invalid traffic

Digital Advertising Ecosystem

Need For Frequency Capping and Transparency in The Digital Advertising Ecosystem

Reach and Frequency are the two key metrics on which the success of a brand campaign hinges. It’s like instead of conveying your message to 50 people 2 times, you are just sharing the same message 5 times to just 25 people. That results in more impressions but less reach. Therefore, ensuring frequency caps are enforced becomes paramount. So, are your ads getting served to the same audience too many times? Did you know a significant number of impressions are being served on a small number of devices? This challenge prevails across the OTT environments and other mobile app-based placements. This is simply due to a lack of cookie-based measurements on these (cookies don’t work on apps). Let’s demystify the intricacies surrounding metrics like Reach and Frequency and unveil how monitoring frequency capping violations can not only enhance campaign performance but also instill trust in the audience. The Deceptive World of Frequency Measurement Traditionally, marketers have relied on Ad Servers for accurate frequency measurement. Yet, the intricacies within the digital space world present a different narrative. Cookies, which have long been the stalwart of web tracking, lose their efficacy, necessitating a shift to more elusive identifiers like Device ID (Google Advertising ID or IDFA) which can be triggered by the publisher platforms (apps and OTTs). Here is an example of a recent campaign on a LEADING OTT player for a leading meat and seafood brand. As you can see 76.70% of the impressions were violating FCAP thresholds, which means that roughly half of the consumers saw the campaign much more than the required frequency. Another interesting angle is that as the campaign becomes longer, the FCAP violation keeps increasing. Within 11 days it was 76.62% but in the second part of the campaign, it increased to 83.82% in just 3 days [Ref. Fig:1.1]. This means that if you have a longer-running campaign, your control on FCAPs becomes lower and the campaign ends up reaching the same set of audiences. Fig 1.1: F-breach detected for Advertiser #1 Advertiser #1, utilizing a DSP, believed in the presumed capabilities of the publisher. When this is broken down with Device ID-wise numbers, you can see that some consumers saw the ad 15,145 times. Compared to the client threshold of 3, this is a MASSIVE violation of the cap. Imagine the consumer who saw the same ad 15,145 times! The person might remember the brand, but maybe not in a very friendly manner. Fig. 1.2: Top Device ID Frequency Observation What did the DSP’s FCAP report show? It masked this reality, showing an average of 3, leading to wasted ad spend and irritated consumers. Why? Since they didn’t consider Device ID as the parameter (even though it was passed) but used IP. User Agent as a way to measure FCAP. Also, they reported on AVERAGE FCAP which is misleading and doesn’t show the spread of the wastage. The Problem Seen by All Fig. 1.3: Findings by Fou Analytics The problem of frequency violations prevails and can be attested as a genuine issue in the digital ecosystem. According to an analysis done by FouAnalytics, there have been grave scenarios where invalid traffic was seen loading ads and taking active measures to defeat frequency capping. Bots are detected to be rotating device IDs and cookies to trick the ad servers into serving more ads to the bot. And the number of times bots see an ad is surprisingly shocking. As per the findings, there have been instances where as many as 342 times an ad is seen by a bad bot. [Ref to Fig:1.3] Thereby, Frequency Capping intelligence emerges as a critical solution. It serves as a safeguard against overexposure, preventing users from being bombarded with the same ads repeatedly. The efficacy of this practice, however, relies on advertisers actively engaging with publishers and fostering a transparent ecosystem for advertising on Mobile app platforms. Solution to Frequency Capping in Mobile App Platforms One effective strategy involves tracking Google Advertising ID (GAID) and device ID to validate genuine users and identify frequency capping violations. At mFilterIt, we set a VAST tag-based campaign where in real time the VAST requests which were violating the threshold were blocked and the wastage controlled. Here in another case of a leading consumer goods brand, the publisher tried to push up to 10% of requests which violated the FCAPs, but due to VAST request blocking in real-time, the campaign was protected and impressions were prevented on repeat users, money was saved and the campaign performance improved. Table 01: A multination consumer goods company ads on a social networking/short video platform The mFilterIt ad fraud solution also identifies the trends in VAST distribution trends and request blocking trends along with impressions distribution by location and impression and event trends. Way Forward As the digital advertising landscape continues to evolve, the need for frequency capping and transparency becomes increasingly apparent. Navigate the complexities of the app-based ecosystem and ensure that campaigns are not only impactful but also delivered with integrity and transparency across the digital ecosystem.

