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full funnel validation

Reclaiming Digital Transparency: 1000Farmacie’s Full-Funnel Approach

The dashboard says ROAS is up. Conversions are climbing. The team’s celebrating. But beneath the surface, something’s off. Traffic looks strong—but isn’t converting. Budgets are growing—but impact isn’t. That’s the trap of affiliate fraud and misattribution—they inflate performance on paper while draining real results. From cookie stuffing and click spamming to bot traffic masked as human behavior, invisible threats distort the numbers marketers rely on most. The missing layer? Full-funnel validation. This blog breaks down how misattribution quietly sabotages performance, why validation is no longer optional, and how 1000Farmacie uncovered the gap—and fixed it. The Hidden Cost of Misattribution Affiliate marketing promises performance-based growth—but what happens when the performance you’re measuring isn’t real? Misattribution is one of the most under-recognized threats to marketing efficiency. It occurs when credit for a conversion is incorrectly assigned to the wrong source—often due to deceptive practices designed to exploit attribution models. In affiliate campaigns, where commissions and payouts depend on tracking performance, this opens the door for fraud. Fraudsters use several tactics to hijack attribution and artificially inflate results: Cookie Stuffing: This involves secretly placing multiple affiliate cookies on a user’s browser without their knowledge or action. If the user later makes a purchase—regardless of the actual channel that influenced it—the fraudulent affiliate still gets credit. Click Spamming: Also known as “click flooding,” this technique sends a high volume of low-quality or automated clicks hoping to match a legitimate conversion through sheer volume. It’s a numbers game that can distort your attribution data and create phantom performance. Bot Traffic: Sophisticated bots mimic human behavior—browsing products, clicking links, even triggering conversion pixels. These non-human visitors can seriously inflate your traffic numbers, conversion rates, and ROAS, all while draining budget. The impact isn’t just technical—it’s strategic. When misattribution is baked into your performance metrics: Budgets get misallocated to underperforming or fraudulent affiliates. Reports tell a distorted story, masking the real sources of growth. Optimization decisions become flawed, leading marketers to double down on what isn’t working and overlook what is. Worse, it creates a false sense of success—campaigns that seem to be thriving on the surface may actually be leaking value underneath. So here’s the question: How much of your affiliate “performance” is actually performance—and how much is fraud disguised as success? Why Full-Funnel Validation is the New Must-Have If misattribution is the invisible leak in your performance marketing, full-funnel validation is the essential tool to detect—and seal—it. At its core, full-funnel validation involves verifying every stage of a user’s journey, from the initial click on an ad or affiliate link to the final conversion. This comprehensive approach delves deeper than surface-level metrics to assess whether the traffic, clicks, and conversions are legitimate, human, and incremental. Here’s how it operates: Traffic Quality Checks at the top of the funnel detect suspicious patterns—such as bots, data center IPs, or abnormally high click rates. Engagement Validation in the middle of the funnel monitors behavioral cues: is there genuine user interaction, or just empty clicks? Conversion-Level Analysis at the bottom ensures that attributed sales are backed by authentic user journeys—not automated scripts or cookie drops. This layered approach provides marketers with comprehensive visibility into the authenticity of their traffic. The necessity of full-funnel validation becomes even more evident when considering the current landscape: Bot Traffic: In 2023, bots accounted for nearly half (49.6%) of all internet traffic globally, with “bad bots” responsible for a third of this figure.   