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mFilterIt's Attention Metrics Tools

How mFilterIt’s Attention Metrics Tools Differs from Competitors?

Blog, Ad Fraud Blog - Valid8 /

Most branding campaigns today are measured by impressions, clicks, and viewability scores. These numbers can confirm that ads were displayed on a screen—but they reveal very little about whether the audience actually paid attention. An ad might be technically viewable, yet ignored, skipped, or scrolled past in a split second.  That’s why marketers are increasingly turning to attention measurement. Unlike traditional metrics that focus on exposure, attention metrics uncover whether ads truly capture consumer focus and influence behavior. In today’s crowded media landscape, it’s not enough to win screen space—you need to win meaningful human attention.  The real challenge, however, is choosing the right solution. While some tools provide only surface-level visibility checks, others go deeper to show how attention translates into engagement and impact. In this blog, we’ll compare these approaches—highlighting how mFilterIt measures attention across the full funnel to help brands optimize campaigns, reduce wastage, and drive ROI.  Why Attention Metrics Matter? Traditional metrics like impression and viewability only measure if the ad was viewed or not based on the standard IAB viewability criteria. According to this, a display ad is considered to be ‘viewable’ if at least 50% of its pixels are visible on the screen for one second, and a video ad is considered to be ‘viewable’ if viewed for two seconds.  However, these criteria might light up the dashboards with green signal metrics but do not answer the real questions.  Was the ad genuinely noticed? Did it capture attention long enough to influence action? Did it contribute to measurable outcomes? This is exactly what attention measurement does.  It captures the right set of insights required to know whether a particular campaign performed well or not. What further steps need to be taken at the optimization level.  But do all attention metrics tools offer the right set of insights you need? Here’s how you can find that out.  Here are four key dimensions that brands need to consider while evaluating attention measurement solutions:  Depth of measurement – Moves beyond basic visibility to capture interaction, dwell time, and attention stickiness.  Funnel coverage – Assesses attention across the journey, from awareness to engagement to conversion.  Optimization readiness – Ensures real-time, actionable insights that can directly help in optimization of media and creative strategies.  Adaptability across channels – Verify that the solution delivers accurate insights across regions, platforms, and emerging environments like OTT/CTV.  How mFilterIt Differentiates from its Competitors? Stage-by-stage Breakdown When evaluating attention metrics tools, it is important to recognize how they measure performance across the campaign funnel – top, middle, and lower stages. To understand the real impact of attention analytics advertising, brands need to move beyond surface-level simple viewability indicators and assess how focus translates into outcomes at every step of the customer journey.  Here’s how we at mFilterIt takes a differentiated approach compared to competitors.  Awareness & Reach Stage – Top Funnel Competitor approach: Focuses on surface-level visibility signals like impressions, audibility, player size, and exposure time. While these confirm the ad was served, they fail to reveal whether the user actually noticed or engaged with it.  mFilterIt approach: Our ad fraud solution, Valid8, goes beyond visibility to assess real view-worthiness, tracking mute percentage, skip percentage, scroll behavior, fullscreen or PiP usage, and contextual relevance. This ensures brands measure whether ads are actually seen and absorbed by users rather than just being displayed.  Consideration & Engagement Stage – Mid Funnel Competitor approach: Relies on proxy metrics like cursor hover or generic data, which provide limited insights into the depth of engagement.  mFilterIt approach: Measures authentic engagement behavior signals, including scroll depth, unmute/mute events, fullscreen adoption, repeated interactions, etc. It also segments engagement by audience type and placement (creative performance, audience segments, and placement quality), enabling marketers to make informed adjustments and design more effective mid-funnel strategies.  Conversion & Action Stage – Lower Funnel Competitor approach: Often stops at the conversion level or requires 3rd party uplift or attribution tools, leaving advertisers with fragmented data that does not connect directly to outcomes.  mFilterIt approach: Maps attention signals to business results, linking behaviors like bounce rate, time on site, OTT/CTV drop-offs, and conversion likelihood. This allows brands to spot underperforming placements, optimize spend, and tie attention directly to return on investment.  Regional Accuracy and OTT/CTV Attention Measurement – A Major Differentiator Most competitors rely on standardized viewability or attention models that overlook the local nuances of user behavior, cultural context, fraud patterns, and brand safety requirements. This often leads to misrepresentation of campaign effectiveness in diverse markets.  On the other hand, mFilterIt’s Attention Measurement Tool embeds regional data intelligence and advanced fraud detection into its measurement framework. It ensures that brands receive contextually accurate and market-relevant reporting.  In addition, mFilterIt brings a distinctive advantage in OTT/CTV ecosystems, where risks of ad overexposure, inflated impressions, and fraudulent traffic are notably high. By combining attention-first measurement with invalid traffic (IVT) checks and brand safety validation, mFilterIt ensures ads reach the right audience segments while controlling costs and maximizing genuine engagement.  This approach enables brands to move beyond surface-level metrics and gain a true view of audience behavior across regions and media platforms.  Therefore, if you operate across diverse regions, multiple platforms, and emerging channels like OTT/CTV, you may need an attention metrics tool that provides deeper, more contextual insights rather than relying solely on contemporary benchmarks.  Final Thoughts The advertising industry has evolved far beyond counting impressions, and if you are still stuck only on those metrics, you are probably lagging behind. To keep up with the competition, brands need to know whether their campaigns are truly resonating with real people and driving meaningful outcomes.  Therefore, it is important to use advanced solutions that connect attention with authentic engagement beyond viewability and drive true business impact.  So, if you’re ready to move beyond surface-level validation and unlock the real value of your advertising, it’s time to explore mFilterIt’s attention metrics intelligence.  Book a demo today and see how attention metrics can transform your advertising strategy. 

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How MFA Sites Hurt Ad Performance

