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Brand Bidding in Affiliate Marketing

Brand Bidding in Affiliate Marketing: What It Is and Why It’s Riskier in 2025

Blog, Affiliate /

Your brand keywords are your identity. But what if you’re paying higher cost for your brand keywords, or in worst case scenario – paying for your organic traffic.  Brand bidding is a technique used by affiliates and competitors where they bid on your branded keywords to divert your traffic to their landing pages. The impact of brand bidding in affiliate marketing is not just limited to ad budget wastage.   The brands have to pay more for their own branded keywords, they lose search traffic, and revenue drops.   In 2025, it is expected that the expenditure on search advertising will hit $351.5 billion worldwide, indicating a strong growth in the paid search sector. And with the demand for search surges, it is critical for brands to have the right protection against brand bidding violations.    According to our analysis done, we have found that 43% of affiliate traffic is invalid.   This blog is going to unpack:  Why brand bidding protection is critical in 2025?   What Leading Brands Are Doing to Prevent It?    How mFilterIt Protects Your Affiliate Program from Brand Bidding?    Why Brand Bidding Is Riskier in 2025 In 2025, brand bidding has become more than just a compliance problem; it has emerged as a strategic threat. It directly attacks the authenticity of your website, leaving users in a dilemma and baiting them to make the purchase from an affiliate’s website or tracking link. Let’s understand how brand bidding is riskier in 2025:  1. Increased PPC Brand Bidding = Higher CPCs on Brand Terms Affiliates bidding on brand keywords are directly proportional to the cost-per-click. The higher the bidding, the higher the cost-per-click, leading to an increased cost of paid search campaigns, making the visibility achievement on search engines greater challenge.   2. Detection Becoming Harder Due to AI-powered Tool Monitoring the actions of affiliates and enforcing policy violations rules have become tougher for brands as affiliates consistently use cloaking, dynamic redirects, and global targeting by AI to evade detection.  3. Exploitation of Performance Metrics In 2025, brands are relying heavily on performance metrics, prioritizing channels that generate maximum clicks, conversions, and ROAS. Hence, affiliates aim to exploit these metrics by click baiting users and taking credit of the purchases, they made without creating any new demand. This boosts the performance statistics of affiliates through mispresented numbers.  4. Brand Goodwill at Stake Misleading affiliate advertisements, fake discounts, and unreliable affiliate tracking links can severely hamper the goodwill of the brand by eroding customer trust.  Real Impact: How Brand Bidding Eats into Your ROI Your market funnel is at risk; brand bidding is draining your profits. Let’s know how profit leaks are undermining your return on investment (ROI):  1. One Customer, Double Payment If users who are your organic customers, are specifically searching for you, visit an affiliate’s tracking link and make purchases, you lose one organic user and instead pay the affiliate commission on a sale you would have gotten anyway.  2. CPCs Rise Manifold Your PPC campaigns land in a competitive landscape when affiliates bid on your keywords, increasing the cost-per-click and affecting the overall paid search efficiency.  3. False Attribution Affiliates gain commission from selling your products, but no new demand is created. The customers are the same buyers who would have visited your website, anyway, hence creating false attribution.   4. Poor UX = Lost Conversions Misleading or outdated ad copy from affiliates can create confusion, frustration, or distrust — increasing bounce rates and reducing conversion quality.  How to Prevent Brand Bidding: What Leading Brands Are Doing As major talks are going around how to prevent brand bidding in affiliate marketing, brands are also recognizing its importance. The following are the strategies opted by them to tackle the same:  1.Transparent Brand Policies and Contracts Brands create their affiliate program agreements, forbidding affiliates to steal their trademarked terms. The agreement includes what keywords the brand can use; the penalties imposed on the agreement and more.  2. Real-time Monitoring through Automation Brands are keeping a hawk’s eye on violations of their trademarks by affiliates. They monitor the landing pages, ads that appear above their official website and take action accordingly.  3. Negative Keyword Implementation The tactic of negative brand keyword implementation is followed by several brands across the affiliate campaigns to prevent affiliate ads from triggering on brand terms.  4. Timely Audits & Reporting Brands evaluate affiliate traffic through patterns, source, and conversion behaviour to detect and prevent suspicious behavioural patterns. This also includes reviewing landing pages and promo codes to identify any misleading information.  5. Cross-Functional Team Alignment (Legal, PPC, Affiliate Management) Leading brands are bringing legal, PPC, and affiliate teams together to tackle brand bidding in affiliate marketing. Legal handles takedowns, PPC monitors brand keyword activity, and affiliate managers enforce the rules. When these teams work in sync, violations get caught faster and the brand stays protected.  6. Third-party Solution for Detecting Brand Bidding Violation Third-party solution provides unbiased monitoring and detection of brand bidding violations. By offering an external perspective, it ensures transparency, credibility, and consistent protection of a brand’s search presence.  How mFilterIt Protects Your Affiliate Program from Brand Bidding Every click, every booking, every creative asset your brand deserves to own them. Yet brand bidding and unauthorized promotions quietly cause loss of direct traffic, inflate acquisition costs, and dilute trust.  That’s where EffCent steps in, mFilterIt’s affiliate monitoring solution built to protect your performance marketing ROI. But how do we do it? Let’s know now –  Real-time Monitoring –Track brand keyword bidding across ad networks and regions to spot misuse instantly.  Actionable Reporting –Deliver daily reports that highlight brand bidding violations for quick corrective action.  Proprietary Detection –Use Effcent’s technology to precisely identify unauthorized bids on branded keywords.  Restrict Violations –Enable immediate blocking of ad networks bidding on brand terms.   Know how a leading brand utilized mFilterIt’s affiliate monitoring solution to combat brand bidding.  Conclusion Brand bidding is a real threat to your performance, budget, and brand trust. As we

