Interviews, insight & analysis on digital media & marketing

A brief guide to CTV targeting in 2022

By Artjom Gammel, Partner Director at Xandr

Stated often, CTV is currently the biggest opportunity in the programmatic advertising industry. It is a young format with new technical challenges in a market environment located between traditional TV broadcaster-behemoths and tech-savvy, pioneering pirates. Macro trends like privacy focus, cord cutting, streaming wars and market consolidation heavily influence the evolution of this specific market. 

Yet it is challenging for advertisers and traders to apply data for targeting like they are used to from traditional channels in their DSP. So we need to ask the question, what kind of CTV data is available today and how it can be activated by use cases?

Audience Targeting

First is audience targeting. As CTV devices are used by more than one person we normally speak of household targeting. I see three pre-dominant approaches when it comes to audience targeting in CTV: First-party data activation, IP Targeting and cross device. 

First-party data activation

As CTV by nature is a new, cookieless and ID-limited environment, most of the available audience data sits siloed within a first party. Audience data here can be related to the registered user or the viewership behaviour. These data owners can be categorised into publishers and device manufacturers (SmartTV and OTT devices). 

The simplest way to activate publishers’ data are buying pre-targeted deals. On the one hand publisher’s see exactly which content has been watched but can apply the data on the other hand on their own inventory only. While device manufacturers have the capability to activate their data across publishers offering wider scale, they normally only see if and how long an app has been watched. Depending on positioning and strategy device manufacturer offer direct data sales, media bundles and/or activation via proprietary platforms. 

Few, large device manufacturers work on introducing CTV identifiers. Stable, standardised identifiers can improve data activation in the CTV environment among many other benefits.

IP Address Targeting

The IP address is available in the oRTB bid requests, usually. IP address was being used in targeting for quite a while and is still an effective way to target audiences from a technical feasibility perspective. However, it is defined as personal data by GDPR. Therefore, it is vital that CTV publishers use a CMP and collect users’ consent before making it actionable. While it is still the most common currency for CTV targeting it faces a risk of being removed like third-party cookies at a later date.

Some data providers have audience data tied to IP addresses and can offer audience segments in data marketplaces. The IP Address can also be used for geo targeting, as an identifier in a cross device audience extension or for brand safety and fraud prevention by verification providers. 

Cross device 

Audience extension with a cross device graph links various identifiers to a user or a household. A graph can include CTV data if the graph owner has access to that data and the ability to link the identifiers. Those links can be based on IP-Address, hashed email addresses or other identifiers. Main cross device use cases are audience extension, frequency capping and attribution.

Cross device graphs can be enabled within DSPs. Publishers or advertisers are also able to maintain graphs themselves and activate this data via audience segment uploads.

Contextual Targeting

Whilst audience targeting in CTV remains challenging, contextual approaches can seem more sophisticated. There are two which are important to highlight:  Geo and Content related targeting.


Geo Targeting can be performed within the IP address. The IP address indicates the location of where an impression originates. Even with truncated IP addresses it is possible to target wider fences like county or city level. With the full IP address, it might be even possible to target more granular than zip codes.

Data providers can translate location information to audience information. Effectively, it is geo targeting but they possess data with information in which areas specific audiences over-index. Geo segments can be accessed via data marketplaces. Some DSPs also offer geo targeting as feature in-platform. 


In bid requests it is possible to identify which CTV app is being watched via the app bundle ID. It can be used for rough contextual targeting on niche apps. However, it does not help to target actual content. If a streaming service is being watched through CTV the app bundle does not tell whether a horror movie or a sitcom series is being watched. 

Consequently, the Content object has been introduced in the oRTB protocol. Publishers can pass granular information about the actual content like genre, episode, age rating, live/vod and many more. In EMEA we see increasing publisher adoption in this field. Xandr’s Invest DSP for example offers content object parameter targeting for buyers. It also makes this information available to data providers.

Brand Safety

Technically, pre-bid brand safety segments are excluded from contextual targeting. From a commercial perspective it a very different use case, though. It has more or less the same technical fundament as contextual targeting with its strengths and weaknesses. In contrast to contextual targeting, it can make more sense to verify the app being watched. Also, brand safety providers can check other signals in the bid request to block suspicious traffic. Such brand safety segments are offered by the usual large verification providers in data marketplaces.

Currently first-party data and geo targeting approaches are the most effective, available and common used CTV targeting solutions, today. Meanwhile third-party data solutions will have a hard time as long as CTV remains supply-constraint and stays dominated by a handful of big fishes operating private marketplaces. For 2023, content object adaption, the evolution of standardised identifiers and improvements of CTV access in cross device graphs may bring incremental improvements to targeting. Still, advertisers will have to endure limited and siloed targeting possibilities for some more time.