How MFA Sites Hurt Ad Performance and Why Attention Metrics Matter for Marketers

Blog, Viewability /

Do you usually find yourself wondering what is the real impact of the branding campaigns that I have run? Where did the audience go? Why isn’t the performance on dashboards not translating into outcomes? Here’s the truth that might hurt a little – An ad ‘seen’ does not mean it is seen by the people who matter. Your programmatic campaigns, specifically planned to maximize reach, visibility, and engagement, might be only getting seen by bots or irrelevant audiences due to it’s automated nature and vulnerability. The ads could be running on MFA (Made-for-Ad) sites, pages designed to game the system, packed with cluttered ads and irrelevant content. These environments drain budgets, distort performance metrics, and leave marketers chasing numbers that mean nothing. According to a report by ANA, brands waste 15% of their ad spend on MFA sites instead of premium inventory, and most marketers don’t even realize it’s happening. So here’s something you need to focus on if you want to move the needle. Because viewability doesn’t equal visibility, and visibility doesn’t equal attention. Therefore, marketers still focusing on just the viewability metrics to measure an ad’s performance, need to move beyond vanity metrics and start looking at what really matters – attention measurement or also called attention metrics. For modern marketers measuring attention is a more reliable and smarter way of understanding whether ads are truly working or not. Let’s understand how it really helps. In this article, we will unpack: What are MFA sites and why marketers need to care? Why is viewability no longer a reliable metric to measure ad performance? Why is it important to measure attention metrics? How to eliminate MFA sites? How does an ad fraud solution like Valid8 by mFilterIt help brands to optimize for real impact? What are MFA (Made-for-Ad) Websites? How These Sites Impact Campaign Performance? MFA (Made-for-Ad) websites, also called arbitrage sites, are not made for efficiency, visibility, impact, or to reach real audience. They are solely designed to steal the ad revenue being spent by marketers. These sites, on the surface, may look like legitimate publishing platforms with articles, images, or even video content; however, are filled with thin or recycled content, clickbait headlines (often fake news), and layouts overloaded with ads, including tactics that encourage accidental clicks. The working model of MFA sites is to exploit programmatic campaigns by doubling impressions and ad spend, while delivering no real user engagement. Here’s a quick breakdown of how MFA sites work and manipulate the whole programmatic ad ecosystem: Auto-refresh: Ads reload every few seconds, inflating impression counts (CPM metrics) without giving users time to process the message. Fake content loops: Articles mimic real stories but lead nowhere, trapping users in an endless cycle of clicks without giving meaningful information. Aggressive layouts: Ads are stacked near navigation buttons or scroll traps, tricking users into accidental clicks and artificially boosting CTRs. Traffic laundering: The automated nature of programmatic campaigns often bundles MFA domains as safe inventory, making them appear legitimate in DSPs and SSPs. All this contributes to budget wastage, as most DSPs and SSPs don’t classify MFA traffic as fraud. The impact on campaigns is significant, with high bounce rates, negligible dwell times, and minimal brand recall. For branding managers running branding campaigns, it dilutes your message, associating your brand with poor-quality environments. Why is viewability no longer a reliable metric to measure ad performance? Viewability has been the industry standard to measure ad performance for years. According to IAB (Interactive Advertising Bureau) guidelines, a display ad is considered “viewable” if at least 50% of its pixels are visible on the screen for one continuous second, and two seconds in case of a video ad. A standard that is now too easy for fraudsters to manipulate, and MFA sites do exactly that. Some common tactics used in MFA sites to inflate CPM campaign models include: 1. Ad stacking Multiple ads are layered on top of each other in a single placement. Only the top ad is visible to the human eye, but every ad in the stack registers as “viewable.” Advertisers end up paying for impressions that never had a chance of being seen. 2. Pixel stuffing Ads are shrunk into tiny 1×1 pixel placements that are invisible to users but still count as “in view.” To reporting systems, the campaign looks like it’s meeting viewability standards, but in reality, no human could ever engage with these ads. 3. Auto-refresh placements Ads are fixed to corners of the screen or reload every few seconds to inflate impressions. They remain technically viewable but rarely capture user attention. These tactics make dashboards look green, but in reality, high viewability doesn’t equal high value. Viewability metrics give marketing teams a false impression that their ads are performing, but do not reveal if users genuinely noticed, processed, or engaged with the ad. This is why relying on viewability alone is no longer enough. It has become a vanity metric, only useful for technical checks, but meaningless when it comes to proving real business outcomes. Today, the focus has shifted to attention metrics, which provide a truer measure of whether an ad actually made an impact or not. Here’s How Attention Measurement Makes a Difference Attention metrics are about measuring the reality of how each programmatic or branding campaign performs. These metrics don’t just confirm if an ad appeared on screen; they measure whether it actually captured user interest. This includes tracking metrics such as: In-view duration: How long the ad stayed visible. Engagement signals: Scroll depth, clicks, dwell time, video played with sound, whether skipped or not, etc. Completion with focus: Whether a video was watched without being muted or minimized, and quartile progression. Contextual relevancy: Whether the surrounding content was contextually relevant to the ad and encouraged the user to stay. Here’s what we consistently observe at mFilterIt when auditing campaigns polluted with MFA inventory: Therefore, unlike viewability, attention metrics reflect real human behavior. It reveals if users scroll past your ad

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Leverage affiliate monitoring to prevent fraud & boost ROI

