mFilterIt Experts

Decoding complex digital challenges like ad fraud, brand safety, brand protection, and ecommerce intelligence for brands to help them advertise fearlessly.

Ecommerce analytics

Amazon’s Big 2025 PPC Algorithm Change: Is Your Ad Spend Still Working?

In 2025, winning on Amazon isn’t just about spending more — it’s about spending smarter. Amazon has quietly reengineered its algorithm, shifting from a pure CPC-bid system to one that prioritizes traffic quality, listing performance, and conversion strength. If your entire Amazon strategy revolves around running ads, you’re likely overspending and underperforming. Here’s how the landscape has changed — and what your team should do next What’s Actually Changed in Amazon’s PPC Algorithm?  The pay-to-play environment still exists, but it’s now part of a much bigger game of trust, signals, and shopper behavior. Here’s what matters in 2025:  External Traffic Is Now a Ranking Factor Amazon now rewards listings that attract off-platform traffic — from Google search, Instagram stories, influencer campaigns, and even emails. This is a game-changer. 1. Why? External traffic signals real consumer demand. It tells Amazon your product is being sought after — not just served through paid impressions.  This is key for sellers focused on campaign optimization and Amazon ad ROAS. External traffic = better organic ranking.  2. Organic Sales = Algorithm Trust  Each organic sale tells Amazon your product sells on its own merit. The more this happens, the more visibility your product earns — reducing your dependency on paid ads.  3. Insight: Brands with strong ecommerce analytics and product-market fit see their share of shelf expand even without heavy ad spend.  Your Listing Is Now the Decider  Clicks alone don’t cut it anymore. Amazon now evaluates:  Time spent on the product page  Scroll and engagement behavior  Bounce rates and exit paths  Conversion rates vs. competitor redirection  If your listing isn’t optimized to convert, your ad dollars are being wasted — silently.  Use ad monitoring and content analyser tools to diagnose weak product pages.  Sponsored Brand Ads Are More Powerful No longer just top-of-funnel fluff, Sponsored Brand Ads now directly influence visibility and conversions. These ad formats tell brand stories, and Amazon is rewarding storytelling that converts. Use Amazon ad optimization strategies that include SBAs to capture high-intent traffic and build brand equity. Where mFilterIt by mScanIt Come In Wondering why visibility is dropping, why ROAS is flat, or why you’re losing to lesser products?  Meet mScanIt by mFilterIt — built for ecommerce-first brands navigating Amazon’s new rules.  It delivers real-time ecommerce analytics across four key fronts: Competitive intelligence: See where competitors are stealing your shelf space Product content performance: Understand if your listings are supporting or sabotaging your ad performance Pricing mismatch alerts: Catch and correct inconsistencies that kill conversions Campaign optimization insights: Identify ad fraud, misattribution, or underperforming placements Whether you’re fixing Amazon campaign fraud or maximizing sponsored brand visibility, mScanIt helps performance teams win.   Amazon’s Algorithm Is Now Reading Your Brand — Not Just Your Bid If you’re still running Amazon Ads like it’s 2022, you’re burning budget. Today’s system is a trust engine, not a pure auction.  Ask Yourself:  Is your product page built to convert cold and warm traffic? Are your prices consistent across channels? Are you riding the wave of organic sales spikes? Are you generating demand beyond Amazon’s walled garden? Because in 2025, Amazon’s algorithm isn’t just ranking your ads — it’s reading your entire brand behavior. DR for Amazon Sellers & Performance Teams Amazon’s 2025 update favors traffic quality over bid size External traffic and organic sales directly boost rankings Listing content and conversion behavior are key algorithm signals mScanIt provides ecommerce analytics and campaign optimization insights in real time Success now requires ad monitoring, pricing analysis, and performance storytelling Explore mFilterIt’s Digital Commerce Intelligence  

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Brand bidding in affiliate marketing

Google’s May 2025 Ad Safety Update: Why It Won’t Stop Brand Bidding Abuse

Google’s latest ad safety update may have made headlines, but it hasn’t solved the real problem.  With buzzwords like “transparency,” “cleaner search ads,” and “policy enforcement,” the May 2025 update sounded like a promise. But while the PR narrative got sharper, brand bidding abuse only got more precise.  It’s time to stop mistaking policy changes for actual protection.  When Brand Equity Gets Hijacked You’ve built your brand with care — through years of campaigns, influencer tie-ups, loyalty programs, and crores spent in media to earn customer trust.  But when someone types your name into Google?  You’re not the first result. An “affiliate” is.  They’ve bid on your own brand keyword. They’ve cloned your ad copy. They’re siphoning traffic meant for you — and worse, charging you commission for it.  This isn’t performance marketing. It’s affiliate abuse in plain sight. According to mFilterIt, over 38% of brand traffic in affiliate networks is exposed to keyword bidding, impersonation, and last-click hijacking — often masked as legitimate support.  These actors aren’t helping you grow. They’re exploiting your brand equity — and eating away at the organic demand you’ve already earned.  Here’s What the Data Shows In a recent case with a major online travel portal, mFilterIt uncovered the scale of the problem:  64% of brand keyword hours across cities showed white spaces ₹1.77 million was saved in just 20 days by identifying and reclaiming these gaps. CPC dropped by 52.47%, and cost per conversion fell by 46.15% Meanwhile, organic bookings jumped 86.1% All because of one trigger:  mFilterIt’s brand keyword and white space detection system caught what no platform tool flagged.  Why Google’s Policy Isn’t Enough Google’s update focuses on impersonation — but brand bidding doesn’t need a disguise. It works in the gray areas:  Tweaked match types  Vague copy  Legal but misleading tactics  By the time a violation is caught, the damage is already done.  You can’t rely on platform policing after the fact. You need real-time Affiliate monitoring that sees what Google doesn’t.  mFilterIt Fills the Gap Google Leaves Here’s what we do (and what platforms can’t):  Detect brand bidding violations in real-time  Identify unauthorized affiliates hijacking your brand traffic Map white space  opportunities city-by-city, hour-by-hour  Plug CPC leaks before they burn through budgets  Don’t Just Trust the Platform. Protect Your Brand. Google may promise clean ads, but visibility still needs verification.  Before assuming your campaigns are safe, ask yourself:  Are you measuring true presence or just platform delivery?  Curious how brand bidding could be bleeding your paid search?  Explore mFilterIt’s Ad Fraud Solution