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Ad Fraud Detection: Why It Should Be a Strategic Priority for Businesses

Ad Fraud Detection: Why It Should Be a Strategic Priority for Businesses

Blog, Ad Fraud /

Ad fraud is not a myth anymore. It has been there for a long time now, and with the emergence of AI and automations, it is only going to increase.   Moreover, ad fraud is no longer limited to fake clicks and impressions. It now infiltrates every stage of the funnel, from impressions and installs to leads and even post-install events. Many marketers think they’re getting real users, but they’re actually getting fake leads and misattributed conversions.  This means performance marketers and advertisers are not only losing money to bot traffic at top of the funnel also to fake leads and fraudulent installs in web and mobile app campaigns, respectively.   This is why ad fraud detection for brands cannot be seen as a checkbox activity anymore. It has become a strategic necessity to protect budgets and ensure real business growth with clean traffic.  The Real Cost of Ignoring Ad Fraud  The financial losses from ad fraud are massive, but the hidden costs are even greater:  1. Wastage of budget  Every click, lead, or install lost to bots or fraudsters is money that could have been spent acquiring real customers. Over time, this budget leakage eats away a significant portion of marketing budgets.  2. Misleading data and decisions Fraudulent impressions, clicks, and leads distort campaign metrics, making it hard for marketers to judge what’s really working in their favor. This leads to wrong campaign optimizations, wasted investments, and strategies built on unreliable performance data.  3. Missed opportunities  Each fake lead or user acquired represents a genuine customer lost to competitors. Ad fraud not only drains resources but also blocks real growth opportunities, slowing down acquisition and reducing overall market share.  4. Brand trust and reputational risks Fraudsters often place ads in unsafe environments, damaging brand credibility. Fake affiliates and impersonation tactics can also misuse brand assets, leading to long-term erosion of consumer trust and loyalty.  5. Lower campaign efficiency and ROI  Campaigns optimized on fraudulent signals end up favoring poor-performing channels. This lowers efficiency, increases customer acquisition costs, and reduces ROI, making brands spend more for less real business impact.  6. Wasted sales and operational resources – Fake leads clog CRMs, forcing sales teams to chase invalid prospects. Time, effort, and operational costs are wasted on unqualified data, reducing team productivity and slowing down real pipeline conversion.  7. Distorted customer acquisition and LTV metrics Fraudulent activity inflates acquisition numbers while delivering no genuine value. This skews CAC and LTV calculations, misleading teams into thinking growth is sustainable when in reality it’s based on fake signals.  8. Eroded stakeholder and investor confidence – When financial reports are built on inflated numbers, stakeholders and investors lose confidence in performance claims. Over time, this damages credibility and makes it harder for brands to secure future investment.  Explore our latest ad fraud guide to learn about various types of ad fraud tactics used today.  Why is Ad Fraud Detection a Strategic Necessity?  Ad fraud detection is a strategic necessity for brands who want to grow profitably in today’s complex digital ad ecosystem. Every rupee or dollar invested in advertising should deliver measurable business outcomes, not vanish into fraudulent traffic, fake clicks, invalid leads, or bot-driven installs.  Effective fraud prevention empowers brands with clean, reliable data, enabling sharper targeting, accurate optimization, and smarter decision-making. This integrity of data ensures that campaigns are scaled based on genuine performance, not misleading signals.  Ad fraud detection also creates a competitive edge for brands that helps minimize wastage, reallocate budgets to winning campaigns, outperform competitors, and strengthen market position. While fraudsters continuously evolve their methods, proactive monitoring becomes essential to stay ahead of emerging threats. Know how ad fraud impacts every stage of the funnel  Why Relying Only on MMP’s Bundled Ad Fraud Services is Not Enough? MMPs are built for measurement and tracking last-click attribution, not fraud detection or prevention. Here’s why relying solely on them is risky:  MMPs payouts are released basis on the number of attributions sources. When fraud is detected, it reduces the sources impacting their primary revenue thereby creating a conflict of interest.   Attribution tools often miss sophisticated fraud tactics such as click flooding, click injection, device spoofing, event spoofing, etc.  MMPs have limited coverage capabilities. They can track activity but struggle to differentiate between bot-generated, fraudulent, and real users at scale.  That is why brands need to shift towards independent and advanced ad fraud detection tools to ensure brand and marketing budget safety and accountability across channels.  What to Look for in an Advanced Ad Fraud Prevention Solution? To truly protect growth, brands need solutions that go beyond surface-level checks. Here’s what to look for:  Full-Funnel Coverage – Protection across all stages of the funnel, impressions, clicks, installs, leads, and post-install events.  Early Detection & Prevention – Catching fraud before budgets are wasted.   Advanced Bot Pattern Recognition – Detecting spoofing, click flooding, and behavior simulations based on various parameters.  Cross-Channel Protection – From Google and Meta to programmatic, affiliates, and apps.  Transparent Reporting – Log-level insights that empower marketers with clarity and control.  This is where we help. Our advanced ad fraud detection solution, Valid8 by mFilterIt ensures only clean traffic enters your CRM data by detecting all types of generic and sophisticated fraud tactics proactively.   Also read in detail: What marketers should look for in a click fraud prevention tool  How Proactive Ad Fraud Detection adds a Competitive Edge? Proactive ad fraud detection isn’t just about saving money. When brands move from reactive checks to proactive fraud prevention strategies, the advantages multiply.  By eliminating this invalid traffic, fake clicks, and installs, brands ensure that every dollar spent goes toward acquiring genuine customers, reducing overall CPA/CPI, and improving campaign efficiency.  Proactive ad fraud detection also helps ensure only authentic leads enter the funnel, enabling sales teams to focus on qualified prospects and close more deals with higher success rates.  Marketers only target real users, leading to stronger engagement, better retention rates, and higher ROAS across digital channels.  Clean, fraud-free data ensures accurate