Affiliate Marketing Campaigns: Know How Smart Affiliate Monitoring Drives Growth

USA, Affiliate, Blog /

The global affiliate market continues to expand at an annual growth rate of nearly 8%, with brands investing heavily in affiliate programs to drive performance and reach new audiences.  But here’s the catch — rising spend doesn’t always equal rising returns.  As affiliate programs scale, the need for transparency and accountability across every click, install, and conversion has become critical. Consider this scenario: one affiliate is driving a surge in installs, but downstream conversions remain flat. Without evidence of what’s happening behind the scenes, how do you explain this performance gap — let alone fix it?  This is where the disconnect lies. Dashboards may glow with inflated numbers, yet real business impact lags. Budgets leak, brand reputation is put at risk, and marketers are left with more questions than answers.  To truly maximize the value of affiliate partnerships, brands need visibility into traffic quality, confidence in partner compliance, and the ability to direct spend toward affiliates that actually drive growth.  In this blog, we’ll unpack:  The most common affiliate fraud and violation techniques. Why traditional tracking often falls short.  How brands can safeguard ROI with deeper monitoring and smarter optimization.  The Blind Spots You Can’t Ignore: Common Affiliate Fraud and Violation Techniques Without active monitoring come hidden risks. As affiliate programs scale to include multiple partners, from influencers, coupon sites, and ad publishers, brands often lose visibility into where and how their campaigns are being run. And without visibility, small issues can quickly snowball into wasted budgets, poor-quality leads, and even damaged brand reputation.  Here are some common affiliate fraud techniques every marketer should know about, along with some real-world affiliate use cases detected by mFilterIt.  1. Brand Bidding A major blind spot is when affiliates bid on your branded keywords. In such cases, you end up paying for customers who would have anyway reached you organically.  Example: A user searches for a brand name on Google and clicks on a sponsored ad from an affiliate pretending to be the brand’s official site. This results in a commission payout for a user who would have converted anyway.      Watch for: Inflated CPCs on brand-specific keywords and affiliate-attributed conversions that come mainly from branded queries.  Impact: You end up paying twice, once for the ad and again for affiliate commissions, with no added value.  2. Ads Placed on Harmful Sites Sometimes affiliates place ads in environments that are completely misaligned with your brand values, such as adult sites, piracy platforms, MFA sites, or counterfeit marketplaces (in case of ecommerce brands).  Example: A family-oriented or financial service app being promoted via banner ads on explicit content sites, often completely unknown to the advertiser.      Watch for: Customer complaints or unexpected mentions of your brand in unsafe spaces.  Impact: Even one misplaced ad can damage years of earned trust, as audience perception is built basis the kind of content they see you besides.  3. Fraudulent Traffic Fake clicks, bots, or incentivized traffic spikes from unfamiliar geographies or domains inflate numbers while delivering zero business impact and making further optimizations even more difficult.  Example: An affiliate running click farms that generate thousands of automated clicks on ad campaigns, resulting in high engagement but no actual sales or customer value.  Watch for: Sudden spikes in traffic or leads from unusual locations or sources that don’t align with real customer behavior.  Impact: Fraud distorts performance data, wastes ad spend, and even manipulates further optimizations.  4. Trademark Violations Affiliates may misuse brand assets like trademarks, logo, images, tagline, etc, run ads in restricted regions, or push creatives that were never approved by the brand.  Example: An affiliate creates a fake offer banner using the brand’s official logo and runs display ads or push notifications directing users to another landing page.      Watch for: Sudden conversions from unrecognized sources.  Impact: It creates confusion and distrust among customers and weakens your brand message or identity.  5. Counterfeit & Fake Offers Some affiliates drive sales through tactics that attract one-time buyers using deceptive offers or counterfeit promotions with no repeat value.  Example: A cashback banner offering ₹200 cashback for downloading an app that actually provides no such benefit, causing consumer frustration and support complaints.        Watch for: Affiliates with high conversion rates but low repeat purchase or retention.  Impact: Your reports may look positive, but customer lifetime value (CLV) stays weak.  Why Traditional or Manual Checks Aren’t Enough? Affiliate payouts are based on performance. Marketers often rely on contracts, affiliate network agreements, and occasional audits to keep their programs in line. But in today’s real-time, ever-evolving digital ecosystem, and increasing use of AI, these safeguards fall short.  1. Contracts & T&Cs are reactive: They define what affiliates shouldn’t do but rarely prevent violations before damage occurs.  2. Manual audits are too slow: By the time discrepancies are spotted, affiliates may have already pocketed commissions and moved on.  3. Affiliates adapt quickly: What worked yesterday may already be replaced by new tactics designed to bypass outdated checks.  It is impossible to manually keep track of fraudulent tactics that affiliates use to earn commissions. That is why most brands are shifting towards a smarter data-driven affiliate monitoring strategy to safeguard their marketing budget and brand reputation before it hits the bottom line.  The Smarter Approach: Advantages of Using an Affiliate Monitoring Solution While self-audits help you identify surface-level red flags, they often fall short when it comes to detecting sophisticated affiliate fraud and ensuring long-term compliance. By combining automation, data intelligence, and compliance checks, it offers brands a smarter way to manage affiliates and protect investments. Key benefits to the brand are:  Enhanced Transparency – Clear visibility into affiliate activities and contributions.  Improved ROI – Optimize affiliate spending by focusing on genuine, high-performing partners.  Brand Protection – Safeguard brand reputation through compliance monitoring.  Market Competitiveness – Stay ahead of competitors by leveraging advanced fraud detection and compliance tools.  Regulatory Compliance – Ensure adherence to global and local regulations to avoid legal penalties.  How mFilterIt Helps: Affiliate

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Learn how shifting to dedicated landing pages with real-time lead validation helps reduce junk leads, improve transparency, and boost your Meta campaign ROI.

Meta Lead Gen or Landing Page Forms: Which Brings You Better Leads?

Blog, Ad Fraud Blog - Valid8 /

You have done everything by the book.  Made a fully optimized, well-researched campaign, targeted a precise audience, and got engaging creatives made by your team. Even your dashboards show that the campaigns are performing great.  But what you hear from your sales team is a whole different story.  “Fake leads, wrong phone numbers, uninterested people, never heard of the brand before” Leaving your performance credibility being questioned.  It’s not that your strategy is flawed. You’ve done exactly what a high-performing Meta lead gen campaign demands, what every marketer does.  The problem lies in where those leads are being captured from.  Meta’s native lead forms are built for speed and simplicity, which makes them great for collecting high volumes of leads. However, since Meta is a walled garden, a closed ecosystem,   This gap in visibility is what allows fake sign-ups, bots, and low-intent leads to slip through. And by the time sales flag the problem, it’s too late, the budgets are spent, the data is messy, and the targets are affected.  The way forward isn’t to stop running Meta campaigns; it’s to change the lead-capturing strategy. By shifting traffic to dedicated landing pages, you bring leads into an environment you control, where real-time validation and ad fraud solutions can help you ensure that only genuine, sales-ready leads make it through. This means cleaner CRMs, stronger conversion rates, and a lot fewer tense conversations in post-campaign reviews.  Continue reading further to know how it works.  Understanding The Problem: Why Meta Lead Gen Campaigns Produce Junk Leads? Meta’s native lead forms are optimized for speed, efficiency, and ease for a seamless user experience. Users can easily fill in the form with a couple of taps, often using pre-filled information extracted from their profiles. While this effortless experience boosts form submissions, it also makes the campaigns vulnerable to lead generation fraud.  This ease in the process makes it even more easier for the bots, or click farms (low-paid workers), to fill in the forms.   Moreover, the bots easily bypass the basic level checks like CAPTCHAs and OTPs using CAPTCHA solvers available at just one click. That is why, marketers relying solely on these efforts to prevent junk leads lack behind.  Here’s how junk leads fill in, when left unchecked:  Invalid or fake phone numbers and emails – Many users submit temporary, outdated, or fabricated contact details. Some don’t even review the pre-filled information before hitting submit, leaving you with leads that cannot be contacted or verified.  Bots and click farms – Automated scripts and low-paid workers mass-fill thousands of forms within a matter of few minutes. While they make your numbers look impressive on the dashboards, they have zero intent to buy and generate zero actual revenue. Zero-intent leads – These are people who sign up purely out of curiosity to know what’s next, boredom, or by mistake. Since there’s little to no effort involved, they have no genuine interest and rarely convert into paying customers.  Repeated or duplicate submissions – The same user, or an automated system, submits identical details multiple times. This inflates your lead count, clogs your CRM with fake leads, and wastes valuable time of sales team resources on the same invalid contacts.  The combination of these factors completely disrupts the campaign goals, skewing performance metrics, and manipulating further campaign optimizations or remarketing efforts.   So, if you have ever wondered why your Meta lead generation campaigns have great CPL but disappointing conversions, above mentioned are likely the reason, the system is rewarding volume, not quality.  The Impact of Junk Leads on Business Growth The impact of junk leads is far-reaching. These fake leads don’t just waste money; they sabotage your entire marketing system. Here how:  Direct financial loss: You’re paying for every click, impression, and form submission. If 40–50% of those are fake or irrelevant, that’s a significant chunk of your ad spend going to waste.  Wastage of operational efforts: Your sales team spends valuable hours chasing invalid numbers, disconnected lines, and people who have no interest in your offer. This not only wastes time but also lowers morale.  Misleading campaign data: Junk leads distort your web performance metrics, making your campaigns look better than they actually are. Your reported conversion rates may seem healthy, but the actual sales numbers tell a different story.  Poor remarketing audiences: When your CRM is full of low-quality leads, your lookalike and retargeting campaigns also suffer. You’re essentially teaching Meta algorithm to target more of the wrong people.  Damaged brand reputation: Repeatedly contacting people who never wanted to hear from you in the first place can hurt your brand image and even lead to spam complaints.  Therefore, to combat junk lead generation fraud, advertisers are now transitioning from native Meta lead forms to dedicated landing pages with custom leads forms.  Why Marketers Should Move from Native Ad Forms to Landing Pages? The shift from native Meta lead forms to redirecting the traffic to dedicated landing pages gives marketers more control, cleaner data, and better lead quality. Here’s how: 1. Complete control over messaging and funnel flow A landing page lets you customize headlines, copy, images, and CTAs to match your campaign objectives. You can guide visitors through a carefully structured journey that builds interest before asking them to fill out a lead form. This helps pre-qualify the lead before it even hits the form.   2. Higher accuracy in data Unlike native forms that pull pre-filled details from a user’s Meta profile (often outdated), landing pages require users to manually enter their information. This reduces the risk of invalid or old phone numbers, emails, and incorrect names entering into your CRM.   3. Behavioral analysis  On a landing page, advertisers can measure valuable engagement signals like scroll depth, time spent on the page, clicks on key elements, etc. These metrics help you understand how invested a visitor was and also help identify patterns for high-quality leads.   4. Consistent brand experience  Campaigns having default Meta lead forms are bound to have the same preset design and

