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How advanced technology will help video advertising thrive in a cookieless future
January 27, 2022
Data never sleeps and is collected every minute of every day to personalize online experiences. However, the online world is changing. Google’s support of third-party cookies and behavioral targeting will end by the end of 2023, and Apple is already giving users the option to 'opt in' to data tracking rather than opting out. So what does this all mean for the future of online advertising campaigns? And more importantly, why do advertisers and brands need to embrace modern technology?
Video content is still king
The appetite for video content is insatiable, and demand is growing.
According to the 2021 WyzOwl marketing statistics, 86% of businesses use video as a marketing tool, a 41% increase since 2016. Users watch, on average, 18 hours of video content each week, and more than two-thirds prefer watching a video to learn about a product or service.
Video content is an indispensable, multi-purpose ad format that can boost brand visibility, spark customer interest in any industry and increase conversions for any product or service.
There are two major types of video content:
- Attraction - the goal of these videos is to broaden the audience and build trust. A video that will garner shares is likely to be funny, entertaining, or evocative. In addition to entertainment, attraction videos should provide enough information for consumers to associate with your brand as an authority. Examples include snackable social videos, thought-leadership videos, and videos that showcase a brand's values and share the story.
- Branded – these videos can be highly targeted to specific audiences and include product demonstrations or instructional videos. They can be helpful for both companies and consumers, and it is not essential to have the best quality to attract viewers.
Why the loss of cookies is not a deal breaker
By removing third-party cookies, marketers will lose the ability to segment audiences according to what resonates with their audience. Additionally, it will also affect the accuracy of measurement, remarketing, and the effectiveness of advertising efforts.
This means that marketers and their branding campaigns will need to generate more first-party data, and one of the best ways to do this is through video advertising.
For campaigns to be successful, advertisers will need to adapt their first-party data strategies to keep the data-driven environment going, especially when it comes to the branding aspects of campaigns that raise visibility.
In the cookieless future, advertisers will also need to depend on contextual marketing, which relies on AI to pinpoint messaging to match the content of both ad and website.
The result will be more effective and profitable ads, which are more relevant to the viewer's interests.
The advantages of first-party data
While third-party data allows businesses to build brand awareness, the use of first-party data is vital to the success of any organization.
First-party data can be gathered through various channels, including:
- Online channels;
- Mobile apps;
- Interactions with digital ads;
- Offline data*
* Offline data collection requires additional effort to integrate it with digital customer data platforms.
By tracking and analyzing visitors' behavior, identifying which content they enjoy, and determining their lifetime value, advertisers can establish the best way to target customers and improve customer engagement by tailoring content and advertising to their specific interests.
For example, by collecting and analyzing first-party data consumer habits, a marketing team can determine which type of content is most effective, and once they know what their audience wants, they can refine their campaigns accordingly.
Technology changes everything
There is no better time for advertisers to implement new technologies and tactics for their video-based marketing campaigns than now.
Deep learning is a true game-changer because it makes use of large sets of unstructured data to solve complex problems. By using data models and advanced algorithms, deep learning can understand human decisions and predict future actions based on online behavior and improve visibility within the same budget. It ensures that whatever we do, ads are bought in the most efficient way according to the ad's end goal.
By identifying a customer's browsing habits, deep learning helps advertisers become better customer journey orchestrators when it comes to sequential targeting. Using the data from deep learning, advertisers can identify specific touchpoints in the user’s interactions with the brand, to create an advertising strategy that, when executed, will make video ads more effective. For example:
- Tease - short video formats tease the message to raise awareness and generate interest in the full message
- Make a noise - full video reveal the entire message and amplify it with complementary display ads
- Follow up - once the video campaign has ended, in-banner ads make sure brands stay in touch with the users to fully capitalize on the interest generated
With deep learning, multiple targeting strategies can also be supported, including contextual, behavioral, and demographics, that adjust content to the preferences of the target group. For example, different creatives can be used based on target group interest; sporty and exciting SUVs for active persons and safe and reliable family cars for parents.
This will ultimately improve the quality of digital marketing campaigns.
However, the best thing about deep learning is that it can learn from actions and improve over time.
It’s time for advertisers to embrace the future
In the cookieless future, it will still be possible for brands to reach their goals, raise their brand visibility, engage with the right audience, and send the right message to the right person at the right time.
Results have shown that campaigns utilizing deep learning perform up to 50% better than those using standard machine learning approaches.
Now is the time for brands to investigate and try new solutions for their video ads before the proposed changes become a reality.
Change is hard. We know that. But being left behind is worse.
RTB House’s deep learning experience
Our proprietary artificial intelligence engine and deep learning algorithms have been working hard since 2017. We actively use deep learning algorithms in 100% of our campaigns, and to date, it has been used in more than 3,000 campaigns in over 70 markets, delivering for some of the world’s biggest brands and over 270 of the most renowned media agencies.
To discover how you can benefit from our expertise, and how our approach can help you get the most out of your marketing campaigns in a cookieless future, contact RTB House today.