Pixalate spoke with Jess Okan, CEO and Co-founder of Screencore, about strategies for minimizing ad fraud in the connected TV ecosystem.
Jess is the Co-founder and CEO of Screencore. Before launching Screencore, Jess enjoyed 5+ years of experience at GothamAds, where he pioneered new developments and innovations, helping them to become a global player. After that, he wanted to try doing something 'different and also difficult' which led to the creation of his company, Screencore.
Jess: Screencore is an AI and machine-learning-based online media solution that is designed to help our publishers and advertisers cover most of their programmatic needs with less workload but with more efficient outcomes. Our goal is to provide the most robust digital advertising platform that a programmatic media company can offer. It's no secret that publishers are looking for the right campaigns for their audiences and brands obviously need authentic as well as real consumers for their campaigns. Screencore is positioned in the center of this industry to provide that necessary online media platform.
Even though we launched our platform less than a year ago, thanks to the great expertise behind it, we started growing our impact in the market exponentially with the right approach and smart marketing. Because, most of our co-founding partners, developers, sales, and marketing teams have a long history in the programmatic advertising ecosystem and are knowledgeable professionals. Because owing to our expertise and grasp of this field, we knew how to start and what to do. Therefore when we decided to build this idea we asked this question, "How can we do it better?" We believe that we are on the right path to answer this question.
Jess: Despite the fact that CTV ads have been around for 5+ years, I believe the Connected TV environment still is a new world and it's vulnerable to many new threats. That's why we keep seeing new fraudulent tactics and methods to undermine our efforts almost every day. The only way to avoid this is to rely on a trusted partner because it's a key factor to fight the fraudsters in our business efficiently. This is where Pixalate stepped in to cover our back. Pixalate helped us to identify what we were doing right or wrong and pointed out the solution. In a short period of time, we successfully removed and blocked the bad elements from our platforms with the help of Pixalate's following features:
Analytics Dashboard: Pixalate's UI is probably the most user-friendly, simple, and detailed platform you can find out there. Pixalate detects and reports more than 40 types of invalid traffic not only from the publishers' sides, but also from the bidding advertisers, device types, ad formats geolocations, etc., and it indicates the result right on the dashboard. After this point, the only thing you need to do is to remove the malicious sources from your platform. It's that easy.
Versatile Scanning Capabilities: Pixalate is able to scan all ad formats and inventory types that we work with across all the screens and devices, such as banner, video, CTV, native, rich media, display ads, and so on. Although we primarily focus on in-app banners/video and Connected TV inventory, having a versatile IVT detection tool is a big plus for us. It allows us to explore different ad formats and screens without worrying about compatibility issues.
Jess: From November '22 - March '23, we saw IVT levels decrease by approximately 70%. This decline in IVT can most likely be attributed to Pixalate's detection system, Analytics which is designed to identify and allow the blocking of suspicious or fraudulent traffic. Pixalate's software can analyze traffic patterns, detect anomalies, and distinguish between legitimate and fraudulent activities more accurately.
Another important factor has been our overall partnership with Pixalate which has led to greater education and awareness of IVT internally at Screencore, which has increased our overall vigilance.
Jess: Our Screencore team is sure that a combination of technological innovations, changing consumer behavior, and evolving regulations and policies will likely shape the future of CTV advertising. Advertisers staying on top of these trends and adapting their strategies are likely best positioned for success in this rapidly evolving landscape. Here are some of the most influential trends that are likely to have a significant impact on the future of CTV:
The rise of streaming services
Streaming services such as Netflix, Amazon Prime Video, and Hulu are becoming increasingly popular. CTV advertising is expected to grow as more viewers turn to streaming services for entertainment. These commercials can target specific audiences based on their viewing habits and demographics. Streaming TV advertising allows advertisers to reach viewers watching live TV and on-demand content, offering new opportunities to reach a wider audience.
Eye tracking and facial recognition for more accurate targeting
This technology allows for even greater targeting at the individual level within the household. Currently, CTV is limited to targeting households due to restrictions such as shared accounts, but this is getting better with facial recognition. It will allow for that extra layer of sophistication when optimizing ads beyond the contemporary standard of who is logged in and what is being watched. Not only will marketers be able to deliver campaigns based on who in the household is watching, but they will also be able to measure who in the household is most engaged.
Voice command for ad engagement
Voice recognition and voice command will change the future of ad engagement. Just imagine you can say, "Hey Siri, can you order me that roller massage that was just on the TV? My back has been hurting for three days". It will help you to maintain an effortless lifestyle with lots of opportunities. People want convenience at every shopping stage – voice command will allow that.
Cross-platform advertising and retargeting
As CTV gains popularity and consumers increasingly use mobile devices, desktop computers, and wearable gadgets such as smartwatches, fitness trackers, and smart glasses, advertisers seek methods to connect with consumers across various platforms. Consequently, cross-platform advertising initiatives are expected to become more widespread, providing consumers with a more cohesive advertising experience. Consider identifying a potential customer who has watched a CTV advertisement to the end and is currently shopping at a mall near a retail location of the advertised brand. How would your advertising strategy shift if you could present a location-based triggered advertisement on their smartwatch?
ML-based creative optimization
Machine learning can greatly boost CTV advertising: contextual engines that monitor the metadata sources and recommend the best music, visual material, and messaging tactics to approach a viewer. These technologies can revolutionize CTV by extending the shelf life of video ads and automatically allowing them to be customized on the fly for specific audiences.
Jess: According to PwC's Global Economic Crime and Fraud Survey 2022, fraud losses are the highest in twenty years of research. The Association of Certified Fraud Examiners estimates that organizations lose five percent of revenue to fraud each year, and the average loss per case is $1,783,000. Screencore has key benchmarks which help mitigate ad fraud and champion a cleaner CTV ecosystem. Here are some of them:
Disclaimer: The content of this page reflects Pixalate’s opinions with respect to the factors that Pixalate believes can be useful to the digital media industry. Any proprietary data shared is grounded in Pixalate’s proprietary technology and analytics, which Pixalate is continuously evaluating and updating. Any references to outside sources should not be construed as endorsements. Pixalate’s opinions are just that - opinion, not facts or guarantees.
Per the MRC, “'Fraud' is not intended to represent fraud as defined in various laws, statutes and ordinances or as conventionally used in U.S. Court or other legal proceedings, but rather a custom definition strictly for advertising measurement purposes. Also per the MRC, “‘Invalid Traffic’ is defined generally as traffic that does not meet certain ad serving quality or completeness criteria, or otherwise does not represent legitimate ad traffic that should be included in measurement counts. Among the reasons why ad traffic may be deemed invalid is it is a result of non-human traffic (spiders, bots, etc.), or activity designed to produce fraudulent traffic.”