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Festive Season Ad Spend from Mobile Ad Fraud

Marketers’ DIY Guide: Safeguard Your Festive Season Ad Spend from Mobile Ad Fraud

Blog, Mobile Ad Fraud /

The festive season in India is like a high-stakes battleground for consumer attention, and in 2025 the stakes are even bigger.  This year, brands are using all possible strategies with irresistible festive offers. More than ever, AI-powered tools are being used to personalize campaigns, predict shopping behavior, and create highly targeted festive experiences for consumers.  Recent reports reveal that digital ad spends are expected to shoot up by 15–25% this year. That’s over ₹60,000 crore expected to be invested (nearly half of the industry’s yearly budget) into the ecosystem in just a few weeks – Dussehra to New Year.  Moreover, shoppers are equally excited. 80% of brands plan to increase their festive budget compared to last year, and most of that action will happen on mobile-first platforms.  This is the golden time of the year for performance marketers to scale their app performance, boost customer acquisition, and maximize ROI.   However, scaling business growth through mobile advertising campaigns during the festive season is not as simple as it might sound. While brands prepare to shine, fraudsters prepare too – to drain festive ad budgets with fake installs, bot-driven clicks, click flooding tactics, event spoofing, etc.   And during high-stakes periods, when the competition is even more fierce, even a small leakage can snowball into lost sales and damaged ROI.  So, how do you make sure the glowing numbers on your dashboard aren’t just smoke and mirrors? The answer is – by detecting and preventing mobile ad fraud this festive season before it hits your bottom line.   TL; DR, what to expect from this article:  Why mobile ad fraud spikes during the festive season?  A hands-on checklist to spot and block mobile ad fraud  The risks of ignoring fraud during festive season  How an ad fraud detection solution helps protect performance campaigns?  Why Mobile Ad Fraud Peaks During Festive Season?  During festive seasons, whether it’s Diwali in India, Ramadan in the Middle East, or Black Friday across global markets, brands significantly increase their marketing investments. And fraudsters follow the money, waiting for chances like these. Moreover, affiliates and media partners also compete aggressively to deliver results in volume. This creates a perfect storm for sophisticated fraud tactics to slip through traditional ways of ad fraud detection.  Here’s why fraud peaks during festive campaigns:  1. Festive budgets attract fraudsters When brands increase ad spends during the season, fraudsters see it as the perfect opportunity to grab a bigger portion of ad budgets as compared to normal days.  2. Traffic volumes overload systems With millions of clicks and installs happening in a short span, it becomes tougher to spot which ones are real and which ones are fake without the right app fraud detection strategy in place.  3. Pressure to deliver numbers Affiliates and media partners often push for higher volumes to deliver results on a faster and larger scale often using various methods, which means fraudulent traffic can slip through unchecked.  4.Short and intense campaign timelines  Festive campaigns usually run for a few weeks. In the rush to maximize results quickly, marketers don’t always get the time to investigate suspicious activity.  5. Shoppers are more active on mobiles Since most festive shopping now happens on mobile, fraudsters use fake devices, bots, and emulators to mimic real user activity, making fraud harder to catch. The Cost of Ignoring Mobile Ad Fraud During High-stakes Periods like Festive Season Ignoring these red flags can be disastrous for brands running mobile advertising campaigns:  Fraudulent traffic consumes budgets that should be driving real festive conversions.  Customer acquisition costs also spike as fake installs get counted.  Fraud makes campaigns look successful when in reality, genuine reach is limited.  Every dollar wasted on fake users is one less spent reaching real shoppers.  Poor campaign performance badly on brands and damages affiliate trust.  Festive campaigns have short windows, meaning there’s little room for error. But by the time mobile ad fraud is detected, the damage is already done.  The DIY Festive Season Mobile Ad Fraud Detection Checklist for Marketers  While recognizing sophisticated levels of mobile ad fraud requires an advanced AI-ML-based ad fraud detection solution to be in place, many patterns of fraudulent activities can be identified using simple observation.   This DIY checklist is made specifically for marketers to address mobile app fraud, affiliate fraud, and what to watch for:  1. Unusual Click-to-Install Time (CTIT) Patterns Fraudsters flood fake clicks to hijack credit for real installs, distorting CTIT and attribution data, making affiliates look like they are delivering genuine users.  Festive Relevance:  High install surges make fake CTIT timings harder to spot.  Affiliates stuff clicks before festive installs to claim credit.  What to Watch For:  Installs happening too fast (<10 seconds) often indicate bot-driven installs.  Installs delayed too long (>24 hours) indicate click flooding.  CTI < 0.1% likely indicates click spamming.   2. Abnormal Post-Install Behavior  Fraudulent or fake installs may look valid at first but fail to deliver meaningful engagement or purchases post-install, inflating top-of-funnel numbers while draining budgets.  Festive Relevance:  Real festive shoppers browse more, add to cart, and purchase.  Fraudsters simulate installs or spoof in-app events only to claim payouts.  What to Watch For:  High installs with shallow sessions or instant exits.  Zero meaningful actions like adds-to-cart or purchases.  3. Click Injection and Click Spamming  Fraudsters generate fake clicks just before a user installs your app organically, stealing credit from genuine traffic.  Festive Relevance:  With installs surging, fraudsters have more organic actions to hijack.  Affiliates exploit festive urgency to push suspicious click activity.  What to Watch For:  Affiliates with sudden spikes in attributed installs.  Install timelines overlapping heavily with organic traffic.  4. Device Farms and Emulator Traffic Large-scale device farms and emulators simulate fake installs and user activity, tricking attribution systems into marking them as conversions.  Festive Relevance:  Higher festive payouts make device farms highly profitable.  Thousands of fake users can be generated overnight.  What to Watch For:  Repeated installs from identical OS versions or device models.  High device reset rates from the same source.  5. Geo-Mismatch and Proxy

