non CPA providers lost share of sales and had their budgets cut as their credited CPA’s went up.

• Remarketing pool shrank, sales flattened at a higher overall cost.

A better approach:• For each provider, measured unique contribution to

reach overall and to remarketing reach. • Rewarded trial drivers and reach providers and

eliminated remarketing for all but one partner.

Awareness

Free Trial

Buy

New approach led to renewed subscriber growth!


Proven online marketing mix modeling techniques are applied to drive full online channel optimization

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Three primary approaches:

Conversion interaction analysisGoal – impact of immediate response (click and immediate viewthrough) behavior on overall channel responses (view and organic conversions)

Online Cross channel analysisGoal - decompose drivers of online conversion

using more detailed display drivers (offers, promotions, etc) and additional online channels (search, affiliate)

Online Conversion analysis – tiered approachGoal - understand the detailed drivers of online

conversions across marketing elements, both online and offline, and the interactions between them.


Conversion interaction analysis – Immediate response multiplier

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View-based and/or Organic Conversions

Media?

(Y/N)

Click based Conversions

Other factors

View through + Organic Conversions = constant+ β1 * (PC conv.)+ β2 * (lagged PC conv.)+ β3 * (1 hr. PI)+ β4 * (media = 1)+ β5 * (week, month)+ β6 * (site change) + β7 * (…)

What you get: A basic understanding of relationship between click-based, view-based and organic conversions to help in forecasting and planning – identifying the multiplier

Requirements: Differentiation in levels of display media execution

Approach: Use regression to decompose display impact on organic and view-based conversion, controlling for high level market changes

Example regression equationExample approach


Online Cross channel analysis

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View-based and/or Organic Conversions

Media?

(Y/N)

Click based Conversions

Other factors

View through + Organic Conversions = constant+ β1 * (PC conv.)+ β2 * (lagged PC conv.)+ β3 * (site change)+ β4 * (media = 1)+ β5 * (week, month)+ β6 * (…)

What you get: A basic understanding of drivers of online conversion using more detailed display data (offers, promotions, etc) and additional online channels (search, affiliate)

Requirements: Cross channel tagging or log files

Approach: Use regression to decompose display impact on organic and view-based conversion, and other channels.

Example regression equationApproach

Search or affiliate click conversion = constant + β1 * (PC conversions) + β2 * (lagged PC conversions) + β3 * (media = 1) + β4 * (week, month)

+ β5 * (…)


Online Conversion analysis – tiered approach

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What you get: A detailed understanding of drivers of online conversion and the interactions between them, including online and offline efforts

Challenges: Collinearity , too strong of a read, no read, model breakdown

Approach: Basic approach is similar to classic marketing mix analysis, time series regression. However, tactic interactions are explored in more detail, through interaction variables, synergy terms, or additional models (i.e. search or display as a dependent). Expanding further, multiple models are run exploring different parts of the funnel.

Conversions

Online Marketing

Offline Marketing

Other FactorsOffline

Marketing

Other Factors

Classic marketing mix

Search traffic = constant + β1 * (economic factors) + β2 * (TV GRPs) + β3 * (Print TRPs) + β4 * (…)

Example regression equations

Conversions = constant + β1 * (price) + β2 * (special offer) + β3 * (economic factors) + β4 * (TV GRPs) + β5 * (Print TRPs) + β6 * (Search) + β7 * (…)


Attribution Analysis Support Overview

• Cross channel user interaction / conversion path data enablement

• Placebo analysis• Remarketing attribution analysis• Offline conversion integration• Custom marketing mix modeling

Attribution analyses can lead directly to optimization of online marketing programs through POE

cross channel attribution overview feb 2010

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