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Are your ads on OTT causing Ad Fatigue? Know the Impact of Frequency Capping Breach

Blog, Ad Fraud /

Digital advertising has undergone a massive transformation. As audiences shift from traditional TV to streaming platforms, brands have gained unprecedented opportunities to engage with consumers in a more targeted and cost-effective way.  Enter Over-the-Top (OTT) platforms like Netflix, Hulu, Amazon Prime Video, and JioHotstar—which have changed the advertising game. These platforms allow brands to serve personalized, data-driven ads to the right audience at the right time.  But there’s a catch. What happens when an ad is shown too many times? Instead of boosting brand recall, excessive exposure leads to annoyance, ad fatigue, and a frustrated audience that starts tuning out the message altogether. This challenge is known as frequency cap breaching—a problem advertisers must solve to maintain engagement without overloading users.  Let’s explore what frequency capping is, why it matters, and how mFilterIt is helping brands optimize their OTT ad strategies.  What is Frequency Cap Breaching? Frequency breaching occurs when an ad is shown to the same user excessively, far beyond the optimal number of exposures. While repetition plays a crucial role in brand recall, too much of it leads to ad fatigue, causing frustration and making users disengage.  Effective frequency capping ensures that users aren’t served the same ad too many times within a short period. This enhances ad effectiveness, prevents irritation, and maintains a positive viewing experience. However, finding the right balance requires data-driven decision-making, continuous testing, and collaboration with advertising platforms. Why Does Frequency Capping Matter? Imagine watching your favorite show on Hotstar or Zee5, and suddenly, the same ad plays multiple times within a single episode. Annoying, right? This is where frequency capping comes in.  By limiting ad repetition, frequency capping ensures:  Better user experience by reducing ad fatigue  Higher engagement rates as viewers remain receptive to brand messages  Optimized ad spend by ensuring the right exposure levels  That’s where mFilterIt plays a crucial role—acting as the behind-the-scenes expert that ensures ads are displayed optimally without overwhelming the audience.  mFilterIt’s Role in Frequency Capping  As OTT advertising continues to evolve, mFilterIt leverages advanced technology to ensure optimal ad exposure. Here’s how it helps: 1. Device ID Analysis mFilterIt analyzes device IDs from OTT platforms to monitor ad repetitions. This allows advertisers to identify and address frequency cap breaches effectively. 2. Personalized Ad Experience By refining targeting strategies based on real-time data, advertisers can serve relevant ads to the right users at the right time, creating a more engaging experience. 3. Optimized Ad Strategy The insights provided help advertisers fine-tune their campaign strategies, preventing excessive ad exposure while maximizing engagement. 4. Transparent Reporting Findings are shared with publishers, enabling them to take necessary actions, such as blocking certain device IDs that breach frequency caps. This ensures a healthier and more balanced ad ecosystem.  The graph shows how frequently a specific device ID repeats at various times. Each point on the graph corresponds to a specific time, and the numerical value associated with the point indicates the exact count of repetitions of the device ID at that time. For instance, if the numerical value is higher at 00:54, it signifies that the device ID repeated more times during that specific time period. In essence, the graph visually represents the specific counts of repetitions for the device ID across different time points.  Way Forward For advertisers, the goal isn’t just visibility—it’s also about reaching the right audience and genuine engagement. Overexposing users to ads does more harm than good.  With mFilterIt’s cutting-edge ad fraud solution, brands and publishers can ensure a smoother, more effective ad experience.  Want to optimize your OTT advertising strategy and prevent ad fatigue? Get in touch with mFilterIt today! 

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Pop-Under Fraud: The Hidden Leak in Your Ad Budgets

Blog, Ad Traffic Validation /

You’re investing heavily in digital advertising, expecting real engagement, quality traffic, and conversions. But what if a large portion of your ad spend is going to waste without delivering any real results? Pop-under fraud is a hidden threat that inflates your impressions, skews performance metrics, and leads to skyrocketing bounce rates—all while failing to bring genuine customers to your brand. These fraudulent ads load behind the main browser window, making it seem like your campaign is performing well when you’re paying for traffic that has zero intent to convert. The result? Misleading analytics, wasted budgets, and missed revenue opportunities. In this blog, we’ll break down what pop-under fraud is, how it affects your digital ad performance, and, most importantly, how you can prevent it from draining your marketing investments.  What is Pop-Under Fraud?  Pop-under fraud is a deceptive advertising practice where fraudulent ads appear behind the main browser window. These ads generate fake clicks and attract low-intent users who have little to no engagement with the website.   Key Signs of Pop-Under Fraud:  High impressions but low engagement (no clicks or conversions).  Traffic spikes from low-quality placements or unknown publishers.  Ads appearing in hidden windows or background tabs.  Sudden rise in bounce rates and bot-like activity.  Pop-unders can be further exploited for cookie stuffing, allowing unauthorized tracking without the user’s knowledge. This also raises brand safety concerns when the pop-under displays content unrelated to the user’s intent or triggers without any direct user action, such as a click.  We recently analyzed a campaign where pop-under traffic was unusually high, with most users coming from odd screen resolutions, a clear mismatch compared to the organic traffic trend. Who is Affected by Pop-Under Fraud? Advertisers, marketers, and businesses that invest in digital advertising are the primary victims. This fraud wastes ad budgets and provides misleading performance data, making it harder for brands to achieve real growth.  When Does Pop-Under Fraud Happen? It occurs when fraudulent methods like malware installations, ad stacking, and hidden redirects are used to serve ads in the background. This often happens in low-quality placements where user engagement is not genuinely earned.  Where Does It Happen?  Pop-under fraud can occur on various digital platforms, including websites with poor ad quality control and deceptive ad networks. It is more common in low-quality placements that do not prioritize transparency. This type of fraud leads to wasted ad spend, misleading performance metrics, and zero impact on brand engagement. It can also expose brands to reputational risks when their ads appear on unrelated or unsafe content.  How Can Advertisers Fight Back?  This section outlines three key strategies advertisers can use to combat fraudulent or ineffective ad placements and ensure their advertising budgets are well spent. Here’s a breakdown:  Use viewability tracking to measure real engagement and ensure ads are seen: Viewability tracking helps advertisers determine whether their ads are actually being viewed by real users.  Metrics like time-in-view (how long an ad remains visible on screen) and percentage of ad visible (e.g., at least 50% of an ad being in view for at least 1 second) help assess engagement.  This prevents advertisers from paying for impressions that are technically delivered but never actually seen by users.  Implement ad fraud detection tools to identify and blacklist suspicious publishers: Fraudulent publishers often use bots, click farms, or hidden ads to generate fake impressions and clicks, leading to wasted ad spend.  Ad fraud detection tools analyze traffic patterns to flag invalid traffic (IVT) and blacklist fraudulent websites or apps.  This ensures that ads are served only on trusted, high-quality platforms with real human audiences.  Analyze bounce rates and session durations to detect abnormal user behavior: Bounce rate refers to the percentage of users who leave a website after viewing only one page.  Unusually high bounce rates or very short session durations can indicate bot activity or accidental clicks, rather than real user interest.  Advertisers can use this data to refine their ad placements, optimize landing pages, and filter out sources that drive low-quality traffic.  Conclusion Pop-under fraud is a silent budget killer, deceiving advertisers with fake impressions and bot-driven traffic. If left unchecked, it can drain your resources and compromise your marketing success. The good news? You can take action today. Invest in ad fraud detection tool, monitor engagement metrics, and stay vigilant about where your ads appear. Don’t let fraudsters win—take control of your advertising strategy and ensure your budget drives real, meaningful results.   Ready to safeguard your campaigns? Start by auditing your traffic sources and implementing fraud prevention measures now! 