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brand safety in contextual targettig

Brand Safety in 2025: It’s Not a Checkbox Compliance Anymore for Digital Brands

Imagine you’re investing in branding ads to be visible among your target users, but instead, your ads are getting placed beside content that harms your brand image. And unknowingly, you’re funding that content, and your users perceive your brand to be associated with this content. Something similar happened during the recent incident of the Pahalgam attack. Many brands’ ads were appearing beside the terrorist attack news, putting them in a negative light. An analysis done by mFilterIt indicates that 7% to 12% of brand safety violations occur in campaigns that do not prioritize curated content platforms. Brands using traditional methods to block brand unsafe ad placements often lack contextual awareness, resulting in either excessive blocking of appropriate content or overlooking potentially harmful placements. Every misplaced ad leads to erosion of brand integrity and credibility, making viewers assume your brand is funding misleading and harmful content digitally. This directly influences the audience’s perception of your brand, and in worst cases boycotting a brand. Therefore, it is more important than ever for advertisers to keep a vigilant check and control over brand placements and brand safety in the digital advertising landscape. So now the question is for advertisers and marketers globally – Are you sure your ads are not appearing next to brand-unsafe content, fake news, conspiracy theories, or any kind of harmful content that might hurt the emotions of your audience? If not, keep reading ahead. In this article, we will explore the new threats hurting brand reputation, why traditional safeguards are no longer enough, why regions like the USA, MENA, and India must embrace a new level of vigilance – brand safety solutions, and how these solutions ensure brand relevancy and contextual targeting.  How are Brand Safety threats evolving?  Brand safety threats have grown in complexity, driven by automation, evolving content formats, and the unpredictable nature of programmatic ecosystems.  1. AI-generated misinformation and deepfakes The rapid increase in use of generative AI has enabled the creation of hyper-realistic fake content. From synthetic news anchors to manipulated interviews, these deepfakes blur the lines between reality and fiction. When brands are unintentionally associated with such misleading or polarizing content, reputational damage is severe and swift. 2. UGC and influencer-led campaigns With the rise of the creator economy, brands are increasingly promoted in environments they don’t fully control. User-generated content and influencer endorsements can shift tone unpredictably moving from inspiring to controversial in seconds. A misaligned post or unmoderated comment thread can quickly escalate into a brand crisis. 3. Programmatic advertising and algorithmic misplacement While programmatic buying enables scale and efficiency, it often prioritizes impressions over context, which can now be easily manipulated by fraudsters using malicious techniques. This means brands may find themselves appearing next to offensive, misleading, extremist sites, or politically divisive content without ever realizing it until it’s too late. 4. Unsafe YouTube ad placements Despite platform controls, YouTube remains a challenging space for brand safety. Ads can still appear before or within harmful videos, ranging from conspiracy theories to extremist content or inappropriate children’s content disguised as family friendly. This risk of “non-contextual advertising and brand relevancy” remains one of the most visible and publicly damaging threats to brands. 5. M Algorithms M algorithms refer to poorly trained or misaligned algorithms that recommend, rank, or pair with content in unintended ways. For instance, a brand-safe ad could end up placed between two harmful videos due to flawed recommendation logic. These algorithmic failures erode trust and make it harder for brands to control the digital environment in which they appear. 6. Volatile content categories and news cycles Real-time global events, from armed conflicts and political protests to celebrity scandals and financial crises, often drive unpredictable spikes in sensitive content. Without real-time scanning and contextual awareness, brand ads can appear alongside highly charged, emotionally volatile material that damages consumer trust. Why MENA, USA, and India Demand Specific Attention Solving brand safety is not a one-size-fits-all strategy. Every region has its own nuances and with each unique requirement, the solution cannot be the same. Similarly, MENA, the USA, and India represent three distinct digital ecosystems each with its own blend of opportunity and risk. Here’s how: MENA: High Sensitivity, Low Moderation Culturally sensitive content: Misplaced ads risk backlash due to religious and societal norms. Volatile news cycles: Frequent political or religious events heighten reputational risks. Under-moderated local platforms: Arabic and regional languages lack strong content controls. Influencer-driven marketing: Widespread but lacks structured brand safety safeguards. USA: Polarization and AI-Powered Misinformation Politically polarized media: Brands risk appearing near divisive or partisan content. Deepfakes and fringe content: Brand ads are increasingly at risk of appearing alongside conspiracy theories, hate speech, or deepfakes. Consumer activism: Both advertisers and publishers face growing pressure to moderate content more effectively and ensure responsible media buying practices. India: Language Diversity and Informal Ecosystems Vernacular content environment: With over 20 officially recognized languages and hundreds of dialects in use, content moderation and contextual understanding must be language-specific. Unregulated affiliate ecosystems and third-party ad networks: Continue to operate without standardized guidelines for ad quality, traffic authenticity, or contextual advertising relevance. Socio-political sensitivities: Content that’s acceptable in one state may be deemed offensive in another, necessitating hyper-local risk assessment. Therefore, for global brands operating across these markets, understanding and adapting solutions addressing regional, cultural, and political sensitivities is no longer optional but a strategic necessity. Why Traditional Brand Safety Solutions Fail to Solve This Gap? With the evolved landscape and the new threats emerging, traditional methods of brand safety like keyword blacklisting have become outdated. Once the gold standard of brand safety falls short in the arena of dynamic formats and unpredictable algorithms. Brands that still rely solely on outdated methods like keyword blacklisting missing real threats entirely because: It Lacks context: A keyword like “violence” might be blocked even when used in a harmless setting (e.g., a film review). This leads to missed opportunities and reduced reach. Over blocking and under blocking: Generic blacklists often over-filter safe content while still allowing