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Can Ad Fraud Detection Stop Your Brand’s Growth? Know the Truth

Ad Fraud is a term that has shaken the entire digital advertising ecosystem in the past decade. Every year, fraudsters are becoming sophisticated and smart in stealing revenue from advertisers. Whether it’s advertisers, publishers, or ad networks, no one is safe from the threats of cybercriminals. The legitimate publishers get their genuine clicks stolen by fraudsters. Whereas the ad networks have to see their performance suffer and campaigns fail. And the worst of all happens with the advertisers as they pay for both invalid users and organic downloads. In this fight between the fraudsters and the digital marketing ecosystem, myths make the advertisers question the ad fraud detection vendors while the fraudsters feed on their money. Here is another myth that is making noise lately. In this blog, we are busting this myth with some facts which will help you understand the importance of an ad fraud detection software. What is cooking? In the digital advertising world, publishers are spreading the word that they are not able to scale an advertiser’s business due to ad fraud detection solutions. However, the reality is different Publishers lose a high percentage of their revenue due to ad fraud detection solutions. For instance, if an ad fraud preventive service provider detects 70% of fraud coming from a specific source, then that particular publisher receives a payout on just 30% of the genuine traffic by the advertiser. Publishers & MMP union Some of the renowned Mobile measurement platforms (MMPs) also offer ad fraud detection services clubbed with their attribution services. They claim that they will detect fraud in the data attributed by them to an app advertiser and ensure that they receive clean traffic. However, there is a catch. The MMPs bill the advertisers based on the number of attributions. Hence, if the MMPs detect a higher number of frauds on the attributed data, they will lose revenue. Therefore, to ensure that their revenue is not impacted, the MMPs detect 10-12% of the fraud and the rest of the fraud remains undetected. This benefits the MMPs and the publishers as they can claim higher payout from the advertisers. As the MMPs detect low fraud, the publisher encourages the agencies, advertisers, and other stakeholders to use the MMP ad fraud detection as it will eventually benefit them. This is similar to a situation where the culprit is telling to choose where to go and file a complaint to keep themselves safe. And listening to this, the advertisers fail to detect the real fraud and end up losing huge revenue. What do advertisers miss? Real % of Fraud: Due to less fraud reporting by MMPs, the advertisers remain in the dark regarding the actual fraud numbers. This further affects the performance of the ad campaigns, and the advertisers end up losing money twice to invalid traffic. First, they lose money to the invalid traffic before ad fraud solution. Later, they end up losing money on invalid traffic that is not reported by the MMPs. Growth Opportunities: The advertisers use an MMP to measure the performance and get analytical data for their campaigns. However, due to less fraud reported by MMPs, the marketers stay under the impression that their campaign performance is good. Furthermore, as the marketer takes decisions based on this skewed data, they end up investing more in the wrong campaign. This further hampers the overall growth of the business. mFilterIt Vs MMPs In comparison to the fraud detection done by MMPs, we ensure holistic protection of advertisers from ad fraud. Our ad traffic validation suite enables: Full-Funnel Protection MMPs can detect the general bots, but they often miss to detect the signs of sophisticated bots in an ad campaign. As sophisticated bots can easily mimic human behavior, they are hard to detect and require an advanced solution. With our full-funnel approach, we detect sophisticated bot patterns in real-time to help advertisers take immediate action to curb the impact. Detect New Bots Across Domains Every day a new bot is coming, and it is hard to detect across all platforms and domains. MMPs often lose the time to respond to the threats as their systems and rules are updated once in 6 months or a year. Whereas we detect a new bot on any campaign, we ensure to flag it across all the advertisers/campaigns. This results in the protection of ad campaigns from the impact of the new bot. Proactive Reporting The attribution platforms provide a late ad fraud report to the advertisers. This means that if the ad fraud is detected by the 20th of a month, then the advertisers will receive the report on the 28th of that month. This further delays the process of taking preventative measures against fraudulent sources. Furthermore, it also affects the invoicing and closures at the end of the month, and even after taking so much time they fail to detect the right number of fraudulent sources. Whereas we provide D-1 data, which means that if the fraud is detected by the 20th of the month, the advertiser gets the report on the 21st of the month. This helps the advertiser to understand the possible impact of the ad fraud and take preventative measures immediately without wasting further ad spends on irrelevant traffic. Early reporting also helps publishers to optimize better and reduce the threat of fraud. Forget the Myth, Believe in Facts With the fast-growing world of digital advertising frauds are making their every move smarter, more discrete, and an illusion to the naked eye. To ensure your marketing efforts are not wasted, it is important to fight against fraudsters with an advanced ad traffic validation solution. A reliable ad fraud detection and prevention solution will help to detect fraud in real time and provide holistic protection against sophisticated bots without impacting your growth. The only party affected is the publishers as their pay-out decreases when an effective ad fraud tool is in place. It’s time to believe the data, not the myths. Get in touch with our experts for deeper insights. Reach out to learn

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You Asked, We Answered: Most Searched Questions About Ad Fraud

