Internet R/F and Cross-Site Duplication Project

April 9, 2003

ARF 49th Annual Convention

Roger Baron; FCB/Chicago

Leslie Wood; LWR

Manish Bhatia Nielsen Net/RatingsJason Bigler DoubleClickLynn Bolger comScoreJim Daniels Church & DwightDoug Honnold comScoreStephen Kim comScoreAllister Lam DoubleClickStacy Malone Universal McCann InteractiveBrian Monahan Universal McCann InteractiveKelly Niehoff MullenScott Penniston FCB/Southern CaliforniaSusan Russo Nielsen Net/RatingsMarc Ryan Nielsen Net/RatingsJennifer Shunk R.J. PalmerDenise Siedner DoubleClickDave Smith MediasmithYoung-Bean Song AtlasDMTJim Vail R.J. PalmerRandy Wootton AtlasDMT

Thank You’s

Background Internet R/Fs were presented at a March 2002 R/F

committee meeting

Dramatically different results from each supplier

Leslie Wood and Roger Baron proposed comparing campaign reach/frequency and cross-site duplication estimates provided by each supplier.

David Smith and Gabe Samuels created coalition of data providers

Coalition investigated and developed a methodology

Ten advertisers have agreed to participate

Preliminary data from one-week of tracking will be presented

The TeamResearchers

Gabe Samuels, The ARF – Project Coordinator

David Smith, Mediasmith – Project leader

Leslie Wood, Leslie Wood Research – Research Designer and Researcher

Roger Baron, SVP, Director of Media Research, FCB/Chicago – Researcher

Team – continuedData Suppliers

Server Centric MeasuresDenise Siedner, Allister Lam; DoubleClick

Young-Bean Song; Atlas DMT

User Centric MeasuresMarc Ryan, Susan Russo; Nielsen//NetRatingsDoug Honnold, Lynn Bolger; comScore  

Key Objectives Compare R/F and duplication measures from

different data suppliersServer centricUser centric

Create standards for reporting duplication

Better understand the possibilities and obstacles to developing a new methodology combining user and server centric measures into a single R/F measure.

Make recommendations for next steps to modeling R/F

Some definitionsServer Centric Measures (SCM)

Count of computers (cookies) that were served an advertising message.

Includes every served impression - the basis for media billing

Need to differentiate US versus international exposure

No demographics

Participating suppliersDoubleClickAtlas/DMT

User Centric MeasuresWebsite exposure from a panel of Internet users who

allow researchers to electronically monitor their browsing behavior.

Statistically projectable to U.S. Internet users

Individual user login allows demographic detailSyndicated service reports websites, not adsMust be provided ad URL’s for this study

Participating suppliersNielsen//NetRatingsComScore

Definitions (cont.)

Reach: Traditional media definition“The number of different persons or homes exposed to a specific media vehicle or schedule at least once. Usually measured over a specified period of time (e.g. four weeks). Also known as cume, cumulative, unduplicated or net audience.”

- Advertising Media Planning, 6th ed - Sissors & Baron

Reach: Internet media definition“The number of different cookies or United States persons 2+ at home or at work, who have been exposed one or more times to a complete Web advertising message over the campaign period.  "Reach" is synonymous with unique audience.”

- ARF Reach/Frequency Committee

Definitions (cont.)

Not

Reached

% Reach

Site 1

Two-site DuplicationThe number of persons or cookies exposed to both sites as a percent of those who are exposed to either site.

Random duplication:Assumes people who browse site 1 are as likely to browse site 2 as anyone in the population.

Not

Reached

% Reach

Site 1

% Reach Site 2

Duplication

Actual duplication is always moreThink: people who browse IDG.NET also browse ZiffDavis

Not

Reached

% Reach

Site 1

% Reach Site 2

Actual

Duplication

Random always

overstates Reach

Duplication

Calculating percent duplication

Definitions (cont.)

Site A Site B A&B

Calculated as: A&B / (A+B-A&B)

Study Design Report the same measures for the same

advertising campaigns from four data suppliers

Server centric suppliers give ad campaign URLs to user centric researchers.

User centric researchers develop custom methodology to report when these ads appear on their sample’s browsers.Required because their syndicated reports just

track websites, not the embedded ads.Custom methodology is still being refined Findings reflect both of the server centric suppliers.

Study Design continued Advertisers across industries

Large ad campaigns

Variety of ad strategiesFrequency capsTargetedROS

Matched variables from both server and user centric suppliers

Reported Measures Total campaign impressions

Total campaign reach Advertiser: “How many people saw my ad?”

For each website in the campaignImpressionsTotal ReachExclusive reach

Duplication matrix of all sites taken two at a time.

Progress Determine technical logistics

What address could everyone readWhat address made sense across suppliers

Full agreement from suppliers to participate

Testing of IAB’s Ad URLs completed

Recruiting advertisers to allow server centric suppliers to share data

NDA’s from team for advertisers

Several advertisers have signed agreements

Data collection just beginning

Issues along the way Advertiser resistance and need for confidentiality

DoubleClick limited to “DART For Advertisers”

Time consuming (gratis) project

Large number of creative units

On-going need to notify UCM’s of creative changes

Complexity of Rich media creative

Handling of geographically focused and “tracking” ads

Inconsistent website name granularity

Custom definitions and report formats

Data / Findings

Data / Findings

Data / Findings

Data / Findings

Data / Findings

Data / FindingsDuplication between two websites is small (typically less than 0.25%)

but slightly greater than random

Data / Findings

Learnings At this early date, there is similarity among the methods

Net reach as a percent of sum of site reaches Average site percent exclusive reach Actual campaign reach vs. random Duplication between websites

Duplication between websites is greater than random, but only slightly As in traditional media, random overstates campaign

reach

Determining User based ad campaign reach and frequency is labor intensive and methodologically immature.

Next steps Continue tracking pilot advertiser campaigns

Add additional advertisers

Report detailed findings at June ARF Internet R/F Committee meeting