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Ad Fraud in MENA: Understanding Web & App Fraud and Its Business Impact

In recent years, the MENA region has emerged as one of the fastest-growing digital advertising markets in the world. With ad spend projected to exceed $8 billion by 2026, the region is experiencing an unprecedented surge in number of mobile-first users, rising eCommerce platforms, and innovative app ecosystems. But along with this digital acceleration comes an equally aggressive threat: ad fraud.  According to IAB MENA, up to 20% of ad budgets in the region, roughly $1.25 billion in 2023, may have been wasted due to fraudulent activity like fake clicks, spoofed installs, bot traffic, domain spoofing, and misattributed conversions, etc. And it’s only getting worse. This budget wastage is projected to go up to $1.6 billion by 2026. This staggering figure reveals a silent budget drain that’s not just affecting the bottom lines of brands in MENA – it’s distorting performance metrics, eroding trust, and misleading optimization decisions.  If your campaigns are optimized based on corrupted data, your ROAS is lying to you. If you’re relying on outdated, conventional ad fraud detection tools, you’re exposed to sophisticated tactics that go undetected in your app and web funnel.  Now the question that arises is – How do we tackle this effectively across the entire ecosystem?  Ad fraud in MENA is evolving rapidly, and so should your defense tech stack.  In this article, we’ll explore how ad fraud violates across web and app ecosystems in MENA, why traditional verification methods fall short, and the need for advanced ad fraud detection solutions to protect the digital ad spending of digital-first brands.  What Is Ad Fraud and Why Is MENA Especially at Risk? The Middle East and North Africa (MENA) region faces a particularly elevated risk of ad fraud. Here’s why:  Rapid Digital Growth and Increased Ad Spend Booming Digital Adoption: MENA is witnessing an explosive expansion of digital connectivity and e-commerce, prompting a substantial shift in brand budgets towards online advertising to engage the large scale of digital audiences. Prime Target for Fraudsters: This escalating investment naturally makes the region a highly profitable target for sophisticated ad fraud techniques. Specific Vulnerabilities in the MENA Ad Ecosystem Reliance on Aggregators and Smaller Networks: Many regional marketers depend on affiliate aggregators or smaller ad networks, which often lack robust transparency and rigorous vetting procedures, inadvertently increasing exposure to fraudulent activities. Trust-Based Partnerships: The prevalence of trust-based business relationships can sometimes bypass the need for stringent validation processes, creating openings for fraudsters to infiltrate the ecosystem. Localization Gaps: Generic ad fraud detection tools may not be fully optimized for MENA’s diverse languages and distinct user behaviors, allowing certain fraudulent patterns to slip through undetected. Lack of Benchmarks: The scarcity of widely accepted, region-specific benchmarks for campaign performance complicates the identification of anomalies and the accurate assessment of campaign effectiveness, masking the impact of fraud. Fragmented Technology Infrastructure: Varying levels of programmatic maturity across different MENA countries can result in inconsistent ad delivery, measurement, and fraud detection capabilities. Dependency on Platform-Driven Metrics: A common over-reliance on metrics provided directly by ad platforms, often without independent verification, can lead to a lack of control and transparency, making fraudulent metrics harder to discern.  Types of Web and App Ad Fraud Impacting MENA Brands Understanding how ad fraud operates across the funnel is critical to combating it effectively. Here are the most common forms of ad fraud affecting digital campaigns in the MENA region:  Web Fraud Click Fraud & Click Spamming: Fraudsters use bots or scripts to simulate user clicks, inflating CPC costs and diminishing ROAS. Pixel Stuffing & Ad Stacking: Ads are rendered invisibly (e.g., 1×1 pixels) or layered behind other content to be counted as impressions but never seen. Domain Spoofing: Fraudsters mimic premium publisher domains to sell low-quality or non-existent inventory.  Lead Gen Fraud: Fraudsters submit fake or low-quality leads to exploit CPL campaigns, draining budgets and sales resources. App Fraud Click Injection: Malicious apps on user devices simulate clicks just before a legitimate install, stealing attribution credit. Incentivized Installs: Users are offered rewards (e.g., cashbacks or discounts) to install apps without true interest in skewing retention metrics. Fake Installs & SDK Spoofing: Bots mimic install behavior or exploit app SDKs to fake installs and in-app engagement. When such fraud goes undetected, it doesn’t just waste budgets – it corrupts analytics, misleads media decisions, and diminishes LTV (lifetime value) from fraudulent users who will never convert or engage meaningfully.  How Ad Fraud Impacts Businesses in MENA  Wasted Spend: A large portion of ad budgets go to non-human or low-value traffic sources. Skewed Attribution: Fraudulent actions misattribute conversions, leading brands to invest in ineffective channels or partners. Reduced ROAS: Since bot-driven or false installs never lead to real engagement, return on ad spend drops. Data Misalignment: KPIs become unreliable because of incorrect data, affecting optimization decisions and long-term planning. Brand Risk: Ads placed on spoofed or irrelevant domains damage brand integrity. Fraud also masks real performance issues, giving marketers a false sense of success when in reality, the wins are artificially inflated. Why Traditional Methods Aren’t Enough in MENA’s Digital Landscape  Despite the rising complexity of ad fraud schemes, many advertisers in the MENA region still rely on outdated or incomplete methods of verification. They don’t offer the speed, depth, or contextual intelligence modern marketers need. Here’s why traditional methods no longer provide adequate ad fraud and mobile app fraud protection:  Manual Audits and Blacklists Are Reactive, Not Scalable Relying on manual traffic reviews or static blacklists can only detect known and repeated patterns, missing newer, evolving fraud behaviors.  In a high-volume, mobile-first market like MENA, fraud detection must be proactive and automated to catch dynamic threats before damage is done.  Lack of Standardization Across Ad Tech Partners MENA’s fragmented ad ecosystem includes multiple intermediaries and networks, many of which lack unified fraud detection protocols.  This inconsistency creates data silos and blind spots across platforms, making it difficult for advertisers to trace where fraud is occurring or hold specific partners accountable.  Blind Spots in ROAS, LTV, and

