Programmatic native advertising is on the rise.
It is a method for integrating marketing assets and messages into a publisher’s feed. Native ads purchased and placed programmatically enable brands to capitalise on increased relevance and personalisation. Machine learning and contextual signals enable programmatic native ads to be tailored to the user, resulting in improved performance for advertisers.
According to the report, 1,900 advertisers invested $2.6 billion between January and May 2021. Compared to 2020, when 926 advertisers spent $1.9 billion, it is clear that advertisers prefer native advertising to be automated to maximise scale and efficiency.
However, the expansion of programmatic trading threatens brand safety, with some environments risking negative associations between buyers and sellers. In one recent case, the Washington Post and New York Magazine unintentionally featured porn from an adult network’s video platform Vidme, which the publishers were using to fix additional video content.
Brand safety has always been a concern in digital advertising, but it is essential for native ads. When seamlessly integrated into their environments, ads strengthen the bond between brands, publishers, and the content on the page. Quality, relevance, and suitability are essential for maintaining and strengthening a close customer relationship.
To protect their reputations and identify optimal native placements, brands should take the following steps.
Select your partners carefully.
Choose ad networks prioritising media security for programmatic and non-automated native ads and continually monitor quality. These trusted ad networks are the foundation for private marketplaces (PMPs), where brands can find a consistent portfolio of premium publishers.
PMPs create a direct, transparent connection between the buy and sell sides, making advertisers confident that available media has been vetted and meets their messaging and values.
Brand safety necessitates careful selection of trading partners and native placements; however, how can buyers ensure they are not limiting their options?
Advertisers commonly use blocklists, allowlists, and keyword blocking to give them specific control over the content surrounding their advertisements. These have risks despite their high value, particularly when combined with other verification methods. Advertisers must be prepared to act proactively to avoid missing out on unexpected opportunities.
For example, the rise in misinformation in 2020 prompted many brands to exercise caution when advertising around Covid-19 content. The pandemic was high on the news agenda, so brands reduced the size of their campaigns when not all content was safe. Authoritative, optimistic, and educational content resulted in positive associations for specific brands.
To take advantage of these opportunities, brands should use tools to identify native placements that are safe and highly appropriate. Artificial intelligence powers advanced contextual technologies that can perform natural language processing (NLP) and semantic analysis. This technique extracts meaning from sentences and words based on grammatical structure, allowing for context categorisation and sentiment measurement.
Thus, contextual targeting ensures that environments and advertising content complement one another, improving brand messaging and engaging receptive audiences. Brands can then make more informed decisions about the suitability of native placements for their brands.
Make sure to ask the right questions.
Before deciding how to mitigate risk, brands should consult with an agency or partner and ask three key questions:
What kind of protection does your solution provide for my brand?
Brands’ values, objectives, and target audiences differ, so one-size-fits-all solutions could be more effective. As a result, brands should look for partners whose tools support custom brand safety criteria. They can then decide which media is most appropriate and relevant to their products or industries.
Are you able to prove that the technology works?
Proven success is critical when choosing the right partners and tools to mitigate risk. Partners should show, for example, how advanced brand safety technologies like semantic analysis and natural language processing increase engagement rates. The NLP market is expected to grow from $3 billion in 2017 to more than $43 billion in 2025; where there is investment, there is value. As a result, you should enquire about the outcomes of your partners who use these technologies.
What impact will your technology have on my reach?
A brand’s safety is complex, and the technologies used to protect it must reflect this. Understanding linguistic complexities and reading content like the human brain will allow brands to maximise their reputation through relevant and appropriate native placements. Reaching target audiences in a safe environment should imply a manageable reach.
Brands must ensure their digital advertising complements existing content and meets audience expectations. The success of native placements is determined by how well ads are integrated into the user experience.
Conclusion
An automated approach can improve efficiency, but brands should use brand safety tools and must develop a customised strategy to determine brand suitability and connect with ad-weary audiences. For native advertising to be effective, brands must collaborate with trusted ad networks, discuss brand safety criteria with their partners, and implement technologies that detect brand-safe placements. Doing so will improve their reputation by delivering relevant and engaging messages in a secure and optimal setting. Brands that use mFilterIt’s Brand Hygiene Protection can increase their relevance, revenue, and target audience. This solution helps to keep advertisements away from dangerous environments, fraudulent affiliates, and untrustworthy publishers.