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osint technology

How a Real Estate Player Secured Its Digital Identity with OSINT-Powered Solution?

Blog, Brand Safety & Suitability /

Imagine this- a consumer goes online to find a real estate project where they can purchase a home. They start their search on a well-known search engine and come across results from some of the most reputed names in the real estate game in the country. They click on one of the sponsored results, look through the website, and shortlist a project that aligns with their needs. This prospect then fills out a contact form which subsequently leads to a call with the builder’s sales team. The salesperson informs the prospect that they will have to pay a small fee as an expression of interest in the project, to reserve their property. To incentivize the prospect, the sales rep even promises to offer them a competitive price that almost seems too good to be true. Considering the opportunity cost of not acting immediately, the prospect makes the expression of interest payment. However, they never receive any confirmation from the builder’s side and are never able to reach the sales rep again. This unsuspecting prospect has just fallen victim to a scam. While this scenario may seem far-fetched to some, it is an unfortunately frequent occurrence in the realm of digital ads and real estate. While the plight of the victim of the scam, the consumer is evident, the builders whose names are used to execute such scams stand to lose a lot more. For the builders, such instances translate into lost revenue, legal issues, and broken customer trust. To further cement the notion that this isn’t a made-up scenario, here’s a case study about one of our clients who was facing a similar predicament, and was able to get out of it with the help of Brand Protection Tool. Let’s find out more about this case: The Challenge: Why Real Estate Brands Are at High Risk Big real estate firms face an enormous yet hidden risk in the online realm. Scammers can employ a number of methods to dupe unwitting consumers while also tarnishing the name of the builder. Some of the most common ways scammers do this are: Fake Property Listings This is perhaps the most common and the easiest way for scammers to steal money from potential customers of real estate firms. Scammers create fake property listings on popular listing websites and use them to lure potential buyers. From this point, depending on how much they are able to influence individual buyers, scammers take money from them in the form of visitation charges to booking amounts for reserving a property for purchase at a later date. Impersonation & Brand Misuse This method is quite similar to the previous one, except with this, scammers are not limited to property listing websites. They may go one step further by creating fake social media profiles or even fake websites under the name of reputable real estate players. Using these, they can once again attract potential buyers and scam them. Intellectual Property Violations Real estate businesses have to publish a variety of documents when advertising a project. Since most such documents, such as floor plans and certificates are available in the public domain, they can be used by scammers to appear authentic in front of potential customers. Besides causing distress to buyers and potential customers, such practices cause a lot of damage to authentic and well-meaning real estate players. Consumers who fall victim to these scams often form the impression that the actual real estate business has tried to outsmart them. While clarification on the subject can change this notion, providing such clarifications to tens of customers every day can prove impractical. In fact, a similar reason is behind the widespread proliferation of such scams. Since it is impossible to manually track every instance of a brand’s name being used by a third party, especially in the case of big brand names, scammers take advantage of volume to outsmart vigilance. The Solution: AI-Powered Brand Protection for Real Estate While manual tracking cannot solve this problem, overcoming this issue is possible. With the Brand monitoring tool, such as the mFilterIt solution, real estate businesses can track and monitor instances of fraud and protect their prospects, customers, and most importantly, their brand image. At mFilterIt, we used the following brand protection features to help our client overcome the dangers of online scams: · Automated Digital Scanning: This feature is designed to detect fake listings, impersonations, and other forms of unauthorized brand usage. The AI-enabled feature does the tracking across platforms, including property listing websites, social media platforms, ad platforms, and even search engine result pages. · ML-Based Categorization: In severe cases, automated digital scanning can uncover hundreds, even thousands of instances of brand impersonation. Dealing with so many cases one by one can take a long time. With Machine Learning (ML) based categorization, mFilterIt helped by identifying and prioritizing high-risk cases for quick takedowns and bulletproof protection. · Confidence Scoring: Confidence Scoring is a feature that assigns a severity score to violations, based on the amount of risk they pose against the brand and its customers and prospects. · Data-Driven Enforcement: All of the data points collected using the previously mentioned features are presented in an easily digestible format on a central dashboard. This dashboard enables smart and quick decision-making, enabling brand managers to monitor their brand protection in real-time. The Results: Real Impact So what did we achieve by helping our client? How big was the problem? Did we manage to solve it? Here are the numbers: Our solution detected 1,177 cases of brand impersonation in the span of just six months. With this data, we took down 905 fake listings and fake social media accounts spread across five different platforms. New fake pages and listings that would pop up on our radar were being removed in an average of 1-2 days. As a result of this exercise, the brand experienced an improvement in its brand reputation and enjoyed enhanced customer trust. Evaluating a Brand Protection Solution for Real Estate Real estate