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rise-in-brand-infringement-scams

Rise in Brand Infringement: How Brands Can Stay Protected This Festive Season

Blog, Brand Protection /

It’s the busiest time of the year… Especially for ecommerce brands, when shoppers are eagerly browsing, ready to shop, spend, and convert. And at this moment, the buzz has already begun, users have already started wishlisting what new products they need to bring home this festive season. Brands are all geared up to make the most from festive sales like Flipkart’s Big Billion Days, Amazon’s Great Indian Festival, Meesho’s Mega Blockbuster Sale, etc. But are you aware, it’s the most wonderful time of the year for whom? Fraudsters and scammers. E-commerce brands are highly targeted by fraudsters during the festive season. mFilterIt spotted more than 1600 suspicious domains and fake websites appearing on ad networks mimicking known e-commerce platforms, dedicated to phishing and selling counterfeits. This is just one part of the bigger problem. Festive season fraud in India has evolved far beyond the occasional fake product listing. Today, cybercriminals run full-fledged operations, registering lookalike domains, cloning brand websites, impersonating customer service representatives, and creating social media ads that look almost indistinguishable from those of the real brands. Around 45% of Indian consumers report that they or someone they know has been targeted by a deepfake-based shopping scam, and over half of these victims, about 56%, ended up losing money to the fraud. Source: Times of India. So, how do brands ensure protection against brand infringement scams to safeguard their integrity in the market and among consumers? In this article, we’ll break down types of brand infringements targeting Indian consumers during the festive season and explore how both shoppers and businesses can protect themselves. We’ll also look at how brand protection solutions help e-commerce platforms keep the festive spirit safe. Why Festive Season Is Prime Time for Scammers? A report by the Anti-Phishing Working Group (APWG) found that phishing and brand impersonation attacks spike by up to 70% during peak shopping seasons. This means that when customers are highly energetic, lured, and distracted by discounts, fraudsters are busy making their fraudulent operations look more legitimate than ever. Here’s why the number of scams surges during this time of the year:  Shoppers are in a hurry – Limited-time deals, flash sales, and midnight offers push customers to act fast. This urgency often means they skip basic checks like verifying seller authenticity or double-checking website URLs.  Massive ad spend boosts brand visibility – Brands invest heavily in festive marketing across channels. Fraudsters hijack this visibility by copying creatives, mimicking landing pages, and targeting the same ad keywords to divert traffic.  Fear of missing out drives impulsive clicks – Festive campaigns create a “buy now before it’s gone” mindset. Fraudsters exploit this by using phishing sites, listings, and even emails that look identical to official ones, banking on consumers’ lack of attention.  Customers’ trust in brands – Customers expect big discounts during festivals like Diwali, Independence Day, etc., from the brands they know they can trust. This high trust level lowers their skepticism toward unusually cheap offers, making it easier for scammers to mislead them.  Volume of activity makes monitoring harder – With brands handling high order volumes, launching new SKUs, and running multiple campaigns, it becomes harder to track every marketplace listing, social ad, or new domain in real time, giving scammers a window to operate.  Therefore, the lack of vigilance from both brands’ and consumers’ results in an increase of brand infringement cases and lost brand integrity, sales, as well as customer trust.  Common Types of Brand Infringement Attacks You Need to Know About Several brand infringement patterns repeatedly surface during festive sales. Below are some things you need to be aware of:  1. Fake Websites, Typo Squatting, and Lookalike Domains Fraudsters register domains that closely mimic brand URLs (swap letters like replacing ‘O’ with a ‘zero’, add prefixes/suffixes, use similar TLDs) and build landing pages that copy official branding, logo, and product images. These pages are then promoted by running fake ads across platforms, SMS links, or mass phishing campaigns promising 50-70% discounts. So, customers land on convincing checkout pages and complete payments that never reach the real brand.  2. Counterfeit and Unauthorized Marketplace Listings Unauthorized sellers list fake or low-quality replicas of legit products under a genuine brand name. These listings often come with heavily discounted prices to lure buyers who end up buying substandard goods, leading to a poor experience and loss of money.  According to a joint study conducted by Crisil and the Authentication Solution Providers Association (ASPA), counterfeit goods account for roughly 25–30% of total products sold in India. The problem is particularly severe in the apparel and FMCG industries, where counterfeit selling reaches about 31% and 28%, respectively. Source: Business Standard 3. Social Media Impersonation and Fake Promotional Accounts Fake Instagram pages, cloned Facebook profiles, or fake WhatsApp customer service numbers are commonly used to run festive promotions. Scammers create accounts that visually mimic the brand, run paid ads, or DM followers with limited-time coupon codes that lead to phishing websites or fake storefronts. This not only steals immediate sales from the brand but also floods their original account with angry customers requiring PR and customer-care bandwidth to resolve issues and re-establish trust.  According to research conducted in 2024, 31% of consumers admitted that they are likely to purchase from sellers discovered on social media if the offer seems appealing, leaving them particularly vulnerable to brand impersonation fraud. Moreover, nearly 47% of Indian consumers have encountered scams involving forged celebrity endorsements or questionable online retailers on social media platforms. Source: McAfee  How Brand Infringement Scams Hurt Consumers and Brands: The Ripple Effect The first and most direct victims of brand impersonation attacks are consumers. The festive season makes shoppers even more vulnerable. Major impacts include:  Financial losses – Customers end up paying for products that are never delivered, or receive counterfeit goods of little or no value. Refunds are rarely possible because scammers disappear once the transaction is complete.  Compromised personal data – Fake websites and phishing campaigns collect sensitive information such as credit card numbers, addresses, and login credentials. This

