Blog - mfilterit

Apps Running on Incent Walls: A Hidden Risk for Advertisers

Imagine that you onboard affiliates to market your newly launched app. They commit performance, and you start seeing thousands of new installs overnight. You’re at peace that you’re getting a good return out of your marketing investments. But within a few days, the users start uninstalling your app, engagement drops to near zero and you’re at the same spot where you were on Day 1. Are you thinking what went wrong? The answer could lie in Incent walls. A deceptive method used by affiliates to deceive advertisers into thinking their app campaigns are performing. Here users install apps only to earn rewards, not because they genuinely care about the app itself. While this tactic might appear to boost performance metrics, it creates a dangerous illusion of success, leaving advertisers with inflated numbers but little real value. In this blog, we’ll uncover the risks of incent fraud, how fraudsters manipulate soft KPIs using incentivized traffic, and, most importantly, how advertisers can protect themselves from wasted budgets and misleading campaign results. What Are Incent Walls? Incent walls are digital platforms that reward users with in-game currency, discounts, or other perks in exchange for installing apps or completing designated tasks. These platforms are commonly found in gaming, survey, and reward-based applications. At first, incentivized traffic might seem like easy way to boost app installs and signups. However, for advertisers aiming to acquire high-quality users who engage with their app, this method poses several serious risks. The Risks of Incent Traffic for Advertisers Low-Quality Users: The Engagement Mirage Users who install apps through incent walls are not genuinely interested in the app’s purpose. Their primary goal is to claim a reward, which means they rarely interact meaningfully with the app. This results in: Poor user retention – Users abandon the app after meeting the required conditions. Artificially inflated metrics – Install numbers rise, but true engagement remains low. Skewed data – Advertisers may misinterpret the success of a campaign, thinking they are reaching a relevant audience when they are not. High Uninstall Rates: A Costly Cycle Since incentivized users have no real interest in the app, they often uninstall it as soon as they receive their reward. This leads to: Increased churn rates – Making it harder to build a stable user base. Wasted ad spend – Marketers pay for installs that offer no long-term value. Negative app store rankings – High uninstall rates can lower an app’s ranking in stores, affecting organic discoverability. Fraudsters Manipulating Soft KPI Events Incent traffic often gets blended with organic or paid traffic to manipulate key performance indicators (KPIs). Fraudsters use this technique to: Create a false sense of campaign success – Users complete basic actions like sign-ups or tutorial completions but never become engaged customers. Drain advertising budgets – Advertisers spend on user acquisition without any long-term return. Make detection harder – By mixing incent traffic with legitimate sources, it becomes challenging to separate real user behavior from artificially boosted metrics. How to Detect Apps Running on Incent Walls Warning Signs of Incent Traffic: Unusual Traffic Spikes – If installs surge from specific sources within a short time frame, it could indicate incentivized installs. Low Engagement Rates – Users acquired through incent walls often fail to complete meaningful in-app actions beyond the reward requirement. High Uninstall Rates – A sudden drop-off in user retention post-installation is a strong red flag. Suspicious Sources – If the traffic originates from reward-based apps, it is essential to scrutinize it further. Real-World Case Studies: Spotting Incent-DRiven Fraud Sample 1: Telecom Provider’s Inflated Installs A popular telecom provider ran a campaign unknowingly on an incent app. Users were directed to install the app through a shared link and complete certain steps to earn over 3,000 coins. While installs skyrocketed, actual customer engagement remained minimal. Sample 2: Banking App’s Misleading Growth A campaign for a top-tier banking app was identified on an incent platform. Users followed a shared link, installed the app, and completed a simple action to claim rewards. The result? A surge in installs but little to no account activations or transactions. These cases highlight how incentivized traffic can inflate metrics while delivering no real business impact. How Advertisers Can Protect Themselves Implement Advanced Fraud Detection Tools Advertisers can combat incent-driven fraud by leveraging ad fraud detection solutions like mFilterIt, which provides: Real-time monitoring – Identifies traffic anomalies that signal fraudulent activity. User engagement analysis – Distinguishes between genuine and incent-driven users. Source validation – Ensures traffic quality by filtering out incent-originated installs. Focus on Quality Over Quantity Instead of chasing high install numbers, advertisers should prioritize user intent and engagement. Strategies include: Running targeted ad campaigns that attract relevant users. Optimizing app store listings to improve organic discovery. Monitoring post-install behavior to measure genuine engagement. Final Thoughts: Protecting Your Ad Budget While incent walls may appear to offer a quick boost in installs, they ultimately lead to poor-quality traffic, budget wastage, and skewed campaign analytics. By proactively identifying and blocking incent-driven installs with ad fraud detection tools, advertisers can ensure their marketing efforts drive real business value. Investing in genuine, high-intent users will always yield better long-term success than chasing artificial growth through incent traffic. Brands that prioritize transparency and authenticity in their marketing will build stronger customer relationships and maximize their return on investment. Ready to stop wasting budget on empty installs and start acquiring real, high-quality users?Connect with mFilterIt today to safeguard your app campaigns from incent-driven fraud and maximize true performance.