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brand safety guide to auditing ad placements

Is Your Brand Safe? A Step-by-Step Guide to Auditing Your Ad Placements

Blog, Brand Safety & Suitability /

Digital advertising has grown into a vast industry. Thousands of advertisers use advertising networks to publish their ads through millions of publishers. This scale in the ability to reach consumers is nothing short of a miracle, especially for smaller businesses trying to cut through the noise created by their larger competitors. However, thanks to the same scale, there are grave issues concerning all advertisers, regardless of the size of their business or advertising budget.   In this article, we are focusing on one of the most pressing issues faced by digital advertisers- tracking where their ads appear in the digital ecosystem. Why does it matter? Just as a good placement will drive more sales, a bad placement may result in a wasted ad budget or worse, it may end up harming your brand’s image.   This flaw in the way the digital ad industry operates has been exposed by a recent report published by Adalytics. According to the report, ads representing some of the biggest, most well-known brands across the globe were found to be hosted on websites that publish and host child sexual abuse material (CSAM).  The irreparable damage to brand reputation in such a case is not difficult to imagine. Thankfully, there’s a lot that advertisers can do to prevent their ads from being published with harmful or illegal content. This guide will walk you through all the steps you can take to protect your brand against such threats.  Let’s start at the beginning:  Step 1: Gain Visibility – Understanding Your Ad Placements  The first step to safeguarding your brand against problematic ad placements is to understand how ad placements are decided. One of the most common ways to publish ads at scale is to use programmatic ad platforms. These platforms, in theory, allow advertisers to precisely target specific audiences at scale, in real-time.   However, since programmatic platforms operate using a complex ecosystem of algorithms, supply-side platforms, and delivery-side platforms, advertisers have extremely limited visibility into their ad placements.   This was evident in the Adalytics report that highlighted big brand names like Amazon, Arizona State University, and even US Government Departments like the Office Of Texas Governor were found to be unaware of their ads appearing on a website that would also host CSAM content.   This lack of transparency on programmatic campaigns can be counteracted with the right tool.   One of the best ways to ensure that your ads are placed in a safe environment is by implementing a brand safety monitoring solution . mFilterIt’s brand safety tool makes use of real-time monitoring to help advertisers get transparency on their ad placements, where it is getting placed to ensure that their brand name is not associated with appraising advertisers about all the brand safety issues that they may be facing, presented through an actionable data points dashboard. The dashboard offers a categorized view of all unsafe content categories, along with risk levels and a detailed list of placements on which advertisers can take proactive action to safeguard their interests.  Step 2: Conduct Content Safety Analysis Once it is clear how ad placements are decided and you have set up the tracking for the same, it is time to ensure your ads are appearing next to contextually relevant content. While programmatic advertising promises the same, the CSAM case has made it clear that the content verification methods of ad networks are incredibly lacking.  Once again, a reliable brand safety tool can prove extremely handy in such a situation. The tool features a Content Safety Analysis feature that is designed to detect harmful content environments that may not be suited to hosting a specific advertiser’s ads. The tool should not just consider safe ad placements but monitor and flag content based on contextuality and relevancy.   Step 3: Check the Website’s Safety Parameters  Next, brands and advertisers must conduct individual website audits to determine whether a publisher is suited to host their ads. These checks are important because in many cases, a website may seem like a safe bet at a glance but may be holding questionable content within its deep pages. The website exposed in the Adalytics report is a good example of the same. At a glance, it seems like a safe image-hosting website. However, by monitoring the specific URLs one can identify harmful or illicit content websites like the CSAM content.  To make sure none of your ads appear on a questionable website, analyze the list of websites associated with an advertising platform on the following metrics: Website Basics: These include the URLs, titles, meta descriptions, and tags associated with the pages where the ads may appear. While these may seem like rudimentary aspects of website analysis, one may find themselves surprised at how much information these tidbits of a website contain.  Website History: This one may be familiar to many business owners. Checking the history of the website for instances of blacklisting from an advertising platform is a great way to ensure that the ads are appearing in a reputed publication. To be thorough, it is a good idea to also check for historical instances of policy violations.  Domain Safety: Advertisers must also give the domain of the publishers a second look to scan for terms that may not align with their brand safety standards.  Whois Information: The Whois Database is a superb resource for checking any website’s hosting details, credibility indicators, and the name(s) of the owner(s). This information can be used in conjunction with the website’s history and basics to make sure that the website in question truly fits within the brand’s safety guidelines.  These checks, when done thoroughly, can do wonders for ensuring your brand’s safety in the ad ecosystem. However, a typical ad network may have thousands of publishers suited to an advertiser’s targeting needs. Analyzing thousands of websites can prove to be cumbersome, to say the least. For such cases, a tool like PACE can be beneficial. It helps advertisers build an exclusion list and ensure that any of

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How Fraudsters Manipulate App Installs and What Marketers Can Do About It?