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win the digital shelf with ecommerce analytics

Win the Digital Shelf This Festive Season with Data-Driven Ecommerce Analytics

Blog, Digital Shelf Analytics /

Festive season is around the corner, and the most challenging times for ecommerce brands as well. The battle to win on the digital shelf and ultimately the conversion is real.  It’s that time of the year when traffic is peaking on ecommerce platforms because of festive sales like Big Billion Days, Great Indian Festival, etc. The consumer intent is high and willing to spend during this time  According to a RedSeer report, festive season sales accounted for $9.2 billion in revenue in 2021 alone. Moreover, according to a report by KPMG India, the festive season generates up to 30-40% of annual retail sales. But with this surge in opportunity comes a sharp rise in complexity – more competition, fluctuating prices, last-minute stockouts, unpredictable consumer behavior, and an overwhelming amount of data scattered across platforms.   However, amid the chaos of flash sales, ad campaigns, and instant demands, brands can’t afford to rely on guesswork or delayed reporting.  And here’s the harsh truth: every missed keyword, every out-of-stock product, every ranking position lost gives an edge to your competitor who is doing all the above.   That’s why leveraging a real-time ecommerce analytics solution isn’t just helpful; it’s essential. To win sales, and more customers during this festive season, brands must operate with complete clarity on what’s working, what’s not, and what needs immediate action. Because in a market where every second counts, only those who can see and act faster will own the digital shelf.   In this article, we will talk about the challenges ecommerce brands face during mega sale campaigns/festive season sales and what ecommerce brands should focus on during peak times.  Challenges Ecommerce Brands Face During Festive Season Sales It’s easy to be caught up in dashboards, creatives, and campaign calendars. But if you zoom in, there are deeper challenges that affect outcomes throughout the process, and many ecommerce teams miss them until it’s too late.   1. Limited Visibility into SKU Performance Even the best-selling products can lose sales if they’re not consistently available or properly listed across platforms. During the high traffic periods – availability is opportunity. If your shoppers are exploring and don’t find your product on the digital shelf, they will move to the next best option. And for you, it’s just a lost opportunity. While being present is important, it is also essential to do a continuous scan to avoid out-of-stock situations and not appearing for the competitive keywords.    These blind spots are often only caught when it’s too late. Without real-time visibility into SKU-level performance insights, brands risk losing high-intent buyers in the most critical hours.   2. Inconsistent Product Details on Various Platforms You’ve invested in driving traffic, but if your product page has low-resolution images, outdated specs, or a missing description, it directly impacts consumer behavior, their decision making and kills conversion.   The complexity of this challenge is that ecommerce platforms often display different versions of your product content, especially when multiple sellers are involved. This inconsistency across PDPs not only looks unprofessional but can also lead to poor SEO rankings and reduced shelf visibility, costing you valuable clicks.  3. Price Undercutting and Discount Violations Everyone wants to be the cheapest during a sale, and sometimes resellers/competitors take that a little too far. Unauthorized discounting or MAP violations often go unchecked during peak periods.   While this might spike short-term sales for violators, it damages your brand’s perceived value, confuses customers, and disrupts your pricing strategy and even campaigns running for particular products.   4. Delayed Response to Competitor Actions During the festive season you might also see a lot of new competitors emerging with aggressive pricing plays, and flash campaigns. And if your team isn’t tracking these shifts of pricing in real time, your brand risks falling behind.   Knowing who’s gaining visibility, what keywords they’re winning on, and how they’re bundling or discounting helps you respond quickly and protect your share of shelf and avoid loss of revenue.   5. Disconnected Media and Shelf Performance  Running ad campaigns and making sure they are working in your favor are two different things. Many ecommerce teams measure clicks and impressions but fail to link them to what matters: improved product rank, better keyword positioning, and higher conversions.  If your ad budget isn’t moving the needle on your shelf presence, it’s time to question where and how you’re spending. Media and shelf performance must be aligned for your campaigns to deliver real ROI.   6. Struggling to Stay Discoverable in Crowded Search Results Discoverability is the first touchpoint to even be considered. However, with hundreds of brands competing for the same keywords, simply being listed on a platform doesn’t guarantee visibility. Festive sales demand aggressive yet mindful keyword bidding, and organic placements become harder to maintain.   If your product isn’t ranking on the first few scrolls, you’re invisible to most shoppers. And the worst part is you might be bidding on the wrong keywords or missing out on search trends altogether.    7. Poor Product Availability During Peak Times It’s frustrating when your campaigns are performing well, but the product isn’t available in key regions or goes out of stock right in the middle of a peak day. Stock availability across SKUs, platforms, and cities can make or break festive performance.   Consumers don’t wait; they simply move to the next best option. Without proactive availability tracking and alerts, brands risk losing sales not because of strategy, but because of a lack of visibility into inventory gaps.  Here’s How Leveraging Ecommerce Analytics Solution Helps You Take Back Control To thrive during high demand periods like festive season sales ecommerce brands need more than dashboards, they need real-time, platform-specific, SKU-level intelligence that turns complexity into clarity, and data into actionable insights.  This is exactly where our ecommerce intelligence solution – mScanIt helps. It is an AI powered analytics tool that empowers ecommerce, media, and content teams with real-time, granular, and actionable insights, so you can make smarter decisions, faster.  Here’s how mScanIt helps you overcome the festive season chaos and

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guide to click fraud tools for marketers

What Marketers Should Look for in a Click Fraud Prevention Tool?