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The Hidden Cost of Instinct: Ecommerce Pricing Intelligence Insights

Blog, Digital Shelf Analytics / mFilterIt Experts

Most brands are still pricing based on instinct, internal costs, or outdated competitor scans. And it’s costing them, sometimes without them knowing. A 5 percent gap in your average selling price compared to the market can quietly bleed revenue week after week. Miss a category-wide discounting trend by even a few days, and you’re left reacting while others are gaining share. Winning on price today isn’t about dropping rates. It’s about knowing exactly where you stand—by SKU, by platform, by geography—and acting before competitors force your hand. Without that visibility, pricing becomes reactive, inconsistent, and risky. This article breaks down what marketers miss without doing an in-depth pricing analysis and how to fix it with real-time data. The Hidden Risks of Operating with Pricing Blind Spots Here are the risks that arise when you don’t have full visibility into their pricing environment and competitors’ moves: 1. Limited Visibility into Average Selling Prices (ASPs) Without tracking ASPs across marketplaces, brands risk flying blind. A price that seems competitive internally can be completely off when placed next to real-time market dynamics. Take this example. Your brand launches a product at $50, feeling confident in its positioning. However, the ASP for similar products across key platforms has quietly dropped to $42. Without that visibility, your brand unknowingly overpriced itself, losing both traffic and conversions. Pricing too low can hurt just as much, eroding margins without gaining meaningful volume. 2. Discounting Trends That Quietly Erode Margins Competitor discounts don’t always show up in obvious ways. Flash sales, time-limited offers, and bundle pricing often fly under the radar, but their impact adds up. If you’re only tracking list prices, you’re missing the real picture. Say a competitor has been quietly running 10% discounts every weekend. On paper, their list price matches yours. But their actual selling price is lower, and you’re unknowingly losing share—or worse, matching that price later and cutting into your own margins just to keep up. 3. Missed Opportunities in Competitive Categories High-growth categories move fast. If you’re not actively watching how competitors price within them, you risk losing share without even realizing it. Electronics, seasonal products, trending gadgets—these are the battlegrounds where pricing decisions directly shape who wins the sale. Picture this. A competitor drops prices on wireless earbuds just as demand spikes. Their volume surges. Your product sits at the same price, losing visibility, conversions, and momentum. By the time you react, the wave has already passed. 4. Non-Compliance with MAP (Minimum Advertised Price) Guidelines MAP violations usually don’t scream for attention. They slip in quietly. And if you’re not actively monitoring them, the damage creeps in just as quietly—until retail partners start picking up the phone. Think about it. An unauthorized seller lists your product below MAP on Amazon. Most buyers won’t question it. They just assume that’s the new normal. Your retail partners? They see it too—and they’re not happy about being undercut while playing by the rules. It’s not just a pricing issue, it’s a trust issue. Building a Data-Driven Pricing Strategy Here’s what a modern, proactive pricing strategy should include: 1. Benchmarking Using Real-Time ASP and Discount Data Imagine this. Your flagship product sits at $120. Competitors? They are all clustering around $105. You notice it only after weeks of slower sales and rising cart abandonment rates. At that point, it is not just about lowering prices. It is about regaining lost ground. This is where real-time benchmarking changes the game. Tracking ASPs and discounting trends live—not after a quarter closes—helps brands stay responsive, not reactive. If you are serious about staying competitive, set up monthly reviews where your prices and discount patterns are directly compared against your top 5 category rivals. No guesswork, just clear gaps you can act on. Without this discipline, even the best pricing strategies fall behind market movements that happen faster than internal processes can catch up. 2. Comparing Pricing Against Industry and Category Averages You are confident in your pricing—until the numbers tell a different story. In the fashion category, your dresses are priced 20% higher than the industry average, while your footwear is underpriced compared to competitors. Neither situation is ideal. One segment risks losing volume due to sticker shock, the other leaves margin on the table. Category-level pricing analytics show patterns that product-level thinking often misses. They reveal whether your brand’s pricing feels premium, fair, or inconsistent to shoppers browsing multiple options at once. Smart brands tackle this by setting up category-specific dashboards. These dashboards track where your pricing stands against both the industry and direct competitors, allowing you to course-correct without guessing. It is not about matching everyone else—it is about knowing when you should stand out and when you should realign. Without this layer of visibility, your pricing strategy is flying blind at the category level 3. Monitoring MAP Compliance Using OEM Codes You can’t fix what you don’t see—and MAP violations are a classic example. Most brands only catch them when a retailer complains or when brand value takes a hit. By then, damage is already done. That’s why tracking MAP compliance with OEM codes or unique identifiers isn’t just useful, it’s non-negotiable. Let’s say a SKU slips below MAP on a niche marketplace. With OEM-coded tracking, the violation is flagged immediately. No manual checks. No delays. You now have the leverage to take it down or reach out before your other retail partners even notice. This level of automation only works when MAP monitoring is baked into your pricing system. Alerts should be real-time, platform-wide, and specific to each product variant. That’s how you stay ahead, not just informed. 4. Analyzing Pricing Across Geographies and Platforms What works in Europe might fall flat in North America. And the same product can demand two very different prices depending on where—and how—it’s being sold. In European marketplaces, brands often have higher prices. Less competition, stronger demand, and fewer discount-driven shoppers make that viable. In contrast, North America moves fast and fights hard on price. Aggressive