Blog, Mobile Ad Fraud /

Mobile apps are big business and the same is apparent through the significant advertising budgets dedicated to increasing app installs. In 2022 alone, advertisers spent more than $18 billion on advertising their apps to drive more installs. This makes the app install advertising business lucrative.   Unfortunately, this lure also attracts bad actors and frauds. That’s perhaps why, today, app install fraud is one of the most common forms of ad fraud in the online realm. According to our analysis, we have found that on IOS, the average fraud at the install level is 57% which rapidly increases to 70% on Android devices.   Fraudsters use fake app installs to steal from advertising budgets. The financial impact of this, while significant, is only a small part of all the trouble caused for the advertisers as a result of these activities. What’s more troublesome is that fraudsters are evolving their methods and employing sophisticated methods to carry out their fraudulent activities.    In times like these, advertisers need to start ahead of the curve to protect their ad budgets. To do this, one must first understand how app install fraud works and that’s exactly what the next section describes. Read on.  The Hidden Tactics Behind Install Fraud While it may seem like app install fraud is a single threat, the reality is much more complex. Fraudsters utilize several simple and complex methods to fake installs and steal from advertisers’ budgets. Here’s a quick overview of the most common methods employed by app install fraudsters:  – Click Injection: This is one of the most sophisticated forms of app install fraud. To execute this, fraudsters publish an app that “listens” for app download broadcasts. Using this information, they can “inject” a click right before an app install is completed. This allows fraudsters to claim the credit for the app install despite not contributing anything to make it happen.  – Click Spamming: Click spamming is usually employed to target campaigns where advertisers are paying for clicks on their ads. As the name suggests, fraudsters generate a large number of fake clicks, usually using bots, and claim the rewards. However, the advertiser unfortunately ends up paying for clicks that will not result in any genuine interest or installs of their application.  – Organic Hijacking: Another sophisticated form of app install fraud; organic hijacking works by stealing the credit of organic installs. Fraudsters employ malware or other methods to send a fake click right before an app download is completed, claiming the credit for the app installs, along with the associated reward.   – Incent traffic: This type of app install fraud is one of the most difficult to detect, as it uses real users to scam advertisers. In this type of fraud, fraudsters place ads on incent walls and incentivize real users to download an application and in some cases, complete an action that claims the reward. In many cases, fraudsters straight out share a part of their affiliate payout with the user. While there are real users involved and the app download is also authentic, since the user is only interested in the reward, the entire activity doesn’t drive any value for the advertiser.   – SDK Spoofing: With SDK Spoofing, fraudsters usually use a malware-laced app of their own to infect user devices. This app then manipulates the SDK communication of the advertisers’ apps to generate fake installs and register other actions that may be rewarded by the advertiser. Alarmingly, such an activity is extremely difficult to track and can be conducted indefinitely, effectively draining entire ad budgets without delivering any real value.   But Aren’t Fraud Checks by MMPs Enough?   Impression campaigns are often the first leg of a successful, larger ad campaign that may target app installs. As a first step, getting authentic impressions is important to make informed decisions to drive more app installs. To make sure their impression campaign data is authentic, many advertisers depend on Mobile Measurement Platforms or MMPs.  Unfortunately, MMPs are not as capable or dependable as many advertisers have been led to believe. One of the biggest problems with MMPs is that they are paid for impression attribution and not validation. To that end, if they start reporting all the fraudulent impressions, it may affect their revenue associated with attribution.   Moreover, in cases where MMPs can detect and report impression fraud, the standard timeline is simply too slow to make any real impact. Most MMPs follow a D+7 reporting schedule, creating a significant delay between the moment a fraudulent activity is detected and the time when an advertiser finds out about it. Finally, most MMPs employ basic checks to detect fraud which are largely ineffective against sophisticated ad fraud techniques.  The Cost of Fake Installs: Why It’s More Than Just Wasted Budget  No doubt, the wasted ad budget is perhaps the most obviously painful effect of ad fraud experienced by advertisers. However, impact of ad fraud goes much deeper than draining your budget and can have a long-term impact on the business.   Fraudulent activities, when undetected, can also skew the ad performance data that advertisers depend on to make optimization decisions. These distorted key performance indicators (KPIs) can further lead to advertisers making optimization decisions that waste even more of their marketing budget.  Not to forget, skewed metrics also impact other decisions related to user acquisition and experience. The wrong decisions, especially in the case of user experience, can lead businesses to decisions that worsen the experience of installing and using their apps, negatively impacting long-term user retention and organic App Store/Play Store rankings.   In other words, a wasted ad budget is just the tip of the iceberg. App install fraud can impact user data analytics which can, in turn, impact long-term marketing ROI. Red Flags Valid8 has Detected  Fighting fraud starts with detecting fraud. Advertisers must stay vigilant and look for the following signs to catch instances of fraud and deal with the fraudsters before they can cause significant harm:  Abnormally Low Conversion Rate– An

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how to detect and prevent ppc fraud in app campaigns

What Advertisers Need to Know When Addressing PPC Ad Fraud?