Affiliate Fraud: In 2022, fraudulent clicks constituted 17% of all affiliate traffic, leading to an estimated $3.4 billion in losses.   Ad Fraud Growth: Ad fraud is projected to cost advertisers $84 billion in 2023, accounting for 22% of all online ad spend, with expectations of this figure rising to $170 billion by 2028.   The benefits of implementing full-funnel validation are substantial:  Improved Attribution: Accurately identify which partners and platforms genuinely drive value—and which ones are manipulating the system.  Smarter Budget Allocation: Redirect spending toward high-performing channels and eliminate wasteful or fraudulent ones.  Real-Time Insights: Detects and addresses fraud as it happens, preventing damage before it escalates. Without full-funnel validation, many marketers are operating in the dark—especially in affiliate-heavy campaigns, where performance-based payouts create strong incentives for manipulation. Modern marketing demands more than just tracking conversions; it demands proof of authenticity. Full-funnel validation is the safeguard that ensures your data, decisions, and dollars are grounded in reality. Case in Point: 1000Farmacie’s Affiliate Campaign Was Underperforming—But Looked Great on Paper 1000Farmacie, a leading digital pharmacy marketplace in Italy, serves over 1 million retail customers with more than 800,000 orders annually. As part of its performance marketing strategy, the company relied heavily on affiliate partnerships to drive conversions and grow reach. On the surface, the numbers looked strong. But beneath that surface, there were serious issues affecting efficiency and accuracy. When mFilterIt stepped in, their full-funnel fraud detection and validation uncovered critical insights:  28% of affiliate traffic showed signs of invalid activity—including tactics like click spamming and cookie stuffing. A significant portion of traffic displayed non-human behavior patterns, such as:  Visits originating from data center hubs.  No mouse movement, scroll, or swipe behavior. Misattribution at the order level accounted for a large share of the problem, distorting ROI and misguiding budget allocation. To address these issues, 1000Farmacie deployed mFilterIt’s full-funnel validation and real-time fraud prevention stack, which included: Automated blacklisting APIs integrated directly with ad managers to block fraudulent sources in real time. Traffic quality validation from visit to conversion, identifying anomalies and flagging suspicious sessions. Omnichannel monitoring dashboards that offered transparency across paid and affiliate channels. Ongoing campaign optimization with a focus on reducing invalid traffic and correcting attribution errors. By validating 5.7 million visits and 60+ paid channel orders, and reducing incorrect attribution by 20% on affiliates, mFilterIt helped expose the disconnect between reported and real performance—proving that what looked like success was, in fact, driven by inefficiencies and fraud. The Outcome: Real Efficiency, Better Attribution, Higher ROI With full-funnel validation in place, 1000Farmacie was able to move from reactive to

