As per industry experts, programmatic ad spending is expected to witness significant growth in the coming years, with the budget projected to reach a staggering $725 billion by 2026.
This growth is anticipated to be driven by various factors, including the rise of third-party cookies, which have enabled behavioral targeting and increased ad inventory.
However, this trend is expected to face challenges due to data privacy regulations such as GDPR, leading to a decline in ad inventory and driving up advertising costs.
Furthermore, the postponement of Google’s third-party cookie phase-out to H2 2024 has added further uncertainty to the future of programmatic advertising.
Overall, advertisers are exploring various solutions to navigate the changing landscape of programmatic advertising and capitalize on the opportunities presented by evolving technologies and user behavior.
Understanding Contextual Targeting
Contextual targeting is a specific form of contextual advertising that involves the strategic placement of ads based on the type of content a user is consuming on a website, app, or CTV video. Unlike traditional methods that rely on user behavior and past activities, contextual advertising focuses on the user’s current browsing environment and behavior.
As a subset of programmatic advertising, contextual targeting is typically implemented through ad networks that segment contextual ads and target groups based on pre-selected parameters, including:
- Content of the web page or app the user is visiting
- Keywords used on the web page or app
- The topic of the web page or app
- User’s search intent and behavior
- Location of the user
- Device the user is using
By leveraging contextual targeting, advertisers can ensure that their ads are shown to users who are more likely to engage with their content and take the desired action.
What’s the Difference Between Contextual Advertising Behavioral Advertising
The main distinction between contextual and behavioral advertising lies in the timing of targetable user actions. Behavioral advertising targets users based on their past browsing behavior, whereas contextual advertising is based on the real-time context of a user’s content consumption.
To target users based on their behavior, advertisers segment their audience using “digitally observed” actions, such as websites visited, ad clicks, click-through rate (CTR), and items purchased or downloaded. They achieve this through the use of automation and behavioral data that is gathered from various sources.
In the context of CTV, behavioral targeting refers to the practice of using information from user profiles to create advertising campaigns that are tailored to specific factors such as viewing habits, search history, language, and other relevant preferences. This involves analyzing user data to develop targeted ads that are more likely to be of interest and relevance to the viewer.
What Makes Contextual Traffic Unique?
Contextual targeting generates traffic that lacks behavioral data about users due to its unique nature.
Contextually-generated users may not be suitable for traditional techniques like retargeting unless they choose to accept cookies on the advertiser’s website.
This requires advertisers to put in extra effort to create valuable and relevant experiences for contextually-generated users once they land on their website. To achieve this, advertisers need to pay close attention to the following:
- The kind of content the user is viewing or reading.
- The keywords used in the content
- The channel through which the user is accessing the content
- The type of device the user is using (desktop, iOS, Android, etc.)
By leveraging this information, advertisers can create more targeted and effective campaigns that resonate with their audience. Additionally, advertisers need to adopt a user-centric approach that focuses on delivering value to the user, rather than simply pushing ads at them. This will ultimately lead to better engagement and conversion rates, even without relying on traditional behavioral targeting techniques.
For advertisers using contextual targeting, it’s crucial to understand the origin of each stream of context and the type of content their audience was consuming before clicking through. This information will determine the messaging, conversion offer, and next steps that should be provided to the user on the website.
As a result, advertisers using contextual targeting may need to frequently experiment with different ad and landing page copy to determine what resonates best with their audience. However, depending on the contextual data provider, advertisers may have limited data points to monitor and analyze. Therefore, it’s important to work with a contextual partner that can provide transparency regarding the placement of contextual ads, the audience, and the down-funnel results.
In the case of contextual CTV advertising, Peer39 offers metrics such as ad start impressions, ad completion rate by channel, age/gender of the audience, channel, content categories, number of ads per channel, number of ads per show, OTT service, and production type. This contextual data, combined with sales and conversion data, can inform the type of traffic, messaging, and creative that performs best on a large scale.
As the costs of behavioral advertising continue to rise, advertisers are increasingly looking to contextual traffic as a more cost-effective alternative. The popularity of contextual advertising has been growing across various platforms, including websites, apps, and CTV, leading to a significant increase in ad budgets being allocated towards this approach.