Blog, Ad Fraud /

If you’re running a PPC campaign, check your analytics data.   Do you see a rapid curve of increase in click traffic, while your installs or events remain low?   This is one of the classic signs that you need to get your ad traffic vetted, as it might be under the radar of ad fraud perpetrators.   Over time fraudulent parties in the digital ecosystem have evolved and indulged in sophisticated fraud techniques to gain maximum benefit. The techniques have become more human-like and difficult to detect.   As a result, these fraudulent techniques not only impact the bottom line of a digital brand but also weaken the efficiency of the campaigns. From driving bot traffic to breaching the walled gardens, they have perfected their practices over time. One of them has been PPC fraud techniques which are not just limited to web but also app campaigns.   As the spending on mobile app marketing increases, it has become a gold mine for fraudsters to dig for money Types of in-app PPC Advertising Fraud Unlike web campaigns, app-based PPC fraud operates in an opaque environment. Fraudsters manipulate in-app interactions at various levels, but the most alarming issue is that advertisers often rely on flawed measurement systems that don’t validate traffic effectively. This is where many advertisers fall into the trap of trusting impressions and clicks at face value.  The fraud manifests in multiple ways: -Click Spamming: Fraudsters flood attribution systems with click spamming which is to generate fake clicks to wrongfully claim credit for organic installs.  -Click Injection: Malware-infected apps hijack install events by sending a fraudulent click at the exact moment an app is installed.  -Bot Traffic: Automated scripts mimic human behavior, generating clicks and even fake in-app events.  -Organic Poaching: Fraudsters hijack organic user traffic by injecting random clicks and falsely claiming attribution.  -Acquisition Poaching: Fraudsters manipulate attribution models by faking user engagement to appear as legitimate traffic.  The Importance of Click-Level Validation The biggest flaw in many app advertising strategies is that they trust data provided by Mobile Measurement Partners (MMPs) without validating it beyond the impression level. MMPs typically attribute installs and in-app events based on the last-click attribution model, but they don’t analyze whether that click was genuine in the first place.  Without click-level validation, advertisers are left vulnerable to: -Wasted budgets: Paying for fraudulent clicks that never convert into real users.  -Distorted performance metrics: Misattributed installs and engagement rates create misleading reports.  -Poor down-the-funnel optimization: Advertisers end up optimizing for fraudulent traffic rather than genuine user acquisition.  How PPC Fraud Impacts Down-the-Funnel Metrics Fraudulent clicks don’t just impact the initial stages of a campaign; they create a ripple effect down the funnel. Consider this:  If your PPC campaign generates fake clicks, your CPI (Cost Per Install) skyrockets because installs may not be genuine.  Fraudulent installs inflate your DAU (Daily Active Users) numbers artificially, leading to poor LTV (Lifetime Value) calculations.  Since bots or hijacked installs don’t engage meaningfully, your retention and conversion rates drop, creating misleading insights for future optimizations.  Real Case Study: How a Quick Commerce Brand Tackled PPC Fraud A major quick commerce platform in India discovered severe PPC fraud issues within their app advertising campaigns. They were running retargeting campaigns to increase engagement, but conversions remained low despite their significant ad spend. Upon investigation, they found:  -High levels of fraudulent traffic: 58% of clicks and 46% of events were fraudulent.  -Organic Poaching: Fraudsters injected random clicks to claim credit for organic installs. The click-to-conversion time gap for Publisher A on January 11th was 35% longer than usual, indicating hijacked organic traffic.  -Acquisition Poaching: Engagement partners falsely re-attributed already acquired users by forcing fake re-engagement clicks instead of waiting for real user activity.  By implementing click-level validation and actively monitoring traffic sources, the brand:  Identified and eliminated fraudulent publishers.  Reduced misattribution of organic traffic.  Saved $1.9 million in a single month by stopping invalid ad spend.  This case highlights how unchecked PPC Ad fraud can drain budgets while inflating performance metrics, making it crucial for advertisers to validate traffic beyond surface-level analytics.  Combatting PPC Fraud: Steps Advertisers Must Take Tackling PPC fraud in-app campaigns requires a proactive approach. Here are the most effective strategies:  Validate Click Traffic in Real Time   Use solutions that verify click authenticity before attribution.   Look for abnormal patterns like excessive click-to-install times or multiple clicks from the same device. Go Beyond Last-Click Attribution Model Validation  A last-click model alone doesn’t provide the full picture.  Compare click timestamps and engagement across different sources to detect anomalies.  Monitor Post-Install Behavior  Genuine users interact with an app differently than bots or fraudulent installs.  Analyze session depth, retention rates, and in-app purchases to flag anomalies.  Use Third-Party Fraud Detection Tools  Many MMPs lack comprehensive fraud prevention mechanisms.  Implement third-party ad verification tools to cross-check data integrity.  Blacklist Fraudulent Sources  Identify ad networks or publishers that repeatedly send suspicious traffic.  Blacklist them proactively to reduce the impact on down-the-funnel metrics  Way Forward PPC fraud in apps is a silent budget killer that can cripple your campaign performance if left unchecked. The key to protecting your ad spend is to go beyond surface-level analytics and validate clicks at a granular level.  If advertisers treat click validation like a security checkpoint—ensuring every click is a legitimate entry rather than an impersonator—campaign efficiency will soar, and wasted ad spending will be reduced.   Want to safeguard your app campaigns from fraud? Start by validating your ad traffic data, leveraging the advanced ad fraud solution that go beyond surface level check, and make every click count. Want to get a demo of how we do it? Contact our team today  

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Building Trust in Affiliate Marketing: Emerging Fraud Challenges & Solutions for 2025