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Lead Landing Page Optimisation

Lead Landing Page Optimization – How to Spot Bots and Improve Lead Quality

Blog, Ad Fraud /

The USA digital advertising industry significantly relies on lead generation strategies. For advertisers in the USA, landing pages are the backbone of their ad campaigns. Millions are spent each year on ads to drive traffic and capture user attention.   But traffic is not always equal to opportunity. Marketers often notice unsettling patterns – even when dashboards show high volume of engagement and ad traffic, clicks, and form fills, somewhere conversions still lag behind.  Why is this happening?  The issue lies in the quality of traffic. Even the most beautifully designed, highly optimized landing page doesn’t convert if the people (or bots) visiting it were never real prospects in the first place.  Bots, click farms, and fraudulent traffic infiltrate digital ad ecosystems and degrade the lead quality, leaving advertisers with misleading reports and empty pipelines.  This not only leads to wasted ad spend but also performance inefficiencies across campaigns.   To overcome this challenge, improve landing page traffic quality and lead quality, brands need to rethink their landing page optimization strategies. Landing page optimization is no longer just about design, CTAs, or A/B testing; it is also about ad traffic validation and lead validation.  In this article, we will talk about:  What is lead landing page optimization?  The hidden threat brands in the USA need to be aware of.  How can advertisers spot bot patterns themselves?  Need for behavior analysis in landing page optimization – some practical steps to implement this  How an ad traffic validation and lead validation solution helps?  What is Lead Landing Page Optimization? Landing page optimization refers to the process of improving key elements of a landing page, such as design, messaging, and user experience to maximize conversions. A good landing page has a clear headline, persuasive copy, an easy-to-find call-to-action, and a layout that minimizes friction. All these steps help maximize conversion opportunities. But only if the traffic is real.  Advertisers often track clicks, form submissions, and engagement to guide optimizations. But bots quietly pollute the funnel, making A/B tests, bounce rates, and conversion data unreliable. This leads brands to optimize for noise while neglecting real buyers.  To break this loop, landing page strategies must go beyond surface-level optimizations. Incorporating behavioral analysis (like unusual browsing patterns or abnormal session times) and web fraud monitoring ensures traffic quality, helping brands achieve meaningful results and stronger ROI.   The Hidden Threat: How Bot Traffic Pollutes Lead Generation Campaigns Bot traffic is one of the most damaging but often overlooked issues in digital advertising. In the USA, where ad spend is among the highest globally, bots exploit every opportunity, from fake clicks to automated lead form submissions. Moreover, these aren’t just spam bots; fraudsters now use sophisticated bots that mimic real human behavior and are harder to detect.  Pay-per-call campaigns are also a widely used lead generation method in the USA. However, instead of connecting advertisers with genuine prospects, fraudsters generate fake or automated calls to trigger payouts. This not only wastes budgets but also distorts campaign performance data, leaving marketers with no real customer engagement to build on.  Further, the impact is severe.   Bots fill out lead forms with junk data, leaving sales teams chasing contacts that never convert.  Fraudulent submissions make campaigns appear cheaper per lead, masking the true cost of acquiring real prospects.  Inflated lead volumes give a false sense of demand, making it harder for marketers to forecast and allocate budgets effectively.  With CRMs overloaded by bot-generated entries, genuine leads get neglected, reducing the chances of meaningful customer acquisition.  Landing pages and ad creatives end up being optimized for fraudulent behavior instead of genuine prospects.  And when businesses base optimization decisions on false signals, it directly leads to long-term ROI damage.   That is why validating ad traffic based on various behavioral signals and parameters is no longer optional; it’s a core part of the landing page optimization strategy to combat web fraud.  DIY Guide: How Advertisers Can Spot Bot Patterns Themselves While recognizing sophisticated bot behavior requires an advanced AI-ML-based ad fraud detection solution to be in place, many patterns of fraudulent activities can be uncovered using simple observation and existing analytics platforms. Advertisers and marketers in the USA can start by monitoring:  Abnormal session duration: Bots often leave instantly, resulting in high bounce rates.   Repeated form fills: Look for duplicate names, fake emails, or strangely perfect data entries.  Analyze unnatural browsing patterns or scroll behavior: Real users skim unevenly; bots scroll mechanically, or not at all.  Watch clicks patterns: Bots click too quickly, with no hesitation or natural flow.  Unusual geographies/devices: Leads showing up from regions or devices outside your campaign targeting also indicates bot activity.  Traffic spikes at odd hours: Sudden bursts of activity at 2 AM followed by dead ends or zero follow-ups.  Junk conversion: High volume of form submissions, but emails bounce or calls go unanswered.  Bot registrants and junk leads: CRMs filled with incomplete profiles, disposable email IDs, or leads that never respond waste sales resources.  These DIY checks act as early warning signs against bot traffic. This helps advertisers identify suspicious patterns before optimizing landing pages.  Why Behavior Analysis Complements Landing Page Optimization When advertisers only optimize design and messaging of a landing page, they improve the chances that a visitor will take action. On the other hand, behavior analysis acts as the missing piece in the landing page optimization process.  Behavior analysis helps track how users move, click, and engage with a landing page or an ad, separating real prospects from fake ones.  By monitoring signals like irregular mouse movements, abnormal session durations, repeated form submissions, or patterns that don’t match natural human interaction, advertisers can separate genuine prospects from fraudulent traffic in real time.  As a result, this not only helps improve campaign efficiency but also improves lead quality. Sales teams receive fewer junk leads, reducing wasted effort. Marketers can make smarter budget allocation decisions when they’re working with clean data instead of bot-inflated numbers. Ultimately, it protects ROI by ensuring that every dollar spent is directed toward

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Every Brand Needs an Affiliate Monitoring Audit Checklist for Fraud-Free Growth

