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
    Audio
    BY CUSTOMER TYPE
    Brands & Agencies
    Publishers
    Platforms & Partners
  • Insights
    IAS Insider
    Media Quality Report
    Research
  • Innovation
  • About
    Quality Impressions™
    Newsroom
    Leadership & Awards
    Careers
    ESG at IAS
  • 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 Korean Korean
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
    Audio
    BY CUSTOMER TYPE
    Brands & Agencies
    Publishers
    Platforms & Partners
  • Insights
    IAS Insider
    Media Quality Report
    Research
  • Innovation
  • About
    Quality Impressions™
    Newsroom
    Leadership & Awards
    Careers
    ESG at IAS
  • 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 Korean Korean
  1. Home
  2. | Channels
  3. | Programmatic
  4. | Problematic programmatic: Getting to grips with pre-bid technology
October 4, 2016 by IAS Team

Problematic programmatic: Getting to grips with pre-bid technology

Programmatic
Resources
Topics
Share:

With the UK’s investment in programmatic set for double digit growth, pushing spend towards £2.5 billion in 2016, it’s no surprise the demand for greater transparency and highly viewable, bot-free and brand-safe impressions within the programmatic ecosystem is at an all-time high.

There has been a legacy issue with real-time bidding (RTB) where transparency into what inventory buyers are bidding on is brought into question. As buyers balance programmatic trading with potential risks to brand safety, ad fraud, viewability targets, price, and other criteria – all in a fiercely competitive market – transparency is absolutely essential.

Media quality vendors have recognised this need for transparency and created intelligent, pre-bid targeting segments using data points from billions of impressions, which can be implemented across campaigns to provide highly accurate targeting that fits with a media buyer’s requirements. But it is vital for buyers to understand how these targeting segments are generated and how they can be used to best effect.

Mapping scores

So how are pre-bid segments created and how do they come to be put into the hands of media buyers?

Media quality vendors have highly scalable platforms and rating engines, fuelled by data points from billions of impressions that allow these intelligent targeting segments to be created. Data is collected from billions of unique URLs every day, each with its own associated set of metrics. Some of these are largely static, such as a URL’s brand safety scoring – how much risk that URL content poses to brand advertising. Others are inherently dynamic and based on user behaviour, viewability and fraud being the obvious examples.

All these metrics are grouped together and analysed, and a predictive score is created for each URL and placement. A basic map of scores is then produced, which the demand-side platform (DSP) will use as the selection logic for buying media.

Optimising for targets

These pre-bid segments must then be exposed to the buyer, typically through a DSP or a maintained bidder. Because a typical ad auction must be executed within 10 milliseconds, it isn’t possible for a DSP to provide the media quality vendor with a constant stream of all bid request URLs in real time. It would create too much latency in the delivery chain if a request was sent from a supply-side platform (SSP) to a DSP, then referred to the media quality vendor to supply a URL rating before the DSP could finally conduct the auction.

Instead, the media quality vendor’s URL scores are held by the DSP in a continually updated cache – a component that stores data so future requests for it can be served faster. The DSP can ask about a particular URL at any time – the response is conducted via an API which can scale to the queries per second (QPS) needed. This allows the DSP to create the universe of scores offline and allows instant access to the pre-bid rating through a simple look-up rather than any transmission of data.

Finally the DSP must visualise the segments in their user interface for client targeting. Typically, segments are shown in the UI with a description, for example, ‘target top 10% of impressions in view for the longest period of time’, or ‘exclude ads that have a high risk of fraud.’ Buyers can select multiple segments to ensure that while brand safety and fraud risk is minimised, they are optimising towards their viewability targets.

Analysis is key

While pre-bid segments go a long way to helping buyers reach their campaign targets they don’t necessarily provide a guarantee in all cases. For example, preventing delivery on suspicious or non-brand-safe URLs is an immediate win, but the competition for highly-viewable impressions is fierce and supply for these is not unlimited.

As with all RTB buying strategies, one should take the time to closely analyse winning bid prices, segments, and volumes, both at the campaign and macro level to ensure targeting segments are working effectively.

With pre-bid segments the issue of transparency in RTB has vastly improved and thanks to the addition of key media quality elements in programmatic buying, such as viewability, buyers can now be confident the inventory they are bidding on is far more accurately represented.

Read more here.

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

Constructing Your Quality Path: How media quality strengthens supply path optimization strategies
Constructing Your Quality Path: How media…
Learn more ›

November 16, 2022 by IAS Teams

Navigating your advertising strategy this election season
Navigating your advertising strategy this election…
Learn more ›

November 2, 2022 by IAS Teams

IAS & Diageo talk media quality and transparency
IAS & Diageo talk media quality…
Learn more ›

October 1, 2022 by IAS Teams

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

Audio

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

© 2023 Integral Ad Science, Inc.

Accessibility_Icon Accessibility statement

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

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.

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.