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IPL 2025 Ads: Smart Brand Tips for Monitoring, Frequency & Fraud

The Indian Premier League (IPL) continues to shatter records, not just on the field but also in the advertising arena. The 2025 season has witnessed a remarkable 29% increase in the number of advertisers compared to the previous year, with over 55 brands vying for attention during the first five matches alone.  However, with this vast opportunity comes significant risk. The surge in advertising can lead to overspending, ad fatigue among viewers, and an uptick in fraudulent activities targeting high-profile events like the IPL.   This blog explores how strategic implementation of ad monitoring, frequency capping, and fraud detection can be the difference between a successful IPL campaign and a costly misstep.   What will your brand get out of IPL advertising?   Here are the benefits your brand will get out of IPL advertising:  Fast Massive Reach   The Indian Premier League (IPL) isn’t just a cricket tournament—it’s a nationwide spectacle with a global fanbase. In the 2024 season, the IPL reached a cumulative audience of 546 million viewers on television alone, with digital platforms like JioCinema attracting an additional 620 million viewers.  This unparalleled reach offers brands instant national visibility.   For brands, this means instant national visibility. Doesn’t matter if you’re launching a new product or driving top-of-funnel awareness, IPL advertising is your opening batsman—aggressive, high-impact, and out to make a statement from ball one.   In most media environments, building this kind of reach would take weeks, even months. With IPL, it can happen in a matter of days, sometimes even overnight. You’re not just reaching people—you’re entering living rooms, conversations, and social media feeds in real time.   Hyper-Engaged Audience  IPL viewers are not just numerous; they are deeply engaged. During the 2024 season, JioCinema reported that viewers spent an average of 75 minutes per session, up from over 60 minutes in the previous season.  This substantial time spent indicates a highly captivated audience, providing brands with extended exposure and increased opportunities for message retention.   A neuroscience study revealed that during IPL 2024, viewers exhibited 1.2 times higher attention to ads on connected TVs compared to linear TV, and brand equity increased by 1.5 times on connected TVs.  This heightened engagement translates to more effective advertising, as audiences are more receptive and responsive to brand messages during the tournament.   Better Brand Recall  Repeated exposure during the IPL significantly enhances brand recall. The tournament’s high-frequency matches and extensive viewership provide multiple touchpoints for audiences to internalize brand messages.   Integrating advertisements with specific in-game moments, such as boundaries or wickets, further amplifies recall. For instance, Cadbury Dairy Milk’s #ThankYouFirstCoach campaign during IPL 2024, which featured heartfelt tributes to cricketers’ first coaches, resonated deeply with audiences and reinforced brand association.  By now you’ve understood the massive opportunity IPL advertising is. But over the years, there’s been a marked increase in programmatic ad buys and real-time bidding (RTB). Platforms like JioCinema have enabled precise audience targeting, allowing brands to bid dynamically for premium ad slots in real time. While this opens up opportunities for better efficiency and control, it also intensifies competition.   With thousands of brands vying for the same inventory, standing out without overspending becomes a strategic challenge. The very speed and scale of programmatic — if not managed carefully — can lead to frequency spikes, wasted impressions, or audience fatigue. For smart advertisers, this creates an opportunity: those who can balance agility with optimization can win both attention and efficiency.  Ad Monitoring  With millions of impressions served in real time across multiple platforms, devices, and geographies, this is not the kind of campaign you can set and forget. Without active monitoring, you risk losing both visibility and impact.  Performance dips, under-delivery, missed geographies, or even incorrect creatives can all quietly eat into your campaign effectiveness. These aren’t just technical glitches — they’re lost opportunities in a media moment that’s all about timing and precision.  This is where our Ad Detection & Analysis on OTT solution comes in. Built for high-velocity environments like IPL, it enables brands to monitor every single impression with precision — across CTV, mobile, and OTT platforms.  The ad monitoring solution provides comprehensive ad tracking, detecting when, where, and how your ads appear. Whether it’s during a top-billed match or a weekday double-header, you get complete visibility into ad delivery across regions, languages, and content types.  It also offers Peak Viewership Heatmaps, helping brands align their ad placements with moments of maximum audience engagement — ensuring not just delivery, but visibility when it matters most.  Performance is benchmarked category-wise, allowing you to understand how your brand stacks up against others in your industry. Plus, with regional and language-based analysis, you’ll know exactly how your ads performed in key cities like Mumbai, Delhi, Bengaluru, and across language feeds including Hindi, Tamil, Telugu, and Kannada.  In short, this isn’t just monitoring — it’s effective campaign intelligence, tailor-made for IPL-scale advertising.  Frequency Capping  With matches happening nearly every day and audiences tuning in across screens, the risk of overexposing your audience to the same ad grows rapidly. Too many impressions in a short span can lead to ad fatigue, reduced attention, and even negative brand perception.  This is where our Frequency Capping Management solution steps in. Built with IPL-scale dynamics in mind, it provides real-time control over how many times an ad is shown — per user, per device, per region, and even per campaign.  The platform checks every ad request against the cap limit before serving. If a device has already reached the cap, the ad is withheld — ensuring no overserving occurs. This allows for real-time protection against over-frequency, reducing media wastage and boosting campaign efficiency.  Brands can configure caps using multiple parameters:  Publisher-based: Set distinct limits per publisher or apply a uniform cap across all.  Geolocation-based: Adjust capping for different cities or regions.  Campaign-based: Apply caps tailored to specific initiatives or objectives.  Time-based: Control exposure over days, weeks, or months.  The system integrates seamlessly with ad servers and wraps creatives with a smart VAST tag that enforces these rules automatically

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pay-per-call

The Hidden Cost of Lead Generation Fraud in Pay-Per-Call Campaigns & How to Stop It