Affiliate Monitoring Audit Checklist: Every Brand Needs for Fraud-Free Growth

Blog, Affiliate /

If you’re running an affiliate program, chances are you have seen both sides of the story. On good days, affiliates bring in new customers, drive sign-ups, and help you scale faster than you imagined. But on bad days, you notice ad spends rising, driving minimal value, organic traffic dipping, or complaints from customers who clicked on an “official offer” that never came from you.   This is the reality for many performance marketers and affiliate program managers today. Affiliate marketing may be one of the most powerful growth channels for industries like ecommerce, fintech, and travel, etc. But it is also one of the most unpredictable if left unmonitored.   A single fraud affiliate can misuse your brand name, bid on your own keywords, or send traffic from unsafe domains, leaving you with inflated costs, lost revenue, and damaged brand credibility.  That is why the industry focus has now shifted to not just running affiliate campaigns but also monitoring affiliate performance closely.  Regulatory bodies like the Advertising Standards Council of India (ASCI) have been tightening disclosure norms and ad monitoring guidelines, signaling that brands are supposed to take complete accountability for how affiliates promote them.   Therefore, monitoring your affiliate ecosystem isn’t just a best practice anymore, it’s becoming the standard for sustainable growth.  So, here’s the big question: How do you keep affiliates in check without slowing down the performance they bring?  In this blog, we’ll walk through what a structured affiliate monitoring audit framework looks like and how brands can implement it to protect their budgets, brand reputation, and long-term growth.  Here’s What an Affiliate Monitoring Audit Checklist Looks Like  Affiliates often exploit loopholes to earn quick payouts using various affiliate fraud techniques like brand bidding, misuse of promo codes, duplicate listings, etc. To avoid this, we have curated an extensive affiliate monitoring audit checklist to help you evaluate your affiliate partner’s performance and take proactive decisions. Check out here:   1. Are affiliates using your brand assets and claiming to be your “official partner” without approval? Your brand name is your most valuable asset. Yet, some fraudulent affiliates often misuse it in ad copies, metadata, or promotional creatives to attract users without being directly associated with the brand. These unauthorized claims like “official partner” or misuse of logos not only confuse customers but also trigger legal complications.  How to audit and identify trademark violations:  Regularly scan ad copies, metadata, and landing pages for your brand name, variations, or misspellings.  Check that logos, product images, and creatives are only used with explicit brand approval.  Verify that affiliates don’t claim false associations like “official partner” unless authorized.  2. Do you often see other landing pages ranking on your brand keywords? Affiliates often bid on your brand keywords, driving up cost-per-click (CPC), hijacking search intent that anyway belongs to the brand organically. They also use techniques like typosquatting, like “Amazn deals” or “Flipkrt offers”, to divert users and earn commissions that eventually inflate your spend.  How to monitor affiliates for brand bidding:  Monitor search engines for affiliates brand bidding on your brand keywords.   Look for typosquatting errors and usage of competitor or brand keyword combinations.  