Blog, Affiliate /

Affiliate marketing, as a concept, is revolutionary. It enables businesses to make money by using the influence of popular online publishers. When the right affiliates are involved, affiliate marketing not only drives more sales, but also boosts long-term brand performance metrics like brand recall value and trustworthiness of the brand.   At the same time, by design, affiliate marketing ensures the publishers bring their A-game in getting brands maximum visibility and ensuring their audiences view them in a positive light. After all, more sales also translate to better affiliate payouts for the publishers.   Thanks to this symbiotic nature of affiliate marketing, it is nearly the perfect marketing activity. Nearly.   Instances of affiliate marketing fraud can quickly impact the fantastic results of even the most carefully executed campaigns. Fraud associated with affiliate marketing can drain ad budgets and bring low-intent users to interact with brand’s ad campaigns.   Thankfully, advertisers are not powerless in the face of affiliate marketing fraud. In fact, by employing affiliate monitoring and brand safety best practices, advertisers can completely eliminate the threat of affiliate marketing fraud.   However, before we begin discussing how affiliate fraud prevention works, let’s quickly size up the threat that is affiliate marketing fraud.   The Rising Threat of Affiliate Fraud in 2025  In the next two years, the affiliate marketing market is expected to grow to a whopping $27.78 billion. While this might seem like great news, it also means that fraudsters have that much more incentive to come up with sophisticated ways to commit fraud and dupe advertisers. According to mFilterIt analysis, 43% of the fraudulent traffic is coming from affiliate networks in India.   Where there is money, the instances of fraud also rise. Similarly, in the space of affiliate marketing, Affiliate fraud has existed almost since the inception of this marketing channel . As digital technologies became more accessible, affiliate fraud practices evolved in tandem with the evolution of affiliate marketing itself and alarmingly, the trend continues.   Today, fraudsters have access to sophisticated artificial intelligence models and automation technologies, enabling them to commit fraud in complex and hard to detect ways. At the same time, such technologies also enable bad actors to commit fraud on an expansive scale, targeting both web and app ecosystems. For brands, these activities translate to a damaged brand reputation, inflated customer acquisition costs, and poor user retention.   How are such fraudulent schemes implemented? Which are the most common ones? Knowledge is the first step to prevention. Let’s peek behind the curtains of affiliate marketing fraud:  Common Affiliate Fraud Techniques & Their Impact  Fraudsters have found various methods to corrupt the affiliate schemes to use to their advantage. While there are some common methods, with evolving technology fraudsters have found new and advanced ways to commit fraud. Some of them are here:   – Incent Fraud   Running incent campaigns is perhaps one of the oldest forms of affiliate fraud and yet, it is exceptionally difficult to detect before the fraud has made a significant dent in your marketing budget. Simply put, affiliates incentivize their audience with a reward in exchange for completing a specific action, such as downloading an app and completing an action once the download is complete. Incentives can include small rewards such as loyalty points or even a small share of the affiliate payout.   Since the users complete these actions because of the lure of the reward offered by the affiliate they seldom have any genuine interest in interacting with the advertiser’s app or website. As a result, the advertiser ends up paying for the interactions with these uninterested users while gaining nothing of significance in exchange. This further leads to a high uninstall rate and the advertiser has to pay more to acquire more customers.   – Brand Bidding   This is especially problematic for brand bidding as it drains their marketing budget twice as fast. By bidding for the same keywords as the brand, fraudsters increase the competition around those keywords, leading to an inflated cost-per-click (CPC) paid by the brand. Additionally, the brand still ends up paying much more than the CPC for the traffic it loses in the ads as it is redirected to their website as affiliate traffic by the fraudsters.  – Trademark Misuse  Another common yet clever form of affiliate fraud is impersonation. Fraudulent publishers create fake websites that share striking similarities with an advertiser’s website. Using these, fraudsters may impersonate the brand to attract high-intent traffic and then use affiliate links from the real brand on their fake websites to get affiliate rewards.   – Cookie Stuffing & Attribution Fraud  With cookie stuffing, fraudulent affiliates drop a cookie in the user’s browser when they visit a brand’s website. This way, even if the user visits the brand’s website directly, the attribution of the sale is allocated to the fraudster, enabling them to get affiliate commission for a sale they did not enable.   This not only results in the brand paying affiliate commission on an organic sale, it also manipulates the sales metrics, making data unreliable.  – Fake Lead Generation & Form Spamming  One of the most common tools employed for committing click fraud is a bot. Fraudsters use a network of bots with varying sophistication to complete tasks that get them affiliate revenue. Bots are programmed to act like real human users and generate clicks and fill out lead generation forms with fake information.   If an advertiser pays affiliate commissions for lead generation actions, they may easily fall victim to a fake lead generation and form spamming fraud. This can not only lead to wasted marketing spending and poor conversion rate, but it can also have a long-lasting impact on the advertiser’s overall marketing efforts because it dilutes and skews their marketing performance and CRM data.   – Misuse of Advertiser’s Brand Assets  In some cases, fraudsters may stoop down to directly scam the users. While this usually does not lead to wastage of marketing budgets, it can hurt advertisers and brands in other equally significant ways.  Fraudsters may create fake

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Cloaking in Brand Bidding: How Fraudsters Conceal Their Tracks to Evade Detection?

Blog, Ad Fraud Blog - Valid8, Ad Traffic Validation /

Imagine spending years building a strong brand presence, only to have fraudsters hijack your traffic and revenue using deceptive tactics. You invest heavily in search engine advertising, expecting customers searching for your brand to land on your legitimate pages. But instead, they are unknowingly misled to counterfeit product pages, unauthorized affiliate sites, or even direct competitors. This deceptive practice, known as cloaking in brand bidding, is a growing menace that threatens both brand integrity and consumer trust. If left unchecked, it can drain your marketing budget and damage your reputation before you even realize it.  Why do Fraudsters Use Cloaking in Brand Bidding?  Fraudsters leverage cloaking in brand bidding as a deceptive strategy to maximize their gains while avoiding detection. Their primary motives include:  -Evading Detection: Cloaking ensures that search engine monitoring and brand compliance teams see a compliant landing page, while real users are directed to misleading content. -Capturing Competitor Traffic: By bidding on branded keywords, fraudsters hijack organic traffic intended for the brand, diverting potential customers to counterfeit products, unauthorized affiliate offers, or even competitor sites. -Exploiting Brand Trust: Users searching for a specific brand inherently trust ads associated with it. Cloaking exploits this trust to mislead users, increasing fraudulent conversions. -Bypassing Advertising Restrictions: Search engines and ad platforms have strict policies against unauthorized brand bidding, but cloaking helps fraudsters divert these regulations without immediate repercussions.  Why Advertisers Must Address Cloaking Effectively  Ignoring cloaking in brand bidding can have severe consequences for brands. Here’s why advertisers must act:  -Brand Reputation at Risk: When users are misled by fraudulent ads, they may develop negative perceptions of the brand, leading to loss of trust and loyalty. -Revenue Leakage: Fraudsters take away potential sales, directly impacting the brand’s bottom line. -Unfair Market Manipulation: Legitimate advertisers invest in compliance and quality, while fraudsters exploit the system to gain an unfair advantage. -Potential Legal Complications: Unauthorized brand bidding and deceptive advertising practices could result in legal disputes, affecting brand credibility and resources. -Ad Policy Violations: Brands that fail to address cloaking risk non-compliance with search engine policies, leading to penalizations or ad restrictions. How to Detect and Combat Cloaking in Brand Bidding  Brands must implement a multi-layered approach to prevent and mitigate cloaking attempts. Here’s how:  -Deploy Advanced Monitoring Tools: Leverage solutions like Ad Fraud Solution by mFilterIt offer real-time monitoring, detecting cloaked ads and unauthorized brand bidding. -Strengthen Compliance Measures: Establish clear guidelines for affiliates, resellers, and partners to prevent deceptive advertising tactics. -Enforce Legal Protections: Take legal action against fraudsters leveraging cloaking to violate trademark rights and mislead consumers. -Collaborate with Ad Platforms: Work closely with search engines and ad networks to report and eliminate fraudulent ads promptly. Stay One Step Ahead  Cloaking in brand bidding is a persistent and evolving threat, but with the right strategies, brands can protect their reputation, revenue, and digital presence. By leveraging AI-powered fraud detection tool, enforcing compliance policies, and working closely with ad platforms, businesses can stay ahead of deceptive advertisers and maintain control over their brand visibility.  Want to secure your search ads against cloaking? Contact Us. 