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Mobile Ad Fraud: Understand How it Kills Your ROAS and LTV & What You Can Do About It

Mobile app advertising is all about data coming from CPI campaigns – ROAS and LTV being the go-to metrics to measure campaign performance and success. But are you sure the metrics you are relying on are giving you the right results?  The numbers on your dashboard are not always true.   As advertisers pour more budget into mobile performance campaigns, many overlook critical vulnerabilities – mobile ad fraud. It’s not just a line-item loss, it’s a performance killer that inflates Return on Ad Spend (ROAS) and erodes Customer Lifetime Value (LTV).  Fraudsters exploit the systems marketers depend on – attribution models and campaign metrics – using sophisticated tactics like click fraud, fake installs, click injection, SDK spoofing, etc.   The result? Campaigns scale based on fake signals, and strategies built on manipulated data lead to long-term business erosion.  In this article, we’ll break down exactly how mobile ad fraud works, why it’s killing your ROAS and LTV, and the steps you can take right now to combat fraud and protect your mobile app marketing investment.  What is Mobile Ad Fraud? Mobile ad fraud is the deliberate manipulation of ad ecosystems to produce fake user interactions – clicks, installs, or post-install events that appear legitimate but are entirely fabricated. These activities are done by sophisticated fraud networks using a range of tools, from bots and emulators to stolen device IDs and malicious SDKs.  The primary objective of fraudsters is to earn money by draining advertising budgets without delivering any real user engagement or business value. This type of fraud not only eats into your ad spending but also corrupts the data you rely on for campaign optimization and ROI measurement.  According to mFilterIt’s analysis, there has been a significant rise in ad fraud in apps at each level of the funnel, the highest being at the install stage:  Common Types of Mobile Ad Fraud Include: Click fraud: Use of bots or click farms to generate invalid clicks, depleting budgets without real engagement. Click injection: Malicious apps trigger fake clicks just before install happens, hijacking attribution for organic or paid traffic. Install farms: Real humans or emulators install apps repeatedly to simulate legitimate installs, often incentivized by rewards. SDK spoofing: Hackers simulate in-app events by manipulating SDK data, making it appear to be genuine user actions. Device farms: A collection of real or emulated devices are used to generate large volumes of fake installs and activity. Attribution fraud: Fraudsters use methods like click spamming or injection to steal credit for installs they didn’t drive.  Understanding the Mobile Attribution Flow To understand how mobile ad fraud destroys ROAS and LTV in mobile advertising campaigns, it is also important to understand the mobile attribution flow. Here’s a step-by-step breakdown of how it works: A user taps on an ad shown on their device.  That click is first logged by the media partner responsible for the ad placement, and the user is redirected to the relevant app store.  Simultaneously, the click data is sent to a Mobile Measurement Partner (MMP) who stores this engagement.  The user installs and launches the app.  When the app is opened for the first time, it triggers an SDK that sends install data back to the MMP.  The MMP matches this install event to previous ad clicks using algorithms and attribution windows.  If a match is found, the install is labeled as ‘non-organic’ and credited to the corresponding media partner.  This data is then reflected in the advertiser’s analytics dashboard, forming the basis of ROI measurement.  Fraudsters use techniques like click injection or spoofed signals to insert themselves into the attribution path at the last moment, stealing credit for real installs or faking installs altogether.  How Mobile Ad Fraud Impacts Your ROAS Return on Ad Spend (ROAS) is one of the most critical metrics for marketers. It tells you whether your advertising investment is bringing returns or not.   1. Inflated ROAS from Fake Installs Fraudulent installs, generated by bots or device farms, appear legitimate on the surface. Campaign dashboards show low Cost Per Installs (CPI), leading marketers to believe their campaigns are effective. But these “users” never convert or engage – they don’t exist.  This false sense of performance skews ROAS calculations, making underperforming channels look profitable. As a result, marketers double down on ineffective campaigns, throwing more money into a bottomless pit. 2. Simulated Post-Install Events Fraudsters use advanced fraud techniques to spoof in-app events such as sign-ups, purchases, or logins to mimic user engagement. These simulated activities trick attribution platforms into registering conversions and inflate downstream metrics.  Campaigns are then optimized for behavior that never actually occurred, misguiding everything from creative strategy to channel selection. 3. Budget Drain Through Attribution Hijacking Fraudsters don’t need to fake the whole user’s journey. Sometimes, they hijack attribution through click fraud, click injection, or click spamming. They steal credit for installs that were actually organic or driven by legitimate partners.  This leads to misallocation of ad spend, with high-performing partners being undervalued while fraudsters receive undue payouts, degrading overall ROI.  How Mobile Ad Fraud Impacts LTV Customer Lifetime Value (LTV) is a long-term metric that reflects the revenue generated by a user over time. LTV is foundational for forecasting, retention strategy, and sustainable growth. But fraud undercuts this in serious ways. 1. Zero-Value Users Coming via Incent Fraud Fake installs and incentivized users attained through malicious techniques like install farms or incent fraud typically show no engagement beyond the install. These users don’t make purchases, complete onboarding, or return to the app, meaning zero contribution to lifetime value. 2. Skewed Retention Metrics When non-human or low-intent users are included in your data, LTV projections are overestimated. You might assume a healthy user base when in reality, it’s full of churned or non-existent users.  3. Deceptive CAC-to-LTV Ratios A campaign might look profitable based on CPA and early event metrics, but if LTV is inflated due to fake users or spoofed events, the actual value delivered will never justify the acquisition cost.  What Marketers Can