Restrict affiliates from inflating CPCs by competing with your own campaigns.  Read this blog to know the signs you’re losing budget for unauthorized brand keyword bidding.  3. Are affiliates running campaigns using fake websites you don’t know about?  Fraudulent affiliates create lookalike websites resembling official sites (e.g., myntra-deals.in). Customers often mistake these for genuine pages, only to be scammed, amplifying further risks.  How to audit links for domain spoofing or IP squatting:  Identify lookalike or spoofed domains mimicking your brand (e.g., myntra-offers.in).  Audit affiliates to ensure all operating domains and subdomains are disclosed.  Prohibit the use of brand trademarks in domain names unless approved.  4. Do you find your brand ads placed on unsafe content websites? Affiliate ads sometimes end up on sites promoting adult content, gambling, drugs, or politically sensitive material. This misplacement not only harms the brand reputation but also leads to regulatory backlash.  How to audit unsafe affiliate ad placements:  Block affiliate traffic from adult, gambling, drug, piracy, or politically sensitive sites.  Use automated filters to prevent placements near hate speech, fake news, or unsafe content.  Continuously audit ad networks for brand-safe inventory.  5. Is your brand voice being manipulated with low-quality or AI-generated content?  Affiliates often generate content, blogs, reviews, or social media posts, to promote offers. But some use AI-generated text or plagiarized material, diluting brand voice and sometimes sharing misleading claims, creating confusion among customers.  How to monitor affiliate programs for content integrity:  Require affiliates to disclose AI-generated content.  Audit affiliate blogs, reviews, and posts for originality and compliance.  Prohibit plagiarism and ensure all content aligns with your brand voice and regulatory standards.  Learn how affiliates use AI-generated sites to game attribution models.  6. Are affiliate links exposing your users to malware sites or phishing attempts? Fraudsters exploit affiliate links through cloaking, forced redirects, or even malware injection. Customers may land on unsafe pages, creating cybersecurity threats and broken user journeys.  How to audit affiliate campaigns for unsafe linking practices:  Audit affiliate links for transparency and clarity (no cloaking, forced redirects, or hidden tracking).  Ensure links route only through secure, brand-approved channels.  Validate that links don’t lead to malware, phishing attempts, or unsafe redirects.  How do you enforce affiliate compliance and blacklist bad actors proactively? Affiliate fraud techniques are moving fast and adapting faster than most compliance teams. A one-time audit cannot prevent ongoing abuse. Without advanced enforcement and proof, even detected violations may continue.  How to enforce affiliate compliance:  Set up continuous monitoring for violations across ads, domains, and links.  Maintain an active blacklist of non-compliant affiliates, domains, and IPs.  Withhold payouts from affiliates breaching compliance rules.  Conduct quarterly audits to proactively identify risks.  How mFilterIt Helps Strengthen Your Affiliate Monitoring & Compliance Strategy  Running affiliate campaigns without continuous monitoring is like leaving your brand vulnerable to affiliate fraud activities. You may not notice the risk immediately, but affiliate campaigns,

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brand safety

Why Addressing Regional Nuances is Critical for Effective Media Brand Safety?