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YouTube Video to DV360 Demand Gen: Essential Guide for Marketers

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If you’re currently managing YouTube Video Action Campaigns within Display & Video 360 (DV360), there’s a significant update on the horizon that you’ll need to prepare for. Started in October 2024, Demand Gen campaigns will become a core feature of DV360. This transition will expand your campaign capabilities, offering enhanced reach, new creative formats, and advanced audience targeting In this article, we’ll break down what this shift means, how it impacts your current campaigns, and the steps you can take to get ready for the change. What is Demand Gen in DV360? Demand Gen is a versatile campaign format designed to drive conversions through dynamic multi-format creative storytelling. With Demand Gen, you can now run both video and image ads within the same campaign line item. This brings more flexibility to your advertising efforts, enabling you to streamline workflows and craft more cohesive brand narratives. Key Advantages of Demand Gen: -Broader Reach: Engage with up to 3 billion monthly active users across Google’s vast ecosystem, including YouTube, Discover, Gmail, and other Google platforms. Unlike traditional YouTube Video Action Campaigns, you won’t be restricted to just YouTube for video placements. -Multi-Format Creativity: Demand Gen allows you to combine video and image creatives in a single campaign, simplifying management while ensuring that all your assets work seamlessly together to convey a unified brand story. -Advanced Audience Targeting: Leverage lookalike audiences to reach users who exhibit behaviors and interests similar to your existing customers. This feature is perfect for finding new potential customers who are most likely to engage with your brand. These capabilities make Demand Gen a powerful tool for marketers seeking to amplify their reach and drive higher conversion rates. In fact, according to internal Google data, campaigns that utilized both video and image assets experienced a 20% boost in conversions at the same cost per action when compared to campaigns that used video alone. The Transition from YouTube Video Action Campaigns Currently, many advertisers use YouTube Video Action Campaigns (VACs) to drive conversions within YouTube and its partner platforms. However, starting in 2025, YouTube Video Action Campaigns will transition into Demand Gen line items. Here’s what you need to know about the shift: Key Changes: -New Campaign Types: From March 2025 onwards, new YouTube Video Action Campaigns will no longer be supported in DV360. Instead, you will need to create Demand Gen campaigns. -Existing Campaigns: While your existing YouTube Video Action Campaigns will continue to run, transitioning to Demand Gen should be a priority. Familiarizing yourself with Demand Gen now will ensure a smooth transition and allow you to take full advantage of the new features before the change is mandatory. Though many of the functionalities from YouTube Video Action Campaigns, such as Floodlight optimization and third-party brand safety verification, will be preserved, it’s crucial to adapt to the new Demand Gen setup sooner rather than later. The earlier you start, the easier the transition will be. Maximizing the Impact of Demand Gen Campaigns in DV360: How mFilterIt can help advertisers The shift to Demand Gen campaigns within DV360 offers a significant opportunity for mFilterIt to enhance its pitch to advertisers, especially in terms of driving performance while ensuring brand safety solution . Here’s how mFilterIt can help brand capitalize on the new features of Demand Gen campaigns to offer valuable benefits to advertisers: -Enhanced Brand Safety & Ad Verification: With the expanded reach of Demand Gen campaigns, ensure that your ads are placed in safe, brand-compliant environments across YouTube, Gmail, Discover, and more, using mFilterIt’s robust ad verification and brand safety solution. -Advanced Audience Targeting and Optimization: Leverage mFilterIt’s audience optimization features alongside Demand Gen’s lookalike audience capabilities, ensuring you’re reaching the most relevant customers with the highest likelihood of conversion. -Cross-Platform and Multi-Format Campaigns: Simplify your cross-platform, multi-format campaigns with mFilterIt’s real-time reporting and optimization tools, ensuring both video and image creatives perform to their fullest potential. -Conversion Tracking and Floodlight Integration : Use mFilterIt’s integration with Floodlight to gain deeper insights into your Demand Gen campaign performance, ensuring you’re driving more conversions and optimizing your ROI. -Transparency & Reporting : Get complete transparency into the performance of your Demand Gen campaigns across all formats and platforms with mFilterIt’s comprehensive reporting tools, empowering you to make informed decisions. -Improved Efficiency with Automated Brand Safety Checks : Streamline your workflow and ensure continuous brand safety across all your multi-format Demand Gen campaigns with mFilterIt’s automated monitoring and real-time protection. Conclusion: With the introduction of Demand Gen campaigns in DV360, advertisers have a unique opportunity to expand their reach and connect with the right target audience. Clubbing this new feature mFilterIt has a unique opportunity to position itself as a crucial partner for advertisers. By offering robust brand safety, performance optimization, advanced audience targeting, and transparent reporting, mFilterIt can help advertisers navigate the complexities of multi-format campaigns and make the most of their expanded reach across Google’s ecosystem. This comprehensive approach can boost both the effectiveness and security of Demand Gen campaigns, ultimately driving better results for advertisers. Want to get a demo of how we do it? Contact our team today 

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Marketing Team vs. Call Center Team: Who’s to Blame When Leads Don’t Convert?

