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