Blog, Brand Safety & Suitability /

When we think about brand safety, the first things that often come to mind are avoiding explicit, harmful, or misleading content. But in reality, the risks can be far more nuanced—especially when advertising across regions with diverse languages, cultures, and contexts. What feels neutral in one market might carry sensitive undertones in another. Take culturally diverse regions like India and MENA. In India, where dozens of languages and dialects coexist, a word that seems harmless in Hindi might have a very different, even offensive, meaning in Tamil or Bengali. In MENA, imagery or references that are acceptable in one country may be viewed as inappropriate or insensitive in another due to local religious or cultural norms. A single oversight can unintentionally shift how audiences perceive your brand. This is why regional nuance matters. Brand safety isn’t just about avoiding the obvious—it’s about ensuring your campaigns respect cultural sensitivities and linguistic differences. Without this lens, even the most well-crafted campaigns can end up in the wrong context, putting brand trust at risk. So, here’s the critical question every advertiser and marketer must ask: Are you confident your ads aren’t being placed next to culturally unsafe, politically charged, or regionally sensitive content? If your answer is “not entirely,” you’re not alone. In this article, we’ll explore: Why addressing regional nuances in brand safety is no longer optional Why markets like India and MENA demand special attention Why generic brand safety solutions fall short How regional intelligence ensures your ads stay relevant, respectful, and truly safe Why Addressing Regional Complexity is the Need of the Hour? India’s digital audience is incredibly diverse, and the demand for vernacular content is growing rapidly. Users are increasingly engaging with videos and posts in Hindi, Tamil, Telugu, Bengali, and many other regional languages across YouTube and other social media platforms. In fact, YouTube recorded a 60% surge in regional language viewership between 2017 and 2020. This isn’t a short-lived spike; it reflects a fundamental shift in how people across India consume and connect with digital content. Moreover, in MENA, Arabic dialect content dominates social platforms, OTT, and digital news consumption. This means brands are exposed to risks that go beyond the usual categories of violence, hate speech, or adult content. Regional complexity includes: Slang and satire that generic filters miss. Cultural references tied to festivals, traditions, or taboos. Political undertones embedded in everyday entertainment content. Religious cues that carry heavy meaning in local communities. Audiences today are hyper-aware. They don’t just notice what you advertise; they notice where you advertise. A misplaced ad next to unsafe local content isn’t seen as an accident, it’s seen as a lack of cultural sensitivity. This is why addressing regional complexity isn’t optional anymore, it’s a foundational need to protect brand trust. Why Regions Like MENA and India Demand Specific Attention Brand safety can never be a one-size-fits-all-strategy. MENA and India represent two distinct digital ecosystems. Both offer ample opportunities for brands, but their complexity makes them uniquely challenging when it comes to ensuring brand safety. Generic designed frameworks fall short because they do not account for the linguistic diversity, cultural nuances, and socio-political sensitivities that define these regions. In India: Languages like Hindi, Tamil, Malayalam, and Punjabi come with their own slang and mixed-language usage like Hinglish, etc. Festivals are frequent and deeply cultural, often tied to religion. Associating with the wrong content during these times can backfire rapidly. Politics and religion influence narratives across states during high-stake or emotional times like elections, tragic events, etc. In MENA: Arabic dialects differ widely. Egyptian Arabic is not the same as Gulf Arabic. Religious sensitivities are paramount; even seemingly neutral symbols can be inappropriate in the wrong context. Political undercurrents often blend with news and entertainment content, making context harder to spot without regional awareness. Therefore, with such complexities, audiences in every region expect brands to demonstrate cultural sensitivity, not appear besides offensive narratives. Know more about how brand safety threats are evolving in culturally diverse regions like India, and MENA. The Consequences of Avoiding Regional Contexts When brands avoid regional nuances, the risks are immediate: 1. Consumer backlash: A single screenshot of an ad next to unsafe content can spread across social media in minutes. 2. Loss of credibility: Cultural insensitivity erodes brand integrity, especially in markets where respect is highly valued. 3. Regulatory violations: In tightly controlled industries like banking, healthcare, or politics, the wrong placement can trigger compliance issues. The Gaps in Generic Brand Safety Solutions Most traditional media brand safety tools use a limited set of predefined categories to identify brand safe or unsafe content such as: Adult or explicit content Violence and graphic imagery Hate speech Political or religious extremism While these categories are essential, they represent only a fraction of the risks brands face in culturally diverse regions. These frameworks fail to capture the regional nuances of local language, culture, and context. And as a result, brands unintentionally end up endorsing unsafe content, damaging trust and ROI. Here’s what generic media brand safety tools often miss: Politically charged regional narratives that are highly sensitive during local election cycles. Culturally inappropriate use of colors, symbols, or metaphors, which may have specific religious or social implications. Localized hate speech or community-specific terms, expressed in vernacular languages or dialects outside the scope of English-only keyword lists. Subtle cues in satire, memes, or slang that convey offensive or divisive undertones but are invisible to global classifiers. This not only exposes brands to reputational harm but also creates the perception that they are indirectly funding harmful narratives. Over time, such misplacements erode customer trust and weaken brand credibility in markets where cultural sensitivity is non-negotiable. This is why the industry needs to shift from generic brand safety to regional intelligence. The Shift Toward Regional Intelligence The digital landscape is evolving fast, and brand safety must evolve with it. The shift is clear – from generic filters to regional intelligence. Regional intelligence in brand safety means embedding cultural, linguistic, and contextual