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Programmatic Ad Risks & Brand Safety Solutions for MENA Advertiser

Blog, Ad Fraud Blog - Valid8 / mFilterIt Experts

Programmatic advertising is seeing a massive growth in the Middle East and Africa region. According to the statistics, the demand of programmatic advertising market will see a splendid growth of 7.89% between the period of 2022-2027. This increasing demand generates from the region’s growing adoption of digital advertising. Where the demand increases, the challenges emerge as well. As more brands invest in programmatic channels, the challenges increase too. Despite its advanced and automated system of ad delivery, these channels are prone to some fundamental challenges like programmatic ad fraud, brand safety and transparency gaps. In this blog, we will break down the challenges in programmatic advertising, its impact on advertiser’s campaigns and how marketers can solve it and make their programmatic campaigns effective and brand safe. An Overview of Challenges in Programmatic Ads in MENA region Advertisers are often drawn to this due to its promise of scalability, automation and precision targeting. However, these platforms pose several structural and operational challenges that limit the growth for the advertisers and give a picture they didn’t expect. Here are a few key challenges in programmatic that the advertisers in MENA region face today: – Lack of Transparency What is not visible cannot be trusted. Yet, advertisers have to spend trusting the platforms, based on metrics shared, without knowing where their ads are showing up. One of the most persistent issues in programmatic advertising is the limited visibility into where budgets are being spent, who is watching their ads, where their ads are placed. The supply chain often involves multiple intermediaries — DSPs, SSPs, trading desks, and more — each adding layers of complexity. As a result, advertisers frequently struggle to track where their ads are running, how much is being spent at each step, and whether the impressions served are real or just bot driven. – Rising Threat of Programmatic Ad Fraud MENA’s digital ecosystem, while growing, remains vulnerable to various forms of programmatic ad fraud — from invalid traffic (IVT) and fake clicks to domain spoofing and impression laundering. Without robust ad fraud detection and prevention measures, a significant portion of programmatic budgets risks being wasted on non-human or low-quality traffic, diminishing campaign performance and brand trust. – Limited Access to Quality Inventory Access to high-quality, premium inventory is still a challenge across many MENA markets. While larger markets like the UAE and Saudi Arabia offer better options, advertisers targeting wider regional audiences often end up buying lower-tier inventory. This affects not just campaign reach but also engagement, conversion rates, and brand perception. And adding to this is the problem of ads appearing beside any unsafe content. This leads to a brand reputation issue for advertisers. – Measurement and Attribution Gaps Many advertisers in the region continue to rely on basic performance metrics like clicks and impressions. However, these surface-level KPIs do not paint a full picture of campaign effectiveness. Advanced measurement models like multi-touch attribution (MTA) are still not widely adopted, making it difficult to connect programmatic spend to actual business outcomes like customer acquisition and revenue growth. – Fragmented Technology Infrastructure The level