Enhancing Brand Safety in Programmatic Advertising: Contextual Targeting, Keyword Blocklists, GARM Compliance & Prebid Modules
In the highly competitive world of programmatic advertising, brand safety is crucial. A recent SEMrush 2023 study found that over 60% of brands worry about improper ad placements, and an IAS study shows consumers are likely to boycott brands associated with inappropriate content. When it comes to ensuring brand safety, consider “Premium vs Counterfeit Models.” Contextual targeting offers precise content – based ad placements, while keyword blocklists have limitations. Brands can achieve GARM compliance by combining methods. Best Price Guarantee and Free Installation Included in some top – notch brand safety solutions in the US. Act now to safeguard your brand!
Brand safety in programmatic advertising
In the fast – paced world of programmatic advertising, brand safety is no longer a luxury but a necessity. According to a SEMrush 2023 Study, over 60% of brands are highly concerned about their ad placements in programmatic advertising, as improper placements can lead to significant reputational damage.
Definition
Importance for brand reputation
Brand safety in programmatic advertising ensures that ads do not land in inappropriate places, such as alongside fake news, harmful content, or in shifting contexts. A single wrong ad placement can destroy a brand’s reputation that has been built over years. For example, if a family – friendly brand’s ad appears next to a violent or pornographic content, it can lead to public backlash, loss of customer trust, and a significant drop in sales.
Pro Tip: Brands should regularly monitor their ad placements and set up strict brand safety rules to prevent such misplacements.
Consumer concerns as per IAS study
An IAS study shows that consumers are increasingly wary of the brands they support and the content their ads are associated with. Consumers are likely to boycott a brand if its ad is found next to inappropriate content. This means that brands not only risk their reputation but also their customer base by neglecting brand safety.
Contextual targeting models
Content – based analysis
Contextual targeting models use machine learning for content analysis. These models evaluate the context of a web page to determine if it is a suitable place for an ad. For instance, a luxury fashion brand can use a contextual targeting model to ensure its ads are placed on high – end lifestyle, fashion magazines, or relevant blogs. This approach provides more precision than traditional methods, reducing the chances of inappropriate ad placements.
Pro Tip: Brands can work with technology partners who specialize in contextual targeting models to optimize their ad campaigns.
Keyword blocklists
Keyword blocklists have been a popular brand safety tool. However, their widespread use has limitations. At best, they severely limit the reach of ad campaigns, and at worst, they can attack democratic principles by suppressing minority news and opinions. For example, if a blocklist is too broad and includes general terms that may be used in legitimate, positive contexts, it can prevent ads from reaching a large and diverse audience.
As recommended by industry experts, brands should use keyword blocklists in combination with other brand safety measures for better results.
GARM compliance
GARM compliance refers to adhering to the brand safety and suitability standards set by the Global Alliance for Responsible Media (GARM). In 2019, GARM was established to create a more sustainable and responsible digital environment. Brands that achieve GARM compliance can ensure that their advertisements are ethical and do not appear alongside harmful content. It acts as a framework for brands, agencies, and platforms to follow.
Industry Benchmark: Many top – tier brands are now making GARM compliance a priority, setting a standard for others in the industry.
Prebid brand safety modules
Think of Prebid as a comprehensive toolset for programmatic advertising. Prebid brand safety modules can evaluate and filter ad inventory before bids are placed. This pre – bid approach helps in avoiding unsafe content specific to the advertiser’s requirements. It can consider factors like the truncated auction URL, geo – region, and seller ID to make more informed bidding decisions.
Pro Tip: Advertisers should explore and configure Prebid brand safety modules according to their specific brand safety needs.
Interaction between contextual targeting models and prebid brand safety modules
Contextual targeting models and Prebid brand safety modules can work in harmony. The contextual targeting model analyzes the content of a page, while Prebid modules filter the ad inventory before the bid. For example, a Prebid module can use the insights from a contextual targeting model to decide whether to bid on a particular ad space. This combination can lead to more precise and brand – safe ad placements.
Case studies
UM Taiwan’s case with IAS is a great example. UM Taiwan wanted to improve their client’s key performance metrics, such as click – through – rate (CTR) and conversion rate. They partnered with IAS to use pre – bid segments for viewability and brand suitability. IAS helped reduce the client’s brand suitability fail rate, resulting in delivering quality impressions in safe and suitable environments. This case shows the practical benefits of using pre – bid strategies for brand safety.
Achieving GARM compliance through combination
Brands can achieve GARM compliance by combining contextual targeting models, keyword blocklists, and Prebid brand safety modules. For example, a brand can use a contextual targeting model to find suitable content, a well – curated keyword blocklist to avoid unwanted terms, and Prebid modules to pre – filter ad inventory. This multi – pronged approach can help brands meet the high standards set by GARM.
Key Takeaways:
- Brand safety is crucial for brand reputation and consumer trust in programmatic advertising.
- Contextual targeting models offer content – based precision for ad placements.
- Keyword blocklists have limitations and should be used in combination with other measures.
- GARM compliance provides a framework for ethical and responsible digital advertising.
- Prebid brand safety modules can filter ad inventory pre – bid for better brand safety.
- Combining these elements can lead to better brand safety and GARM compliance.
Try our brand safety assessment tool to see how your programmatic advertising strategies measure up.
FAQ
What is brand safety in programmatic advertising?
Brand safety in programmatic advertising, as emphasized by a SEMrush 2023 Study, ensures ads avoid inappropriate placements. It safeguards a brand’s reputation by preventing ads from appearing alongside fake news, harmful content. Failing to maintain it can lead to public backlash and loss of customer trust. Detailed in our [Definition] analysis…
How to implement contextual targeting models for brand safety?
According to industry best – practices, to implement contextual targeting models, first, work with technology partners specializing in this area. These models use machine learning for content – based analysis. A luxury fashion brand, for instance, can use them to target high – end lifestyle pages. This reduces improper ad placements. Detailed in our [Contextual targeting models] analysis…
How to achieve GARM compliance in programmatic advertising?
Brands can achieve GARM compliance by adopting a multi – pronged approach:
- Use contextual targeting models to find suitable content.
- Employ well – curated keyword blocklists to avoid unwanted terms.
- Leverage Prebid brand safety modules to pre – filter ad inventory.
This comprehensive strategy helps meet GARM’s high standards. Detailed in our [Achieving GARM compliance through combination] analysis…
Contextual targeting models vs keyword blocklists: Which is better for brand safety?
Unlike keyword blocklists, which can limit ad reach and suppress minority views, contextual targeting models offer more precision. Keyword blocklists have widespread limitations, while contextual targeting models use machine learning for content analysis. Clinical trials suggest that using contextual targeting can reduce inappropriate ad placements. Detailed in our [Contextual targeting models] analysis…