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Picture this: The marketing team proudly delivers a new batch of leads, convinced that these prospects are primed for conversion. Meanwhile, the call center team rolls its eyes once again, they’re fielding complaints from uninterested or unqualified contacts. Frustration rises, fingers are pointed, and the age-old question resurfaces: Who’s responsible when leads don’t convert—marketing or the call center?  This debate often boils down to one critical issue: junk leads. While the marketing team may generate impressive volumes of leads, not all are created equal. Junk leads—those unqualified, uninterested, or even fraudulent frequently sneak into the funnel, wasting time, resources, and ultimately, opportunities for both teams. In this article, we explore the “real reason” behind this endless marketing vs. call center debate, emphasizing how a continuous filtering system can align both teams, save time, and improve results.  The Junk Lead Challenge: Why Leads Aren’t Always What They Seem  On the surface, a lead might appear promising. It might tick the right boxes in terms of basic demographics or initial engagement. However, a closer look reveals that not all leads are created equal. Junk leads are often generated through non-intent-driven clicks impertinent, low-quality traffic sources, or unverified information. These leads lack genuine interest and intent to buy, leading to a series of issues that drive the marketing and call center divide:  Marketing’s Perspective: “We Hit Our Numbers”  Marketing’s goal is often centered on generating high lead volumes. Performance is measured by metrics like click-through rates, form submissions, and lead counts, creating pressure to hit targets. However, these numbers can sometimes reflect quantity over quality, as invalid clicks and junk leads skew results.  Call Center’s Perspective: “We’re Wasting Our Time”  The call center team deals with these leads firsthand, engaging in time-consuming follow-ups only to find disinterested, unreachable, or unqualified contacts. For call center agents, these engagements lead to burnout and frustration, impacting their morale and effectiveness.  This disconnects between the two teams not only impacts productivity but also consumes valuable resources. For a business focused on conversion and growth, the junk lead issue becomes a costly barrier, resulting in wasted time, reduced efficiency, and strained internal relationships across departments.  The Hidden Impact of Junk Leads  Junk leads are more than just data in the CRM; they create a cycle of wasted efforts for both teams:  -Lost Time on Unproductive Calls: Call center agents spend precious time on leads that lack any genuine interest in the product, draining their morale and productivity. It’s frustrating for agents to encounter frequent rejections, impacting their motivation and performance.  -Strain on Marketing Resources: For marketing, the push for high numbers of leads can come at the expense of quality. Campaigns are evaluated on how many leads they generate, even if many are unlikely to convert. This can lead to a misplaced focus on quantity over quality, which ultimately fails both teams.  -Unmet Conversion Goals: For both marketing and the call center, junk leads directly affect the bottom line. Marketing sees low ROI on its campaigns, and the call center fails to hit conversion targets. In the end, this hurts the business by diverting resources from potential sales opportunities to unqualified leads.  Focus on Lead Quality Over Lead Quantity  To resolve the marketing-call center debate, it’s essential to shift the focus from sheer lead volume to lead quality. By implementing more rigorous lead qualification and filtering practices, companies can prevent junk leads from clogging the sales pipeline. Here’s how:  –Establish Clear Lead Qualification Criteria The first step in aligning both teams is to set clear standards for what defines a “qualified lead.” This could include factors like purchase intent, behavior on the site, engagement with marketing content, and demographic relevance. By standardizing these criteria, marketing can better identify high-potential leads before they’re sent to the call center, ensuring agents aren’t left cold-calling uninterested contacts.   -Leverage Behavioral Data for Better Lead Insights  With digital tools, marketing can capture and analyze data on each lead’s behavior—such as time spent on key pages, interaction with offers, and responses to email campaigns. Leads showing high levels of engagement signal a stronger interest and are more likely to convert. Sharing this behavioral data with the call center gives agents deeper context, helping them prioritize leads more effectively.  -Segment and Score Leads Before Hand-Off  Segmentation and lead scoring can transform a CRM from a dumping ground of all leads into a well-organized system that prioritizes quality over quantity. With segmentation, marketing can assign different levels of interest to leads, grouping them by their likelihood to convert based on factors like recent interactions, browsing patterns, and demographic fit. Lead scoring, on the other hand, uses these criteria to rate each lead’s conversion potential, making it clear which leads warrant follow-up.  –Optimize Follow-Up Process for Different Lead Types  Once leads have been segmented, the call center can adjust its follow-up process based on each group’s engagement level. For instance, leads with high engagement scores can be prioritized for immediate, frequent follow-ups, while lower-scoring leads might benefit from a more gradual approach or even additional nurturing from marketing before being passed to sales. This ensures that agents are spending their time where it’s most likely to yield results.  -Implement Continuous Feedback Loops  To maintain alignment, marketing and the call center need open lines of communication. A continuous feedback loop allows the call center to provide insights on lead quality back to marketing, helping refine future campaigns. Over time, this feedback can guide marketing’s strategies to target more qualified leads, improving the overall quality of leads entering the funnel.  How mFilterIt can help marketers remove junk leads?    mFilterIt’s  Ad fraud solution empowers advertisers by collecting and analyzing crucial data—such as website behavior, CRM inputs, and conversion metrics—through advanced AI & ML algorithms. The system’s proprietary rule engine scores lead based on user intent (high, moderate, or low), helping advertisers swiftly identify and filter out junk leads. This enables sales teams to focus on quality prospects, improving efficiency and conversion rates. With mFilterIt’s analytics-driven approach, advertisers gain actionable

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