Blog, Ad Fraud Blog - Valid8 /

The high season for advertisers is round the corner. Check your ad campaign report. Do you see a high volume of clicks not converting into your users? You’ve tried every way of optimization, but the results are still not satisfactory. You know you need an answer, but the traditional methods of ad fraud detection might not be able to give you that. Click fraud is no longer limited to just bot traffic. It has become more sophisticated over time. These techniques by fraudsters cannot just click on your ads to inflate traffic but also steal your organic traffic or worse – skew your hard KPIs like leads, sign-up, or even purchases.   Therefore, the traditional methods of identifying fraudulent clicks will not be enough. You will need a tool that has advanced specifications which can help you stay ahead of these evolving threats.   We have simplified this search for you. This detailed blog will help you identify key things to remember when selecting a click fraud prevention tool.   Read ahead to get your unanswered questions like:   What comes next is the critical decision – Which click fraud prevention tool actually solves the problem?  This is exactly what we have done for you.   In this blog, we break down:  What features should an advertiser prioritize in a click fraud protection tool? How is mFilterIt different from standard ad fraud detection solutions?  Why isn’t click-level protection enough for my web and app campaigns?  If you’re comparing solutions or preparing to invest, this is the clarity you need to make the right decision.  Key Features to Look for in a Click Fraud Protection Solution The right click fraud protection tool is supposed to give you actionable insights, measurable improvements, and cross-channel protection. Here’s what to expect from a tool that actually solves your business problems:  1. Proactive Click Validation Click fraud operates in milliseconds, and your tool should also have the capability to detect fraud proactively. Click validation ensures invalid traffic is flagged and filtered before it drains your ad budget. Without this, you’re constantly reacting to losses instead of preventing them.   2. Multi-Channel Compatibility Fraud is not confined to one platform. It spreads across Google Ads, Meta, DV360, affiliate programs, mobile app networks, and even OEM and influencer traffic. Your protection tool should have omnichannel compatibility to work seamlessly across all environments to give you consolidated protection.   3. Behavioral & Session-Based Analysis Basic filters can’t catch sophisticated fraud. You need a deeper context. Modern click fraud prevention software must analyze session depth, scroll behavior, dwell time, bounce rate, and other engagement signals to understand true user intent. This helps distinguish a curious customer from a bot.   4. Device Fingerprinting & IP Reputation Fraudsters often disguise their identity using spoofed devices, anonymized browsers, and rotated IPs. Your tool should apply advanced fingerprinting to track devices across campaigns, combined with real-time IP reputation scoring to catch proxies, VPNs, fraud networks, and repeated offenders.   5. AI-Powered Detection Engine Look for a solution that uses machine learning trained on large-scale, multi-industry datasets to flag both known and emerging fraud patterns. The ability to adapt over time makes this an essential feature for long-term fraud defense.   6. Click Journey & Traffic Scoring A robust platform doesn’t just analyze a single click; it evaluates the entire journey. From impression to post-click behavior, each interaction should be scored based on engagement, path anomalies, and conversion likelihood. This helps identify suspicious traffic that may initially look normal.   7. Custom Rules Engine Every brand runs unique campaigns. A good tool should offer flexible rule configurations, letting you set thresholds for frequency, geo-targeting, source type, traffic origin, and campaign duration. This enables a fraud strategy that aligns with your media goals and market dynamics.  8. Auto-Blocking & Publisher Blacklisting Detection is just one part of the job. Choose a solution that instantly blocks invalid clicks and allows you to blacklist underperforming or suspicious publishers from your affiliate or display ecosystem. It should also integrate with your ad platforms to automate enforcement.  9. Transparent Reporting & Optimization Layer Data transparency is critical for trust and decision-making. A trustworthy platform offers intuitive dashboards with campaign-level and source-level insights, including traffic diagnostics, high-risk locations, time-based fraud trends, and publisher-level threat analysis. Shareable reports should help your media, product, and performance teams to adjust strategies and make data-driven decisions.  How mFilterIt Stands Apart from Other Click Fraud Detection Solutions Most tools stop at surface-level detection. mFilterIt offers a comprehensive, customizable, and omnichannel solution – Valid8 that addresses fraud at every point in your ad journey, built for marketers who demand accuracy, control, and performance clarity. Here’s how:  Multi-Platform Level Protection Across Your Entire Ad Ecosystem Our advanced ad fraud detection solution, Valid8 provides end-to-end fraud protection across all major digital media channels – search, display, programmatic, affiliate, app installs, and OEM campaigns. The platform delivers consistent click fraud validation across all sources, whether you run campaigns across Google Ads, Meta, DV360, affiliate networks, etc.   This ensures you are not just protecting isolated campaigns but safeguarding your entire performance stack. With no platform blind spots, your budget is protected wherever it’s being spent, maximizing both visibility and returns.  Source-Level Transparency Unlike tools that offer generic fraud reports, mFilterIt provides detailed visibility down to the source and sub-source level. You can identify exactly which publisher, sub-publisher, campaign, or device is generating invalid traffic.   This level of granularity enables precise decision-making, whether it’s blacklisting bad actors, negotiating with networks, or optimizing media allocation. This helps marketers to stop ad fraud at the root source instead of relying on broad-level assumptions.  Advanced Custom Logic Enablement for Brand-Specific Protection Our click fraud protection software combines machine learning algorithms with customizable brand-specific rules to deliver smarter fraud detection. The ML engine identifies behavioral anomalies, unusual device patterns, and other red flags that generic rule-based systems miss.   At the same time, brands can implement custom logic tailored to their business goals, regions, or historical fraud