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Affiliate Fraud

Affiliate Fraud 2.O: How AI-Generated Sites Are Gaming Your Attribution Models

Affiliate marketing has long been one of the most performance-driven, ROI-focused channels in the digital advertising landscape. However, the emergence of AI and the need for training AI LLMs has further complicated the scenario. Fraudsters now leverage AI to automate deception and manipulate attribution models. This is what we call affiliate fraud 2.O. As AI lowers the barriers to content generation and website development, the risks of affiliate fraud are expanding in both scope and sophistication. These aren’t just random bots; they’re intelligent, deceptive systems that erode ROI without being easily detected. How Affiliates Manipulate Attribution Models Using AI Generated Techniques? 1. AI-Generated Microsites: Fraudsters use generative AI to mass-produce legitimate-looking blogs and review sites that host affiliate links. These sites offer no real user value and exist solely to siphon attribution credit. 2. Short-Session Click Fraud: AI sites create traffic with sessions lasting just seconds – timed to occur before a user converts, thereby stealing last-click attribution undetected. 3. Bot-Assisted Click Simulation: Using AI-powered automation tools, fraudsters mimic human behaviors like scrolling, clicks, and form fills – tricking attribution platforms into seeing them as valid users. 4. Fake Click-Through Journeys: Entire user journeys are faked using AI – from blog visits to conversion events, mimicking real behavior and misleading attribution systems. 5. Traffic Laundering Through AI Networks: Fraudsters mask their origins by routing traffic through multiple AI-generated sites, using proxies and spoofing to make detection nearly impossible. 6. Pixel Stuffing and Ad Stacking with AI Layouts: AI-created page templates insert invisible ad pixels or stack multiple ads in one slot, creating false impressions and clicks. 7. Link Injection Based on User Behavior: AI scripts detect when a user is about to convert and inject affiliate links at the last second – grabbing credit without influencing the purchase. These sophisticated techniques result in inflated affiliate payouts, inaccurate campaign data, and wasted marketing budgets. According to mFilterIt’s first party analysis of 220 campaigns run in 2024, 25% and 30% of fraud was detected across affiliate campaigns for visits and leads respectively. How mFilterIt Can Help Fight Against AI-Generated Affiliate Frauds At mFilterIt, we offer a robust, intelligence-led ad traffic validation solution – Valid8, to address the challenges of AI-driven affiliate fraud. 1. End-to-End Traffic Validation: We analyze the full user journey from impression to conversion to detect anomalies like short sessions and unnatural behavior patterns. 2. Session-Level Intelligence : We go beyond surface metrics to evaluate behavioral depth, device fingerprints, and engagement patterns distinguishing real users from bots. 3. Proactive Campaign Monitoring : Our system continuously scans geographic spikes, click bursts, and domain impersonation helping brands catch rogue affiliates fast. Conclusion: Affiliate Marketing Demands Smarter Protection Affiliate fraud is no longer simple or visible. It’s intelligent, fast, and quietly drains your performance budgets. As the threat evolves, so must your defense. mFilterIt helps you go beyond basic fraud filters with a fraud detection solution providing actionable insights keeping your ecosystem clean, compliant, and high performing. Ready to reclaim your ROI? Let us help you outsmart affiliate fraud.    