of programmatic maturity varies significantly across different MENA countries. What works in the UAE or Saudi Arabia might not scale effectively in Egypt, Kuwait, or Morocco due to differences in publisher ecosystems, audience behavior, and available technology. This fragmentation complicates regional planning and demands a more localized, agile approach to media buying. – Dependency on Platform-Driven Metrics Programmatic advertising demands specialized expertise across campaign setup, optimization, fraud detection, and analytics. In the MENA region, there is still a noticeable gap in skilled programmatic talent, leading brands to depend heavily on platform-driven metrics. This dependency often results in less control, reduced transparency, and missed opportunities for optimization. Emerging Demand of Programmatic Video Advertising in MENA In the last few years, video content has also become a major medium to drive engagement. Therefore, programmatic video advertising is also seeing a rise in the MENA region. However, this medium also experiences challenges like Frequency Capping Breach, where ads are shown more than the times it is required leading to overexposure and causing ad fatigue for viewers. How to Solve Programmatic Advertising Challenges — and Where mFilterIt Supports As programmatic ads expand across the MENA region, brands need more than just automation — they need clarity, credibility, and control. Here’s what an effective programmatic approach looks like — and how mFilterIt supports advertisers along the journey: – Gaining True Transparency into Ad Traffic and Placements Without knowing where ads appear and who is engaging with them, optimization becomes guesswork. Valid8, our ad fraud detection solution integrates directly with Demand Side Platforms (DSPs) and other sources to provide advertisers with independent visibility into traffic sources, ad placements, and ad inventory quality across the programmatic ecosystem. With this transparency, brands can make smarter, evidence-based decisions for campaign planning and media buying. – Validating Traffic and Detecting Fraud Early MENA’s growing digital market also faces complex threats like invalid traffic (IVT) and domain spoofing. Our ad traffic validation solution applies behavioral analysis, heuristic checks, deterministic models, and frequency validation to verify ad interactions. This enables advertisers to distinguish real users from bots and invalid sources — safeguarding campaign data and ensuring budgets reach intended audiences. For advertisers spending on programmatic video advertising can curb the impact of frequency capping breach by leveraging the frequency cap monitoring solution. This enables advertisers to keep track of how many times their ads are shown to the users, and if they exceed the frequency cap limit. Proactive monitoring reduces the chances of overexposure of ads to the users and helps the advertisers to genuinely reach their targeted audience. – Identifying Safer and Higher-Quality Inventory Ad misplacement can quickly damage brand trust. Valid8 flags suspicious, inappropriate, and Made-for-Advertising (MFA) sites, providing advertisers with placement-level insights. Brands can then proactively blacklist unsafe environments and prioritize premium, brand-safe inventory for better engagement and reputation management. – Enabling Better Campaign Optimization By delivering deep, independent insights — such

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Why QSRs Need Digital Commerce Intelligence & Key Features to Know