Whether you’re an advertiser, publisher, or user, it is natural to have questions about the growing threats of ad fraud. As the digital marketing world is moving ahead, the fraudsters are also becoming smart and coming up with new techniques to defraud marketers. Just like taking preventative measures against ad fraud is important, it is also essential to stay updated with the terms and techniques fraudsters are using. To ensure this, we have covered the most searched questions about ad fraud to help you understand the nitty-gritty of the techniques and tools used by fraudsters. Get ready to binge-read! What is ad fraud? Ad fraud is an attempt to defraud advertisers to steal money and manipulate their data with invalid traffic. The fraudsters usually use bots to perform ad fraud and trick the advertisers into thinking they are getting genuine users. As a result, the advertisers lose their ad revenue on invalid traffic. Furthermore, seeing the inflated traffic the advertisers think their ad campaigns are working and continue to invest in bot-impacted ad campaigns. According to a Juniper Research report, ad fraud is estimated to cost up to $81 billion by the end of 2022. What is bot traffic? Bot traffic consists of automated traffic coming from bots instead of humans. Every traffic generated from bots is not always fraudulent. Sometimes the search engines send bots to crawl the websites for ranking purposes. However, bot traffic is a concern when it is used as a carrier of ad fraud. Often called SIVT or sophisticated invalid traffic. The bad bots manipulate the data of an ad campaign and commit types of ad fraud like SDK spoofing, fake clicks, and fake installs. How to detect bot traffic? Some of the common ways to detect bot traffic that can be identified on websites, apps, and APIs are: Abnormally high pageviews Abnormally high bounce rate Inflated traffic from unknown locations Abnormal session durations High number of junk conversions What is Impression Ad Fraud? Impression means the total number of times an ad was displayed regardless of whether the ad was viewed or not. Impression fraud happens when the fraudsters create a fake website and list themselves on an ad exchange. When an advertiser buys an ad inventory on these websites, they generate impressions with the help of bots. The inflated impression numbers make the advertisers believe that their ad campaign is getting traffic. Wherein, the reality is that the ads are attracting bot traffic, and the fraudsters are getting money for invalid traffic. What is Ad Stacking? This is a type of mobile ad fraud where the fraudsters ‘layer’ or ‘stack’ multiple ads above one another in single ad placement. While just the top ad is visible to the user, the impression or click is registered for all the ads stacked beneath each other. This further lead to advertisers paying for a fake impression or click. What is VPN Proxy Click Fraud? A VPN is used to create a new IP address and mask the original location of a person. This is a strong tool for fraudsters to hide their tracks of ad fraud practices. With the help of a VPN proxy, they create a new IP address which helps them to keep themselves hidden from the ad fraud detection solutions. The fraudsters use this technique to mask their device location and commit fraud. What is Fake Attribution? A fake attribution is a practice followed by fraudsters to steal the credit of an organic install by reporting a fake click as the last engagement. Being the “last-click attribution”, the attribution platforms consider a fake click as an organic click. Usually, a fake attribution is triggered with a help of malware that comes along when a user installs an app from an unknown source. The malware helps to track the user’s activity and notifies the fraudster when the app install starts. The malware search for the relevant information and populates into a fake click report to register as the last click engagement and gets the attribution for an organic install or one generated by a media partner. What is cookie stuffing? This is a technique used in affiliate marketing fraud where a fraudulent affiliate fools the advertiser into thinking that they have sent traffic to their website. But in reality, they haven’t sent any traffic. This practice is also known as cookie dropping and is one of the commonly used techniques in affiliate marketing. By fooling the advertiser, they get the commission for sending a user to their website. Furthermore, the advertiser is wasting money and getting no users in return from their affiliate campaigns What is Ad Pixel stuffing? The technique of pixel stuffing happens when fraudsters place an ad or an entire website inside a frame of 1×1 pixel using an iframe. This makes it invisible to the human eye. When a normal ad runs, the impressions are tracked for the legitimate ad, as well as the ads that are stacked under the invisible pixel. In this way, the fraudsters receive compensation for those fake impressions. Furthermore, they also use bots to generate fake impressions with the pixel-stuffed ads and drain the advertiser’s budget on invalid traffic. What is Incent Fraud? This is a type of fraud where the fraudulent affiliates run non-incent campaigns on incent platforms. Due to this, they attract low-quality users that install only for incentives and have no interest in the actual app. This technique is usually used to increase the install volumes, fix low CR ratios, moderate the quality of user acquisition, or simply increase the margins. What is Click Injection? This is a sophisticated form of click-spamming which is majorly prevalent in android devices. When a user downloads a malicious app, they allow the fraudsters to detect when any other app is downloaded on a device. Once they know that, fraudsters trigger a click before an install is completed. As a result, the fraudster receives a credit for the install that appears legitimate and results in a CPI payout from the advertiser. What

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