B Evidence Grade B Graded under review Safe to Cite Current

4% -- auc gain vs traditional targeting for Exposure-based Factor Model (EFM) for display advertising targeting (2026)

Name: Auc Gain Vs Traditional Targeting Statistics
Creator: Lighthouse Intelligence
Published: 2026-10-03

2026 · n=200 · Neha Gupta (research paper)

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Attribution: Neha Gupta (research paper) View source

Lighthouse Research Team

Last verified: 2026-10-03 · How we verify data →

Source verified Evidence graded

Value

Unit

Percentage

Data Vintage

2026

Entity

Exposure-based Factor Model (EFM) for display advertising targeting

Sample Size

200

Evidence Quality

Strong, reliable evidence

Sourced from a well-regarded research firm or industry leader with transparent methodology and a reasonably large sample.

61/100 confidence

Single source - not yet corroborated

Score breakdown

Extraction

Source Trust

Citation Chain

Independence

Methodology

Freshness

Source

Neha Gupta (research paper) Primary Tier B

http://behavioraltargeting.biz/factoring-past-exposure-in-display-advertising-targeting/ ↗

Confidence: 53/100 Vintage: 2026 Channel: Common Crawl

Source Article

Factoring Past Exposure in Display Advertising Targeting

Original Research

Neha Gupta (research paper) · Original study ↗

Methodology

Tested over 200 real-world online advertising campaigns; AUC gain range 4-7%, midpoint reported

Methodology documented

Segmentation

Industrymarketing

Cite this stat

Plain Text

Exposure-based Factor Model (EFM) for display advertising targeting: 4% auc gain vs traditional targeting. Source: Neha Gupta (research paper) (2026). Via Lighthouse Intelligence -- https://lighthousedata.io/data/efm-model-auc-gain-display-targeting

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<blockquote cite="https://lighthousedata.io/data/efm-model-auc-gain-display-targeting" style="border-left:3px solid #2563eb;padding:12px 16px;margin:16px 0;font-family:system-ui,sans-serif;background:#f0f4ff;"><strong>4%</strong> -- auc gain vs traditional targeting for Exposure-based Factor Model (EFM) for display advertising targeting<br><small>Source: Neha Gupta (research paper) (2026) · <a href="https://lighthousedata.io/data/efm-model-auc-gain-display-targeting" target="_blank" rel="noopener">Lighthouse Intelligence</a></small></blockquote>

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