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programmatic-ad-fraud

Step-by-Step Guide for Marketers to Run Fraud-Free Programmatic Ad Campaigns

With brands shifting a large amount of their budgets to digital platforms, programmatic advertising plays a crucial role in how brands optimize their budget at each stage of the funnel.  The programmatic advertising market in India is still considered to be at a nascent stage; however, it has taken a steep curve and is not going to stop.  According to the Dentsu-e4m Digital Report 2025, programmatic advertising contributed  ₹20,686 crore, accounting for 42% of India’s digital media expenditure by the end of 2024, reflecting a 21% growth over 2023. The report further projects this momentum will continue, with programmatic expected to represent 44% (₹30,405 crore) of the digital advertising market by 2026, growing at a compound annual growth rate (CAGR) of 21.24%.  With the power to automate media buying and provide real-time data, programmatic campaigns offer unmatched scalability and precision. But with great opportunity comes significant risk. If not handled carefully, programmatic campaigns can fall prey to inefficiencies and ad fraud, draining budgets and damaging brand reputation.  This article will guide you through the fundamentals of programmatic advertising, key strategies for success, and how to safeguard your campaigns from programmatic ad fraud. Whether you’re a marketer, advertiser, or decision-maker, this comprehensive guide will help you run campaigns that are both effective and safe.  What is Programmatic Advertising? Programmatic advertising is the automated method of buying and selling digital ad inventory through sophisticated software and real-time bidding (RTB) technologies. Unlike traditional advertising, which involves direct negotiations and manual placements, running programmatic ads enables instant, data-driven decisions regarding which ads to show to which user, and at what price. This automation brings efficiency, scale, and precision, allowing marketers to serve relevant ads to the right audience, at the right time, across websites, mobile apps, and connected TV (CTV) platforms.  Challenges and Limitations in Programmatic Advertising 1. Lack of Transparency Across the Supply Chain The programmatic ecosystem involves multiple intermediaries – DSPs, SSPs, ad exchanges, data providers, and more. This fragmentation often leads to limited visibility into where ads are being served, how much each party takes from the media spend, and what environments your brand appears in. This is referred to as “programmatic black box” making it difficult to determine how much of the budget reaches the publisher versus being absorbed by hidden fees and commissions.   2. Limited Control Over Ad Placement While advertisers can set targeting and exclusion parameters, the automated buying model means there’s still limited control over the final placement in open marketplaces. Ads can end up on irrelevant, low-quality, or even brand-damaging websites if proper safeguards are not in place, diluting campaign effectiveness.   3. Brand Safety Concerns With ads being served in real-time across a vast inventory, there’s always a risk of them appearing next to inappropriate, misleading, or controversial content. This not only affects user perception but can severely damage a brand’s reputation if left unchecked. Fraudsters and low-quality publishers constantly find new ways to bypass basic detection systems. Moreover, not all platforms enforce the same content quality standards, making it harder for marketers to guarantee safe environments for their ads.  4. Programmatic Ad Fraud Threat Programmatic ad fraud refers to malicious activities by fraudsters to manipulate the ad ecosystem for monetary gain. This often involves the use of bots, malware, or spoofed environments to simulate real user behavior, resulting in advertisers paying for non-existent impressions, fake clicks, or fabricated conversions.  For example, fraudsters might use domain spoofing to make a low-quality website appear as a reputable one or deploy botnets that mimic human interaction with ads. These deceptive practices compromise campaign performance, skew data, and go undetected without advanced ad fraud detection solutions.  According to first-party analysis by mFilterIt, conducted across 342 campaigns run in 2024, 31% of invalid traffic in India was coming from programmatic advertising platforms.  The highly automated and fragmented nature of programmatic advertising makes it especially vulnerable to these attacks, underscoring the need for continuous vigilance and robust verification mechanisms.  Why is there a need for fraud detection in Programmatic ad campaigns?  Since programmatic advertising involves a rapid decision-making process, everything cannot be monitored in real-time by humans, which makes these campaigns vulnerable to programmatic ad fraud. Therefore, fraud detection solutions have become an integral part of the ecosystem. These tools verify whether ads are viewable, brand-safe, and served to real users, utilizing pre-bid and post-bid filters, real-time analytics, and machine learning to detect fraudulent activity and ensure quality traffic.  Strategic Tips to Build a Safe and High-Performing Programmatic Ad Fraud Free Campaign Rather than just checking off the setup steps, smart marketers need to focus on strategic execution. Here’s how to ensure your campaign is both effective and fraud-free:  1. Optimize Campaign Reach Through Audience Modeling Use your first-party data (from CRM, website behavior, app engagement) to build micro-targeted audience segments. Supplement with second-party (from trusted partners) and third-party data (from DMPs) when relevant. Implement lookalike modeling and predictive analytics to identify potential high-value segments.  2. Prioritize Inventory Quality via Private Marketplaces (PMPs) Avoid the chaos of open exchanges when possible. Private marketplaces offer access to premium publishers, controlled environments, and better transparency. Programmatic direct is also a comparatively safer option with predetermined pricing and placement.  3. Invest in Contextual Targeting Align your ads with page content that reflects brand values and relevance without relying on user-level data. This enhances performance while staying privacy compliant. 4. Implement Frequency Capping and Creative Rotation Serving the same ad repeatedly frustrates users and depletes ROI. Ensure your campaign respects frequency caps per user and rotates creatives for freshness. Be cautious of fraudulent traffic sources that breach frequency caps to maximize fake impressions, an often-overlooked fraud tactic. 5. Exclude MFA (Made-for-Advertising) Sites MFA sites are low-value domains packed with ads and clickbait content. They exist solely to monetize traffic through ads. These environments offer little to user engagement, dilute brand value, and quietly drain ad budgets. Ensure your inventory sources filter out such domains or apply inclusion lists of verified publishers. 6. Leverage Real-Time Analytics

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fake_lead

Fake Leads Are Surging in BFSI: Here’s How They’re Harming ROI This Quarter

The Banking, Financial Services, and Insurance (BFSI) sector experiences a sharp rise in marketing and lead generation efforts during Q1 and Q2, driven by consumer demand for tax-saving investments, insurance, and loans. However, this seasonal uptick also brings a surge in fake lead generation, banking frauds, KYC frauds, and financial fraud. Between April and January of FY25, India reported a sharp increase in digital financial fraud, with losses reaching ₹4,245 crore across 2.4 million cases, according to data shared by the Ministry of Finance. This marked a 67% rise compared to FY23, when losses totaled ₹2,537 crore from 2 million reported incidents. In FY24, fraud-related losses were slightly higher at ₹4,403 crore, spread across 2.8 million cases highlighting a persistent and growing threat, even with ongoing efforts to strengthen fraud prevention. This growing trend underscores the urgent need for robust lead validation in the BFSI space. Sophisticated Fraud Tactics Currently Plaguing the Industry 1. KYC Frauds Stolen or synthetic identities are used to pass KYC checks, resulting in regulatory risks and wasted acquisition costs. 2. OTP Bypass OTP-based verification is a common layer of security in lead forms. However, advanced scripts and bots automate OTP entry, bypassing this defense and flooding systems with invalid leads. 3. Disposable Numbers Fraudsters increasingly rely on temporarily active numbers to complete lead forms to pass initial security checks but are unreachable for callbacks or follow-ups, leading to dead ends. 4. Bot-Generated Leads Automated bots emulate human behavior by filling out forms, clicking ads, and skewing attribution metrics, wasting paid media budgets. 5. Identity Theft This involves using real individuals’ personal details often obtained through phishing or data breaches to submit fake leads. These often go undetected until serious harm is done. The Real Cost of Fake Leads Fake leads don’t just waste budget – they distort ROI, damage brand credibility, and mislead campaign optimization. Paid campaigns that attract invalid leads inflate customer acquisition costs without delivering real conversions. Sales teams spend time on unreachable or disinterested contacts, impacting productivity and morale. Moreover, fake interactions skew campaign analytics, leading marketers to make flawed optimization decisions based on inaccurate data. In a highly regulated sector like BFSI, engaging with fake or unverified leads poses serious compliance and reputational risks, including audits, penalties, and regulatory fallout. How mFilterIt Protects BFSI Brands from Fake Leads As digital financial fraud continues to escalate, BFSI brands need more than just conventional lead validation filters to effectively combat fake leads. mFilterIt’s ad fraud detection solution offers real-time lead validation, device fingerprinting, and full-funnel visibility to help BFSI brands stay ahead of evolving fraud tactics. Our solution evaluates every lead through heuristic, deterministic, and behavioral models, filtering out invalid or suspicious entries instantly. This ensures that only genuine, conversion-ready leads reach your CRM. What sets Valid8 apart is the proprietary lead scoring engine, which ranks leads by intent – high, moderate, or low – using rich behavioral and attribution data. This allows marketers to focus on high-quality leads and optimize campaigns for better out comes. With Valid8, brands can cut waste, protect ROI, and maintain compliance – all while improving lead quality. Conclusion: It’s Time to Validate, Not Just Generate As fraud becomes more complex, BFSI marketers must shift from merely generating leads to validating them. mFilterIt empowers you to eliminate fake leads, optimize ad spend, and safeguard your marketing efforts. Discover how Valid8 can protect your lead pipeline. Contact us today to schedule a demo.