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attention metrics

What Are Attention Metrics: Why Brands Need To See Beyond Viewability

Blog, Viewability /

Marketers have relied on viewability as a metric for the longest time to measure the success of an ad campaign. Afterall, an ad seen means the ad is working – right? But with the auto-play video ads in the picture and the attention of the users moving to instant scrolling, the ad being just viewable cannot be reliable. The hard truth that modern marketers are realizing – the ad might be technically “seen” but it can be completely being ignored by the audience. Focusing just on viewability metrics is not sufficient to understand whether the user absorbed the ad’s message or not. Therefore, the need for an advanced ad metric to evaluate ad performance was required. This shifted the focus to attention measurement or what the industry now calls attention metrics. In today’s ecosystem, where digital platforms are cluttered, user behavior is fragmented and choose what they really want to pay attention to, being seen is no longer enough. Brands need to understand the real difference between a wasted impression and a meaningful engagement. In this blog, we’ll break down why viewability metrics are no longer enough, what attention metrics actually are, how they differ from traditional viewability, and how ad fraud detection solutions like Valid8 by mFilterIt are helping brands optimize not just for ad impressions, but for real impact. Why Viewability Is No Longer Enough For years, viewability has been the go-to metric to validate ad delivery. According to the IAB (Interactive Advertising Bureau) standard, an ad is considered “viewable” if 50% of its pixels are in view for at least one second (for display) or two seconds (for video). Let’s take an example, think about a banner ad placed in the middle of where the page scroll ends. As per the IAB standard, if it is 50% visible, it will be considered viewed. But in reality, your ad failed to get the attention of your viewers. Or a muted video ad that autoplay’s in the background, technically viewed, but your user never saw it. This is where improvement was really needed from older viewability standards, which didn’t account for whether the user ever saw the ad at all. Viewability is a binary metric. It doesn’t reveal: Whether the user noticed the ad Whether it resonated Whether it drove engagement or action What are Attention Metrics? Attention metrics is a more advanced, holistic way to measure ad engagement. They go beyond visibility and ask: Did the ad actually capture the user’s attention? Rather than relying on a single data point, attention metrics pull together a wide array of proxy measurement signals – behavioral, device context, user intent. Here’s how each signal helps reveal true engagement: 1. Time in View An ad seen for 1 second isn’t equal to one seen for 7 seconds. Example: If a user pauses scrolling and watches your ad for 8 seconds, it signals genuine interest, unlike someone who scrolls past instantly. 2. Scroll Depth How far a user scrolls before encountering your ad can impact its effectiveness. Example: If your display ad is placed lower on a webpage but still gets noticed, it reflects active user engagement, not passive viewability. 3. Position on Screen Ads placed at the top of the page are more likely to be seen but not necessarily remembered. Example: An ad shown at eye-level in the content zone is more likely to draw attention than one placed in the banner blind spot. 4. Audio Status (Mute vs. Unmute) Muted ads play in the background. Unmuted ads demand attention. Example: If a user unmutes a video, it’s a strong indicator they want to hear your message, far more valuable than just a view. 5. Pause/Play Behavior This signal captures active intent to watch rather than passive exposure. Example: If someone pauses your video mid-way and resumes later, they’re engaged. That’s meaningful attention; viewability cannot track that. 6. Skip Rate & Skip Point In skippable ads, when users skip matters more than if they skip. Example: If 80% of users skip at 3 seconds, your hook isn’t working. If most watch for 7-10+ seconds, you’ve captured their attention. 7. Screen Orientation Device orientation changes reflect real-time distraction or focus. Example: A user flipping their phone from portrait to landscape to watch your video indicates commitment. Switching apps mid-ad signals lost attention. 8. Click or Interaction Activity Clicking, swiping, or engaging with ad elements shows active intent. Example: Hovering over a CTA or clicking to expand a product carousel shows curiosity, an attention metric that impressions can’t quantify. 9. Dual-Screen Behavior This detects whether users are actively watching your ad or multitasking on another screen or app. Example: If a user switches to another app mid-ad (like messaging or social media), it signals attention drop-off, even if the ad was technically in view. The Core Differences: Viewability vs Attention Metrics Challenges Brands Face Without Attention Metrics Viewability metrics create blind spots across different ad formats, ultimately affecting how brands measure, optimize, and scale their campaigns. Here how: Display Ads 1. Lack of Depth in User Engagement – Without attention metrics, brands can’t differentiate between a view and actual user interest or interaction. 2. No Insight into On-Screen Placement Performance – Ads may be technically viewable but shown in low-engagement zones, leading to misjudged campaign effectiveness. 3. Inability to Identify and Prioritize High-Intent Ad Impressions – Without behavioral data like time-in-view or interaction rates, valuable signals for retargeting and optimization are lost. 4. Exposure to Display Ad Frauds like Ad Stacking – Without attention validation, fraudulent tactics such as ad stacking, where multiple ads are layered on top of one another, inflate viewability numbers while delivering zero real attention. Skippable Video Ads 1. Misleading Viewability and Completion Metrics – Videos may be counted as viewed even when skipped early, hiding poor creative ad performance. 2. No Visibility into Drop-Off Trends – Without skip point tracking, brands cannot identify where audience interest fades or how to refine the first few seconds. 3. Missing

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Impression Spam

What is Impression Spam? Know How It Impacts App Campaigns.

Blog, Ad Fraud Blog - Valid8 /

While marketers focus on driving installs and scaling campaigns, there’s a silent threat that’s bleeding budgets dry – Impression Spam. These are fake or hidden impressions generated to manipulate attribution models and steal credit for app installs, especially through View-Through Attribution (VTA). On the surface, everything looks great. High impression counts, rising install numbers, good reach. But beneath, you’ll often find invalid impressions that were never actually seen by real users. Here’s the uncomfortable truth: if your VTA numbers are spiking without corresponding clicks, your ads are likely being targeted. Impression spam doesn’t just distort your data; it rewards fraudsters, inflates costs, and hijacks installs that should have been credited to genuine traffic or organic users. That’s where impression validation becomes non-negotiable. In this article, we’ll talk about how impression spam works, what red flags to watch for, and how mFilterIt helps you bring transparency back to your attribution funnel with impression integrity. Why Impression Spam Happens? Most marketers use both Click-Through Attribution (CTA) and View-Through Attribution (VTA) to measure performance. While CTA requires a user to click on an ad before converting, VTA allows installs to be credited based solely on an impression, if the user later installs the app within the attribution window. This is where the impression fraud creeps in. VTA opens the door for bad actors to take advantage of attribution systems, inflate VTA that allow installs to be attributed even when no click happens, just by showing an impression. What is the Difference Between Click Through Attribution & View Through Attribution? While both CTA and VTA serve distinct purposes in performance measurement, their attribution mechanics differ significantly. Here’s How:   Why is High VTA Ratio a Problem? One of the major indicators of impression spam is an abnormally high View-Through Attribution (VTA) rate, particularly when it significantly exceeds your Click-Through Attribution (CTA) numbers. As a general benchmark, if more than 60% of your attributed installs are coming through VTA, it calls for a close audit. It is very less likely for a user to see an ad, not click on it but remember it and later search for the app on play store to install. This kind of user journey is possible, but when it appears on a scale, it’s statistically improbable. An inflated VTA rate often signals that impressions are being generated in unusual ways: Impression stuffing: Multiple invisible ads loaded at once, none of which are truly viewable. Background ad rendering: Ads shown in hidden browser tabs or apps running in the background. Bot traffic: Automated scripts mimic user behavior, including fake impressions and subsequent app installs, to game attribution making it appear as though an ad influenced the install. When in reality, no meaningful user engagement occurs. And while these installs might look normal on the surface (matching attribution windows, geographies, and even device models), they usually show poor post-install performance: no session activity, zero events triggered, and very high uninstall rates. On the other hand, a healthy performance-driven campaign should have a balanced ratio of CTA to VTA, especially when you’re targeting engaged users with clear calls to action. While VTA can play a valuable role in measuring upper-funnel awareness (particularly for display, video, or CTV ads), it should not dominate your attribution model, especially if your campaign objective is direct response or installs. How Impression Spam Hurts Your Campaigns? (Some Red Flags You Shouldn’t Ignore) Impression spam affects campaign son multiple basis: Wasted Budget: You end up paying for impressions that never reached real users. Skewed Performance Data: Optimization decisions based on fake data lead to flawed strategy. Fraudulent Payouts: You reward the wrong sources, while genuine traffic partners get undervalued. Organic Hijacking: Fraudsters take credit for installs that would’ve happened anyway, distorting your organic benchmarks. Poor ROI on User Acquisition: Invalid impression drives low quality installs affecting return on investment as well as LTV And if you’re wondering how to spot impression spam in your performance data, here are a few red flags to keep an eye on: High VTA, Low CTA: A disproportionate number of installs attributed to views over clicks. Short impression-to-install windows: Installs happening unusually fast after impressions are served. Low post-install engagement: Users attributed through VTA show poor retention or event completion. Traffic from non-targeted geographies: This is clearly indicative of impression stuffing or bot activity. Do you know ad fraud is not limited to just impressions? Learn how it impacts your bottom line in this blog.   How mFilterIt Helps You Detect and Block Impression Spam Stopping impression spam isn’t just about identifying invalid impressions; it’s about restoring trust in your data and ensuring that every impression that enters your attribution funnel is validated and has impression integrity. That’s exactly what we do for our clients. Our advanced ad fraud detection solution helps protect the very first touchpoint of the user journey – impressions. Here’s how: 1. Impression Integrity Validation Our tool validates each impression based on multiple parameters – device authenticity, placement, location, timestamp accuracy, etc. It ensures that impressions are not only technically served, but also actually seen by real users under acceptable conditions. 2. Granular VTA vs. CTA Disparity Checks It also helps analyze attribution patterns and conversion timelines, proactively detect anomalies in View-Through Attribution ratios. If the VTA numbers rise disproportionately compared to Click-Through Attribution, it flags the issue before the whole campaign is compromised. 3. Bot Install Detection Linked to Impression Trails Many fraud schemes use bots that not only generate fake impressions but also simulate full-funnel activity. Our tool identifies such bot installs by linking post-install behavior to suspicious impression patterns. This helps uncover impression fraud that traditional MMPs overlook. 4. Source-Level Blacklisting and Partner Insights Our proprietary impression validation solution also gives complete visibility to monitor all traffic sources. Once identified, these sources are automatically flagged or blacklisted, reducing budget wastage at the earliest stage. We have helped Kuku FM improve their engagement by validating their ad traffic. Learn how.   Conclusion: Protect Your Campaigns with