Blog, Digital Shelf Analytics / mFilterIt Experts

The global Quick Service Restaurant industry, as of 2024, was valued at $971 billion. By the end of this year, the industry is expected to grow to $1055.48 billion. In the near future, the industry is expected to continue growing at a CAGR of 9.01%, being valued at $1930.14 billion by 2032. Clearly, these aren’t small numbers. The Quick Service Restaurant model is quickly emerging as a lucrative business and naturally will attract a lot of new players in the coming years. This growth is being powered by a number of factors. The most obvious one is the growing affinity of users towards digital ordering. Similarly, the fantastic growth of third-party food aggregators like Uber Eats, Zomato, Swiggy etc. has added some truly potent fuel to the fire. When the barrier to entry in the industry has become so low, differentiating your business from the rest can be difficult. Thankfully, there’s a proven way to succeed in such a dynamically growing economy- to make data driven decisions by implementing digital commerce intelligence. Let’s see how this intelligence works and how it is obtained in the following sections. The Need for Digital Commerce Intelligence in QSRs To say that in the last decade, consumers have changed the way they make purchases would be an understatement. Thanks to trends and technologies like online food delivery, mobile ordering, and digital loyalty programs, modern consumers are driven by very different motivations as compared to a decade ago. For instance, the abundant availability of options has diminished the brand recall value of even the most memorable businesses and shortened the attention spans of prospects. Getting in front of the right audiences may have become easier in theory, since aggregator platforms and search engines can potentially direct interested audiences towards modern QSRs. However, these platforms have become overcrowded and even with access to targeted audiences and that’s why, getting visibility has become a battle for most QSRs. Here, getting access to and acting upon real-time insights can prove incredibly advantageous. Such insights, usually delivered by data intelligence platforms, can help QSRs improve operational efficiency by enabling better management of demand forecasting, stock levels, and using these metrics to further devise better pricing strategies and menu audits. This is just one aspect of using digital commerce intelligence. With all that said, all the advantages associated with digital commerce intelligence depend on choosing the right tool. How do you do that? Let’s find out in the next section. Key Aspects to Look for in a Digital Commerce Intelligence Solution Specific features that may be important to individual businesses may vary when it comes to picking a digital commerce intelligence solution. However, there are some common features that may be relevant to most QSR business. These include: – Market & Competitive Insights: One of the most important functions of a digital commerce intelligence tool is to enable QSR businesses to make better business decisions. The smart way to do that is to track category trends, pricing, and competitor strategies and hence, the ability to track these metrics is a non-negotiable when picking a digital commerce intelligence tool. – Customer Sentiment Analysis: Choosing a tool that can help you understand consumer feedback from different sources can prove incredibly advantageous. When picking a tool, make sure it has the ability to pull and analyse customer feedback from sources like third-party review websites, search engine listings, and social media platforms. – Actionable Data for Decision Making: Finally, when picking a digital commerce intelligence tool, you are looking for one with an easy-to-understand and user-friendly dashboard. This is important because all the data collected and analysis done by the tool will be presented to you in the dashboard. Here, it should be available in a manner that allows business owners or brand managers to derive actionable insights from the data and use it to inform quick optimization actions and long-term strategies. The best tools in the market will even derive the insights for you, using AI-enabled suggestions. The Impact of Digital Commerce Intelligence on QSR Growth So what kind of a difference can a digital commerce intelligence tool make? Here are some advantages any QSR business can start experiencing almost immediately upon implementing a solution: – Better Menu and Pricing Decisions: Using insights from marketing and competitive analysis and combining them with insights from consumer sentiment analysis can help QSR businesses make better pricing and menu-related decisions. This cannot just potentially improve sales figures but can also optimize menu items for demand and better inventory management. – Improved Customer Retention: With consumer sentiment analysis and insights from performance of campaigns and promotional offers, QSRs can inform better consumer retention strategies. The same data can also be used to create personalised experiences for consumers and incentivise consumer loyalty in a meaningful and impactful way. – Maximized Revenue Opportunities: Analysing the data derived from a digital commerce intelligence tool can help QSRs identify the conditions and times for demand surges. Similarly, analysis of historical data can also help QSRs identify ideal delivery zones and determine which upselling strategies work the best with specific customer personas. Conclusion In a digital economy, access to and the intelligent use of intelligence can put any brand ahead of their competitors. On the flipside, not using the vast amount of data available online to their advantage can prove to be a huge lost opportunity cost for QSR brands. Choosing and implementing the right tool can pay off exponentially in terms of more rapid and sustainable growth, improved operational efficiency, and heightened brand trust. In other words, implementing a data-driven strategy is not optional for QSR brands that are serious about their growth. Have a Quick service restaurant? – Connect with mFilterIt experts to learn how we can help.

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

Blog, Ad Traffic Validation / mFilterIt Experts

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

Leave a Comment / Blog, Ad Fraud / mFilterIt Experts

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

Blog, Ad Fraud / mFilterIt Experts

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

Blog, Ad Traffic Validation / Amit Kumar

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

Blog, Brand Safety & Suitability / mFilterIt Experts

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

Blog, Brand Safety & Suitability / mFilterIt Experts

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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