If you are selling products or services online in the US, there’s a good chance that you have dabbled with performance marketing or pay-per-call (PPC) campaigns, as they are commonly called. In fact, these days, in order to drive any kind of business online at scale, PPC campaigns have emerged as a necessity, and for good reason. In a perfect world, PPC campaigns have the potential to provide businesses with high-intent leads that can easily be converted into paying customers. Many brands have deployed significantly large teams of sales experts to handle the leads generated by PPC campaigns and drive conversions. Unfortunately, the world isn’t perfect, and modern PPC campaigns are plagued with lead generation fraud. Fraudsters use a variety of simple and sophisticated techniques to defraud advertisers and waste their ad spending while making a quick buck in the process. The worst part is that the wasted ad spend has just a short-term impact on such fraudulent activities. In the longer run, scammers can skew the metrics that advertisers use to plan their campaigns. As a result, lead generation fraud can have lasting effects on any brand’s PPC performance. Let us look at this problem in more detail. The Problem: How Lead Generation Fraud is Hurting Pay-Per-Call Campaigns Lead generation fraud is a huge problem, especially for advertisers operating at a large scale. This problem can be made easy to understand by breaking it down into its components: 1. Fake and Invalid Leads The most noticeable impact of fake campaigns is the fake lead generation with the use of bots and duplicates. Fraud publishers employ bots and in some cases, real people to click on ads and generate calls. However, since these calls are generated with the sole purpose of defrauding the advertisers and securing unethical monetary gains for the fraudsters, they have no real intent behind them and never convert into paying customers. The only losing party in this mix is the advertiser who ends up paying for calls that have no chance of converting, no matter how well a sales team works on them. 2. High Volume Of Fake Engagements Fake and invalid leads generated with the use of bots of poorly paid employees of fraud publishers generate a lot of engagement but drive no real value. In fact, they drain ad budgets that could otherwise drive engagements that boost the business’ bottom line. Similarly, the fake calls generated also engage call center resources that could be otherwise used to engage with genuinely interested prospects. This reduces the operational efficiency of the call centers. 3. Lack Of Pre-Call Filtering Mechanisms Most businesses don’t have a mechanism for lead validation designed for filtering out bad and fake leads before their call gets connected to their call center. This results in increased cost-per-acquisition (CPC) for the advertiser. Impact of Lead Generation Fraud on Brands The impact of lead generation fraud on a brand’s campaigns may not always be obvious. However, knowing where to look can work to the advantage of advertisers trying to make the most out of their PPC efforts: 1. Revenue Drain If a brand has fallen victim to lead generation fraud, it means that they are spending a portion of their ad spend on fake leads. Depending on the severity of the problem, this wasted budget can make up a significant portion of the advertiser’s total ad budget. 2. Call Center Inefficiencies Fake leads, after an advertiser has unwittingly paid for them, land as calls to their sales team. As a part of their responsibilities, sales teams have to take these calls and spend valuable time attending to them. Since they never even have a chance of resulting in a sale, the entire ordeal ends up wasting the time of valuable sales resources. 3. Brand Safety and Compliance Risks If a brand is struggling with lead generation fraud, it usually means that its ads are being published by fraudulent publishers. The brand is also usually never aware of the kind of content hosted by such fraudulent websites. As a result of association with such publishers, the brand risks damaging their reputation and in extreme cases, failing compliance checks. 4. Distorted Marking Analytics Finally, such instances of fraud have the potential to skew the very advertising metrics that advertisers use to inform their campaign strategies. If, for instance, an advertiser notices that ads with a particular set of publishers are generating good engagement, they may be inclined to direct more of their budget towards these publishers. However, if the publisher is not generating genuine leads, it leads to the advertiser wasting more of their budget with them. Besides the cost of the wasted ad budget, the brand also ends up paying the opportunity cost of not directing their budget towards genuine publishers that could have enabled them to access genuinely interested prospects. Real Case This problem is exemplified by the case study of one of our clients operating in the banking sector. Our client was struggling with poor lead quality, with some campaigns registering as many as 98% of generated leads as fake. Besides the fake leads being sent their way from bad affiliates, the other challenge our client was facing was to improve the efficiency of their quickly growing call center, something that was being plagued by the menace of fake leads. Let’s look at how we helped our client overcome these issues with our tool’s state-of-the-art validation features. How mFilterIt Solves the Problem Leveraging its advanced AI-enabled technology, mFilterIt helps advertisers gain transparency in their lead funnel. Here are a few ways it solves the lead gen fraud issue for advertisers: 1. AI-Powered Click-To-Call Validation Mechanism Our AI-powered validation mechanism is designed to detect bot-driven call interaction. This is made possible with behavioral and network analysis to identify patterns and detect bot activity. Leveraging this feature, the mFilterIt tool is able to execute reliable lead validation before the call is ever initiated. This, in turn, improves call center efficiency by eliminating fake call connections.

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

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

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?

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

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?

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?

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

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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