Retargeting, Pixels and Cookie Syncing

Ian Herman
axialx
Published in
3 min readJun 13, 2017

Re-targeting is a major cornerstone of programmatic strategy. Although re-targeting is nothing new and has existed as a 1.0 version of programmatic, recombining this tool with new programmatic advancements is worth its weight in data.

Developing an inventory of initial site visitors allows for an effective re-engagement with those consumers that have already interacted with a brand. In analyzing the purchase funnel, a retargeting campaign exists at the very end with limited reach but suitable cost-per-action measurement.

PIXELS

In the burgeoning landscape of data profiling, re-targeting fits into the larger picture utilizing pixel placement (an invisible-to-the-eye image file with a script (code) that places a cookie onto the user’s browser) linking that user’s web browser with their website visit. A pixel is the script or code and the cookie is the placement of that code downloaded (stored) onto a user’s browser. Referred to as a tracking pixel (there are also conversion pixels), a consumer encounters an ad generated from a previously visited website in their future web browsing activity.

In today’s 3.0 programmatic world where targeting consumers at all points along the entirety of the purchase funnel is made possible with the applied use of holistic user profiles. Programmatic version 2.0 (associated with advancements in audience buying but more on that later) did not have the the now available automated application of massive amounts of data collection necessary for segmentation of website visitors for selection of sophisticated media buying. Such a selective media buying strategy can yield higher ad inventory quality (brand safety), effective assessment of publisher platform selection and better-negotiated pricing of ad placement in real time (through auction bidding increasingly performed through private marketplace deals).

So returning to traditional digital advertising in which tracking pixels allow advertisers to measure website visitor traffic and digital ad viewing, let’s turn to the application of pixels in programmatic advertising campaigns.

Historically speaking, the difference between number of site visitors versus conversion rate (purchase action) was satisfactory in fulfilling KPI requirements for brands, companies and marketers searching for performance metrics. Presently speaking, the demand for granularity is where things become interesting.

Whereas the old model depended on targeting a singular platform, today the capabilities available in reaching hyper specific targets (a single individual) are now possible with data management platforms (DMPs) aggregating user data with omnichannel (multi-device and platform) measurement. Simply stated, the data points collected in real time from mobile devices, the offline data brought online via a partner and a DMP coupled with optimization tools including geo-fencing, precise demographic profiling and analyzing consumer relevance for specified products contribute to deeper insight and greater efficiency in executing media buying. The intersection of data collection and pervasiveness of today’s mobile technology allows for the aggregation of this granular assessment of the consumer at an individual level.

COOKIE SYNCING: Mutual Interest drivers between Demand and Supply Sides in Programmatic

Piggybacking scripts (pixels) are the nuts and bolts that integrate Data Management Platforms (DMPs) with Demand Side Platforms (DSPs) and Supply Side Platforms (SSPs). Furthermore, syncing cookies provides a mutual benefit between the DSP and SSP. Current web browsing technology only allows for identifying a cookie from the domain from which the cookie was set. Without cookie syncing, each side of the demand and supply platforms could only evaluate a cookie set by their respective sides, but not to determine if the other side (counter party) has a cookie on that given user. In order to assess each user as a genuine user, the demand side is interested in verifying (matching) user sets to identify that correct (competitive) bids are executing. In other words, the demand side is willing to place higher bids on users for which they already have cookies on a given user. The demand side will then place the bid ideally capturing the piece of ad inventory that will then instantaneously display for that given user. BAM! Ad served and campaign optimizing continues.

Ian Herman is a digital advertising and marketing specialist with a background in programmatic (automated, data driven, real-time marketing). Read more on Ian’s programmatic advertising blog AxialX

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Ian Herman
axialx
Editor for

Investigating the intersection of artificial intelligence and data in automated fields including marketing and advertising, automotive, and technology