Integral Ad Science
  • Solutions
    BY PRODUCT TYPE
    Ad Fraud
    Brand Safety & Suitability
    Contextual Targeting
    Viewability
    Efficiency & Optimization
    BY CHANNEL
    CTV & Video
    Programmatic
    Proprietary Platforms
    Mobile & In-App
    BY CUSTOMER TYPE
    Brands & Agencies
    Publishers
    Platforms & Partners
  • Insights
    IAS Insider
    Media Quality Report
    Research
  • Innovation
  • About
    Quality Impressions™
    Newsroom
    Leadership & Awards
    Careers
  • Careers
Log in
Investor Relations
Contact
US US
UK UK DE DE ES ES FR FR IT IT JP JP BR BR LATAM LATAM APAC APAC
Integral Ad Science
  • Solutions
    BY PRODUCT TYPE
    Ad Fraud
    Brand Safety & Suitability
    Contextual Targeting
    Viewability
    Efficiency & Optimization
    BY CHANNEL
    CTV & Video
    Programmatic
    Proprietary Platforms
    Mobile & In-App
    BY CUSTOMER TYPE
    Brands & Agencies
    Publishers
    Platforms & Partners
  • Insights
    IAS Insider
    Media Quality Report
    Research
  • Innovation
  • About
    Quality Impressions™
    Newsroom
    Leadership & Awards
    Careers
  • Careers
Log in
Contact Us
US US
UK UK DE DE ES ES FR FR IT IT JP JP BR BR LATAM LATAM APAC APAC
  1. Home
  2. | Topics
  3. | Ad Fraud
  4. | How publishers can reduce fraud with Optimization
September 12, 2018 by IAS Team

How publishers can reduce fraud with Optimization

Ad Fraud
Case Studies
Insights
Publisher
Research
Share:

A digital publisher that serves the financial, technology, and healthcare sectors was challenged by a sudden spike in bot traffic to its website. The publisher’s advertisers immediately became concerned that a portion of its inventory consisted of fraudulent traffic. This could easily lead to a breakdown in trust between parties – during the spike, the advertisers’ expectations were not being met. Any ads served to bots had no chance to impact consumers.

In order to prevent value erosion, the publisher needed to address this challenge and provide the highest quality inventory and mitigate the resulting damage to the relationships with its advertisers. The publisher started leveraging post-delivery data, but quickly recognized that such manual optimization was not sustainable, nor was it scalable or accurate enough. As a result, a seamless, automated solution was needed to improve media quality by filtering out fraudulent impressions.

Download the report to learn how the publisher was able to dramatically reduce fraud

Access the content now.
Download
Access the case study now.
Download
Access the guide now.
Download
Access the research now.
Download
Sign up for insights right to your inbox.
Subscribe now ›

Related Posts

Introducing IAS Quality Sync Pre-bid Segments with Xandr
Introducing IAS Quality Sync Pre-bid Segments…
Learn more ›

June 27, 2022 by IAS Team

Ad Context & Attention: The impact of contextually relevant ads on attention and outcomes
Ad Context & Attention: The impact…
Learn more ›

June 23, 2022 by IAS Team

Amplifying Media Quality in Digital Audio
Amplifying Media Quality in Digital Audio
Learn more ›

June 16, 2022 by IAS Team

IAS white red logo
Sign up for fresh insights

Solutions

By Product Type

Ad Fraud

Brand Safety & Suitability

Contextual Targeting

Viewability

Efficiency & Optimization

By Channel

CTV & Video

Programmatic

Proprietary Platforms

Mobile & In-App

By Customer Type

Brands & Agencies

Publishers

Platforms & Partners

Insights

IAS Insider

Research

Media Quality Reports

About IAS

Quality Impressions™

Newsroom

Leadership & Awards

Careers

Helpful Links

Contact

Log in

© 2022 Integral Ad Science, Inc.

Site indexing policy

Privacy policy

Subscription management

Transparent Background - Social Media
Transparent Background - Social Media
Transparent Background - Social Media
Transparent Background - Social Media

Site indexing policy

Privacy policy

Subscription management

Transparent Background - Social Media
Transparent Background - Social Media
Transparent Background - Social Media
Transparent Background - Social Media
Transparent Background - Social Media

© 2021 Integral Ad Science, Inc.

Search

Hit enter to search or ESC to close

Download Content

Fill out the form to have this content delivered directly to your email inbox.

Thanks for your interest. Fill out our contact form if you'd like more information.

Subscribe now

Fill out the form to sign up for the latest and greatest IAS updates— delivered right to your inbox.

Thank you for signing up for the IAS Newsletter.