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counterfiet fraud

Counterfeit Fraud: How It Harms Digital Brands and Undermines Customer Trust

In today’s hyper-connected commerce ecosystem, brand visibility is no longer limited to owned channels. From third-party marketplaces to social commerce platforms, your brand is likely to be represented – accurately or not – in places you don’t control. This growing digital sprawl has opened the floodgates to a persistent and costly threat: counterfeit fraud. A joint report by Crisil and the Authentication Solution Providers Association (ASPA) revealed that an estimated 25–30% of all products sold in India are counterfeit, with the highest incidence observed in the apparel and FMCG sectors at 31% and 28%, respectively. For brand owners, marketing leaders, and e-commerce decision-makers, counterfeit fraud is not just a legal risk but a business risk diluting brand equity, eroding consumer trust, redirecting revenue to illicit networks, and introducing poor quality imitations into your customers’ hands – all of which directly impacts your bottom line. What makes this challenge more complex is that counterfeiters today operate with a high degree of digital sophistication. They mimic your assets, hijack legitimate listings, manipulate reviews, and blend fake inventory with real ones. In this article, we explore the counterfeit ecosystem across digital marketplaces, how it affects businesses and customers, and what brands can do to combat counterfeit fraud. Common Platforms Where Counterfeits Thrive Despite major advancements in platform policies and fraud detection solutions, counterfeiters still manage to operate across many prominent e-commerce platforms: 1. Amazon Amazon has introduced anti-counterfeit protection solutions like Project Zero and Transparency. However, with millions of third-party sellers, counterfeit listings still manage to bypass these basic filters, especially through listing hijacking or misuse of “Fulfilled by Amazon” (FBA) services. 2. eBay eBay is the platform known for consumer-to-consumer sales, is often a hotspot for fake collectibles, refurbished electronics, and designer goods. While eBay does allow users to report counterfeits, the manual nature of enforcement limits its speed and scale. 3. AliExpress, DHgate, Wish These platforms, largely dominated by overseas sellers, are frequently associated with low-cost counterfeit products, particularly in fashion, accessories, and beauty products. 4. Social Commerce Platforms Facebook marketplace, Instagram shops, and TikTok shops have become increasingly vulnerable due to minimal content moderation. Counterfeiters leverage these platforms for product placements, often boosted by influencer endorsements or paid promotions. 5. Emerging Regional Platforms E-commerce sites in regions like Southeast Asia, MENA, and Latin America are seeing a spike in counterfeit listings due to fewer legal frameworks and enforcement mechanisms. How Counterfeiters Operate in Digital Space? Modern counterfeiters are tech-savvy and use a blend of deceptive and manipulative tactics to infiltrate online platforms: 1. Deceptive Listings Sellers use legitimate product titles, images, and brand descriptions to mislead shoppers. Sometimes, they use phrases like “compatible with” or deliberately misspelling brand names to avoid detection. 2. Mixed Inventory On Amazon and other major platforms, third-party sellers mix counterfeit goods with authentic products in shared warehouses, making it difficult for customers to distinguish between the sources. 3. Redirects and Fake Domains Outside the platforms, counterfeiters create fake brand websites with lookalike URLs to trick buyers into purchasing counterfeit products directly. 4. Dark Social Networks Encrypted messaging apps and private social groups are also used to distribute counterfeit items, making them harder to monitor and shut down. The Risks of Buying Counterfeit Products – It’s Not Just Monetary While some price-sensitive consumers may knowingly purchase counterfeit items, many others fall victim unknowingly misled by professional-looking listings, manipulated reviews, and seemingly legitimate seller accounts. Regardless of intent, the hidden costs of counterfeits far outweigh any short-term savings, posing substantial risks to consumer safety, satisfaction, and brand perception. Health and safety hazards are among the most alarming consequences. Counterfeit cosmetics can contain banned substances, fake electronics may catch fire or explode, and imitation pharmaceuticals can lead to serious health complications or even death. Beyond physical risks, counterfeit products are of poor quality, lack durability and post-purchase support. Buyers are left with no warranty, no customer service, and no refund options. The damage to brands is equally severe. Customers who unknowingly receive counterfeit items often associate their poor experience with the authentic brand, leading to erosion of trust and long-term brand equity. Moreover, financial scams, where customers never receive the product or receive blatant knockoffs, result in negative word-of-mouth and public backlash, further harming the brand’s reputation in a crowded and competitive marketplace. How Can Consumers Avoid Buying Fake Products? While platforms and brands continue to invest in brand protection solutions to combat counterfeit fraud actively, consumers must also remain vigilant. Their awareness and purchasing behavior are critical lines of defense against counterfeit fraud. Recognizing the signs of a counterfeit listing and knowing how to navigate e-commerce platforms with caution can reduce the chances of falling victim to fake products. Consumers should prioritize shopping through official brand websites or purchasing from verified sellers that the brand endorses. Seller reputation matters; buying from long-established sellers with consistently high reviews and transaction volumes adds a layer of credibility. In addition, overly steep discounts should raise red flags. If a product is significantly cheaper than the typical market price, there’s a high chance it will be counterfeit. Brands today also offer digital tools to help buyers verify the authenticity of their products. These include QR codes, serial number lookups, and mobile authentication apps. Moreover, shoppers should always take advantage of platform protections such as secure payment methods, buyer guarantees, and staying within official platform communications. Avoiding purchases conducted through private messages or off-platform payment links helps mitigate the risk of scams and ensures recourse in case of fraud. What Brands Must Do to Safeguard Against Counterfeit Fraud Counterfeit fraud is not just a legal issue – it’s a brand reputation and customer trust issue. Here are proactive steps brands can take: 1. Trademark and IP Protection: Secure global intellectual property rights to empower faster legal recourse and takedown actions. 2. Authorized Seller Networks: Establish clear seller guidelines and a public list of authorized distributors and resellers. 3. Product Verification Tools: Introduce anti-counterfeit packaging, QR codes, and digital authentication systems to

