We use cookies to deliver the best possible experience on our website. To learn more, visit our Privacy Policy.
By continuing to use this site, or closing this box, you consent to our use of cookies.X

Multicultural advertising with Contextual AI Download Whitepaper New

State of Brand Safety & Suitability in Video Download Now

Beyond Black and White: The True Color of Brand Safety |   07 Jul, 2020

difference between contextual and keyword targeting

Over the past few years, a lot of brand safety issues have surfaced that have led marketers to review their brand safety measures. The current coronavirus crisis has intensified the brand safety woes of marketers, as most of the brands don’t want ad adjacency to the content dealing with morbidity and mortality.

Common brand safety methods used by marketers include blacklisting and whitelisting. Blacklisting involves avoiding the placement of ads against content containing specific blocked keywords. For video content, a blocked keyword is searched in the topic, title, description, and metadata. In contrast, whitelisting enlists content that has been labeled as safe for ads to be placed. 

How Common Brand Safety Methods Impact an Ad Campaign?

The keyword-based blacklisting method is in reality not as effective as it seems to be. It is marred by under and over-blocking of content. Research shows that because of the use of keyword blacklists, more than half of the safe stories published on the major news platforms are being incorrectly tagged as brand unsafe. 

keyword-based blacklisting approach

The keyword-based blacklisting methods lead to the blocking of completely innocuous content. This is due to its inability to recognize the subtleties in context, or more specifically, the actual context in which a term is employed.

For example, if “alcohol” is the blocked keyword, then the blacklisting method will not only mark a video featuring drunk and driving as unsafe but will also add a video featuring a recipe using alcohol to the list. 

Another problem with blacklisting is that universal blacklists cannot be created. They have to be regularly updated and modified according to the brands’ requirements, current happenings, events, the latest news, countries, languages, and cultures. There is also a requirement to tweak blacklists regularly on the basis of current safe content consumption patterns of consumers so that increased reach for the advertising campaigns can be achieved. 

In general, the implementation of the keyword-based blacklisting approach requires a lot of fine-tuning. But this approach hinders marketers from getting optimal results from their advertising campaigns.

A whitelist provides a safe and trusted environment for brands to advertise within. Curating a whitelist for advertising on a video platform involves tagging unsafe content at the keyword, topic, video, and channel levels. Video-level tagging helps brands to filter out unsafe videos. Brands do not have to blacklist an entire channel just because of one or a few unsafe videos.

Similar to keyword blacklists, whitelists also need to be regularly updated, otherwise, the campaigns will not witness an increase in reach, and brands will miss new opportunities to engage consumers with their ads. 

Creation of whitelists is not an easy process; it requires a lot of curation by marketers and is time-consuming and expensive. As the whitelisting method limits the number of videos against which ads can be placed, marketers are unable to take full advantage of the true potential of huge video hosting platforms like YouTube. The campaign’s reach gets reduced and the right audience does not get fully targeted.

Contextual Targeting: An Alternative for Keyword-based Targeting

The above-mentioned brand safety methods provide only suboptimal brand safety and have significant limitations. Keeping these points in mind, advertisers have been shifting to contextual targeting. This approach allows brand safety with the help of AI and computer vision. 

In contextual targeting, ads are deployed based on the content consumed by the user. Computer vision can accurately detect contexts in videos such as faces, objects, logos, on-screen text, emotions, scenes, and activities. Thus, it can effectively detect unsafe or harmful contexts in videos. 

Amid the coronavirus pandemic, computer vision-powered brand safety platforms enable brands to selectively block ads against mortality-related coronavirus content, while allowing ad placement against positive coronavirus content. Thus, brands can safely capitalize on the news content; this is not possible with keyword blacklists that fail to understand the true context in which the keyword “coronavirus” is being used.

Advertisers can successfully prevent ad placement against known harmful categories by employing AI-based contextual brand safety solutions, but they can also identify inappropriate circumstances that are specific to a brand.

Also read, How brands are navigating brand safety?


Ensuring brand safety without killing the reach is the top priority for advertisers but keyword-based targeting doesn’t allow it. Whereas, AI and computer vision enables marketers to go beyond blacklists and whitelists in order to achieve brand safety in its true color without limiting the reach. Also, ad campaigns achieve better KPIs which results in better ROI.

    Recommended posts
    Migrate from Oracle to Silverpush

    Migrate from Oracle to Silverpush: Unlock Advanced Contextual Advertising Solutions

    The news that Oracle plans to shut down its advertising business by the end of September has sent shockwaves through the ad industry. Once the most prominent advertising data seller in the market, Oracle is now closing its advertising division. This included Datalogix for offline consumer data, Grapeshot for contextual ...


    Cannes 2024 Recap: Silverpush Takes AI Discussions to the French Riviera

    As Cannes 2024 concludes, the echoes of vibrant discussions, insightful panels, and significant meetings continue to resonate. This year’s central theme was clear: AI's growing dominance in advertising solutions, optimizing campaigns for business outcomes, and reaching audiences effectively across various screens. With videos becoming increasingly digital, the potential for more addressable ...

    UK Programmatic Ad Spending & Trends in 2024

    UK Programmatic Advertising Spending & Trends in 2024

    In 2023, programmatic advertising spending in the UK reached roughly £30.6 billion. The programmatic display advertising market is projected to grow by 12.6% in 2024, bringing it to within just four percentage points of becoming fully programmatic. This highlights how integral this technology has become to the UK ad industry. ...