Traditional contextual advertising works by matching a webpage's content with an ad's content. Instead of
using data about the user, the automated system displays relevant ads based on the page's content. While
contextual has long been used in programmatic media planning and execution, it's also been recently touted as
a privacy - forward approach to solving for cookieless advertising.
But contextual needs to be elevated in order to be a sophisticated tool for solving for declining addressability.
Elevated Contextual
Say goodbye to standard contextual…
Source: 1. TripleLift Internal Data from Large - Scale US Advertiser Campaign, 2023
…and hello to elevated contextual with TripleLift Audiences
TripleLift's Modern Contextual Inputs
TripleLift 1PD Audiences segments publishers first - party data against a standard IAB taxonomy, but we don't
just rely on pure contextual plays. We also take user behavior into account within a publisher's page to ensure
that we've properly captured a user's interest:
User Buyer
basketball.com
3 visits
wnba.com
5 visits
nba.com
1 visit
Our approach elevates contextual at the intersection of content and user behavior. In the example nba.com
does not make it into the "Basketball Enthusiast" segment because it has only 1 of 3 visits required for
segmentation. This means our segment definition focuses on high user engagement with the content and
factors in recency and frequency.
• Content (HTML Text)
• User ID and URL
• Meta Keywords
• Meta Description
• Keyword Scoring
TripleLift modernizes contextual with a range of
inputs and sophisticated parsing and scoring of
page content to ensure overall content
alignment, leveraging both natural language
processing (NLP) and machine learning.
Segment
Basketball Enthusiast
3+ visits in last 7 days
to basketball content
Deal ID
BBall123
Bid Req
Deal: BBall123
on
basketball.com
Bid Req
Deal: BBall123
on
wnba.com