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reseller fraud in q commerce

Not All Sales Are Good Sales: Reseller Fraud In Q-Commerce, Here’s How to Protect

India’s e-commerce sector, valued at ₹10,82,875 crore in FY24, is expected to reach ₹29,88,735 crore by FY30, driven by a compound annual growth rate (CAGR) of 15%.With the global expansion of E-commerce and a surge in the growth of Q-Commerce apps, reseller fraud has also rapidly evolved as a high-volume threat to the ecommerce industry. On the surface, everything looks perfect – your quick commerce dashboard might be lighting up with repeat orders, high conversion rates, and the campaign ROI outperforming expectations, but there’s much more to dig upon than you might know. Reseller fraud is a form of abuse that doesn’t wave red flags. It mimics legitimate behavior – users making frequent purchases, ordering popular products in bulk, and seemingly engaging deeply with promotional campaigns. But these aren’t loyal consumers. They’re opportunistic actors – affiliates, local vendors, and small resellers, who exploit platform discounts to stock up on goods, only to resell them at full price in local markets or through offline channels. This not only creates an out-of-stock situation for your brand but also distorts campaign insights, creates a misleading sense of success, and drains marketing budgets meant for genuine customer acquisition. Also, damaging the brand reputation in the eyes of your genuine consumers. You cannot always trust what the dashboard shows. With the evolving fraud techniques, it has become essential to go beyond the standard metrics and dive deep into abnormal behavioral patterns and unveil the full story. In this blog, we will explain one of the lesser known but sophisticated techniques of how resellers keep brands in dark by creating a mirage of a perfect campaign with reseller fraud. What is Reseller Fraud? Reseller fraud occurs when individuals or small businesses exploit discounted products on quick commerce (Q-commerce) platforms, not for personal use but for resale at higher or market prices. These actors make repetitive purchases of the same SKU, in the same quantity, from the same store, paying the same amount – often using the same user account or delivery address. On paper, this may look like consumer loyalty or campaign success. In reality, its unauthorized trade, where your discounts fund someone else’s profit margins. This fraudulent practice has become increasingly common in markets like India, where local kirana stores, small vendors, and even affiliate agents use Q-commerce apps as wholesale backdoors. They buy discounted goods in bulk and resell them at MRP or higher, effectively using your platform’s consumer-facing offers to run their own side businesses. Why Reseller Fraud Is Worse Than It Seems Reseller fraud is particularly dangerous because it doesn’t look like fraud at all, but has far reaching consequences: Margin Erosion Aggressive discounting strategies are meant to drive acquisition and retention, not fuel arbitrage operations. Every fraudulent transaction eats directly into your profits. Distorted Performance Metrics Fraudulent purchases inflate KPIs, making campaigns look more successful than they truly are. This misleads marketers and leads to flawed budget allocation. Inventory Mismanagement Stock intended for real customers is diverted to resellers, leading to out-of-stock situations and unmet demand from genuine buyers. Wasted Ad Spend As platforms report strong performance, brands continue investing in campaigns that are unknowingly amplifying fraudulent behaviors. Strategic Misalignment Decisions based on polluted data like which audiences to prioritize, which SKUs to push, or which publishers to scale can derail broader business goals. Gray Market Selling Perhaps most critically, reseller fraud fuels the gray market, where products are sold through unauthorized, uncontrolled channels. This erodes price integrity, disrupts official distribution networks, and often results in poor customer experiences due to lack of warranties, expired goods, or improper handling. Over time, this undermines brand trust and weakens your position in the market. How mFilterIt help digital brands combat reseller fraud? To combat reseller fraud effectively, brands must move beyond conventional fraud detection tools that only target bots, click farms, or fake installs. The real threat also comes from human-driven, behaviorally complex fraud, and that requires an advanced solution. Valid8 is a multi-layered fraud detection solution built specifically for modern digital commerce environments. It helps brands go deeper, detecting not just invalid traffic but malicious behavioral patterns that compromise campaign and business integrity. How Valid8 by mFilterIt is different than other fraud detection tools? Pattern Recognition: Flags suspicious activities like repeat purchases of the same SKU by the same user/store, high-volume ordering during promotional bursts, or delivery address overlaps. Behavioral Analytics: Goes beyond IP and device-level tracking to understand buying behavior at a user and campaign level. Actionable Insights: Offers strategic visibility into which campaigns, publishers, or discount strategies are vulnerable to abuse, enabling smarter investment decisions. Business Gains: Reduces wastage, improves ROI, and enables true customer acquisition by filtering out non-genuine transactions. In essence, Valid8 helps brands go beyond basic ad fraud detection, offering deeper insights, separating real consumers from opportunistic actors, protecting both their bottom line and their brand experience. Final Thoughts: Clean Growth Over Illusionary Success Reseller fraud is a silent margin killer. While it may inflate short-term numbers, the long-term cost to your brand is undeniable. It distorts your data, misguides your strategy, and siphons off your discount budgets into someone else’s business. However, with advanced fraud detection tools like Valid8, quick commerce brands can turn this vulnerability into strength restoring data integrity, protecting discounts, enabling impactful and insight driven decisions. Because in today’s quick commerce apps landscape, not all sales are good sales. The time to clean up your funnel is now. Contact us to detect reseller fraud in Q-Commerce.  

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