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Affiliate Fraud Is Rising: Here’s How to Secure Your Campaigns

Affiliate Fraud Is Evolving: Is Your Affiliate Monitoring Strategy Keeping Up?

Blog, Affiliate /

Paying affiliates based on performance, right? But are you paying for the performance that drove genuine results? There’s a common misconception that affiliate campaigns are low-risk because they’re performance-based. Well, not quite. Everything has two sides and so do affiliate campaigns. On one side, affiliate campaigns promise scale, reach, and revenue. However, the other one is a darker side of unseen threats due to various types of affiliate fraud techniques, brand abuse, attribution hijacking, misuse of coupon codes, etc. Many campaigns may show rising ROAS, but what’s often missing is how that performance was achieved. Was that traffic truly incremental, or did an affiliate use deceptive techniques just to win last-click attribution? According to an mFilterIt first-party analysis of 343 campaigns run in 2024, 43% of affiliate fraud was detected in India, 35%, 34%, and 33% in MENA, US, and Europe, respectively. In 2025, affiliate marketing success isn’t just about conversions – it’s about validating authenticity, protecting your brand, and rewarding partners who play fair. In this article, we will explore the hidden threats undermining affiliate marketing and understand how affiliate monitoring & brand-safe performance can actually amplify campaign impact when you monitor it right. The Hidden Threats in Affiliate Campaigns While affiliate marketing remains one of the most scalable performance channels, marketers need to recognize the warning signs, to protect both brand equity, budget, and stay ahead. 1. Unauthorized Brand Bidding on Keywords (Search Hijacking) One of the most common forms of affiliate fraud and manipulation is brand bidding. Using this tactic, affiliates bid on your branded search terms, hijacking users who are already looking for your product or website. Instead of converting through organic results or direct visits, users are rerouted through paid ads, earning the affiliate a commission they didn’t truly earn. Impact: This not only inflates your paid search costs but also creates internal competition between your media team and your affiliate partners. And you end up paying twice for traffic that was already yours. 2. Misleading Creatives and Unauthorized Branding Affiliates and influencers often deploy creatives that fall outside your official brand guidelines and misrepresent your brand using outdated logos, fake discount banners, or fabricated promotional messaging. These visuals are designed to grab attention, inflate clicks, creating confusion or mistrust among customers. Impact: Misrepresentation damages brand credibility. These unauthorized creatives often appear on platforms or websites where your team has limited visibility, making enforcement difficult unless you’re actively monitoring across channels. 3. Typo-Squatting and Duplicate Listings Fraudsters often set up websites or marketplace listings using typo-ed brand names or unauthorized duplicates of your product pages. They optimize these pages to rank high in organic results or promote them through ads, redirecting users through affiliate links. Impact: You lose official visibility, and customers may unknowingly buy from unverified resellers or outdated sources, damaging your brand integrity. 4. Promo Code & Cashback Abuse Affiliates and influencers often misuse coupon codes to manipulate attribution. When these codes are placed on public coupon websites, they begin ranking on search engines attracting organic traffic that would’ve come directly to your site. In some cases, influencers even post their codes in comment sections of social media posts, hijacking conversions without truly driving demand. Impact: Skewed performance reporting, reduced margins, reputational damage, and customers conditioned to always expect discounts, even when you don’t offer them 5. Hidden Redirects and Cloaking Techniques Some affiliates use browser extensions, in-app overlays, or cloaked links to secretly redirect users through affiliate URLs, without ever making it visible to your team. What the user experiences and what your tracking tools record may be two very different things. Impact: Lost visibility, deceptive tracking, and lost control over customer journey insights. These invisible tactics not only violate user trust but also pollute your performance data, making optimization difficult. Advanced Affiliate Fraud Tactics in 2025 Every Marketer Should Know About Affiliate fraud today is no longer about random bad actors exploiting obvious loopholes. It has evolved into a coordinated, intelligent system often powered by automation, artificial intelligence, and sophisticated evasion techniques used by affiliates to earn commissions. Affiliate Collusion – Two or more affiliates working together Fraudsters now operate in groups or affiliate rings, where multiple affiliates coordinate their efforts to game attribution models. They rotate tracking links, share device IDs and IP addresses, and even simulate varied browser behaviors to avoid detection. Because each affiliate in the ring appears to act independently, the fraud doesn’t trigger obvious alerts. Without deep behavioral analysis or identity mapping, affiliate collusion generates invalid traffic that siphons off the marketing budget and corrupts data, misleading overall performance. Affiliate Cloaking Fraud Affiliate cloaking involves showing a compliant, brand-approved landing page to your audit tools or standard fraud detection systems while redirecting real users to unauthorized destinations/landing pages. To the brand, everything looks clean: your code sees the right creatives, landing pages, and parameters. But the end user might see fake offers, misleading discounts, or even be redirected to counterfeit products pages. This gives you a false sense of compliance while exposing your customers to experiences you don’t control and can’t see. Why Standard Campaign Metrics Can’t Detect Any of These Most affiliate managers track surface metrics: click-through rates, ROAS, last-click conversions, etc. But what if that conversion came from a hijacked keyword? What if the click came from a cloaked URL? What if the influencer was running fake creatives on irrelevant inventory. Affiliate fraud thrives in the gray zones between attribution layers, browser behaviors, and third-party channels. The truth is you can’t see affiliate fraud in a dashboard; you need affiliate monitoring tools that go deeper. If you’re not validating the “how” behind affiliate conversions, you’re only seeing half the picture. What These Threats Cost You Let’s break down the real impact of affiliate fraud: Paid commissions on traffic that would’ve converted anyway Loss of organic traffic due to brand keyword hijacking Inflated KPIs leading to poor optimization decisions Reputational damage that can erode long-term customer loyalty Missed growth opportunities and lack of strategic

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