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Managing Ads Across Multiple Ecommerce Marketplaces

How a Unified Platform Cuts Hidden Costs of Ads Across Ecommerce Marketplaces

Blog, Digital Shelf Analytics /

Aditya was running a festive campaign for his brand on top eCommerce marketplaces and quick commerce platforms. He sets the bid for a specific keyword, schedules the campaigns, and goes to sleep.  Meanwhile, their competitors reduce the bid cost and get a better position than them. Till the time he sees that and optimizes his campaigns, his competitors have captured the eyeballs.  And in addition to it, he is struggling to keep an eye on all the platforms at the same time.   During peak season time, brands cannot take the risk of losing visibility. But managing cross-platform campaigns manually is like floating on two boats like Aditya. Your human eye will definitely miss something.   This is the hidden cost of managing ads across multiple marketplaces separately.  So, now the question is – How should a performance manager manage ads across Amazon, Flipkart, Blinkit, and others without logging into 5 different dashboards?  Let’s find that out.  In this article, we will talk about:  The inefficiencies of managing ads manually across different platforms.   Why manual campaign creation, monitoring, and reporting are no longer enough in today’s competitive landscape.  How a unified ad manager simplifies complexity by bringing everything into one dashboard.  The role of AI and automation in making ad management smarter, faster, and more efficient.  The Hidden Inefficiencies of Managing Cross-Platform Campaigns Manually Every ecommerce marketplace has its own advertising platform with unique dashboards and reporting methods. Handling 2-3 campaigns across these ad managers might seem like a manageable task. But as the number of your campaigns grows and with increased competition, the manual efforts become inefficient. And the cracks begin to show:  Time drain: Constantly switching between platforms to check performance and make optimizations wastes hours that can be spent on strategy.  Data silos: It gets difficult to get a clear, unified picture of overall marketing spend and ROI, with insights locked inside separate dashboards.  Slow response times: Marketplaces are dynamic. Bids change, competitors adjust pricing, and inventory fluctuates quickly. Relying on manual monitoring means you’re often reacting too late.  Higher risk of errors: Fragmented management increases the chances of overspending, duplicate targeting, or misaligned campaigns, all of which directly impact profitability.  Reporting headaches: Each platform has its own format and metrics. Creating consolidated reports means extra manual work, often leading to inconsistencies or overlooked insights.  Missed growth opportunities: When campaigns are managed in isolation, you can’t easily see cross-market patterns, like whether Amazon campaigns are outperforming Flipkart, or if a product trending on Blinkit could be pushed more on other platforms.  Guesswork in bid adjustments: Without consolidated insights, marketers often rely on trial-and-error when setting bids. This guesswork leads to overspending in some areas while underfunding campaigns that could actually deliver better results.  Therefore, manual ad campaign management methods fail to keep up with the speed, complexity, and interconnectedness of the rapidly growing ecommerce space. Advertisers now need to move towards a smarter, unified system that not only tracks campaigns across platforms but also provides real-time, actionable ecommerce analytics as well as saves optimization time using AI and automation.  What is a Unified Ad Manager? A Unified Ad Manager is a single platform that allows brands to create, manage, monitor, and optimize their advertising campaigns across multiple ecommerce marketplaces and digital channels from one place. Instead of juggling Amazon, Flipkart, Blinkit, Myntra, or other platforms separately, a unified marketing platform consolidates all campaign data into a centralized dashboard.  This unified approach removes the need to switch between multiple dashboards, download endless reports, or manually reconcile metrics. Brands get advanced ecommerce analytics, a standardized view of ad spend, ROI, keyword performance, and campaign results across platforms, all in one single dashboard.  Benefits of Using a Unified Ad Manager 1. Centralized Campaign Management: Create, manage, and optimize campaigns for multiple marketplaces from one dashboard. This eliminates the need to switch between platforms, saving time and reducing complexity.  2. Smarter Campaign Creation Set up campaigns faster using data-driven insights on budgets, products, and keywords. Bulk campaign creation ensures consistency across platforms while tailoring strategies for individual marketplaces.  3. Real-Time Campaign Modifications Adjust budgets, bids, keywords, and product codes in one place. Updates reflect instantly across platforms, and bulk optimization at once makes scaling effortless.  4. Optimization & Bid Management Improve performance with dynamic bid adjustments, budget reallocations, and automated dayparting. The platform even auto-pauses campaigns for out-of-stock products, ensuring ad spend isn’t wasted.  5. AI-Powered Rule Engine Use of AI-based ecommerce analytics helps apply smart rules to optimize campaigns automatically. From adjusting bids to reallocating budgets, AI triggers ensure campaigns remain competitive without constant manual oversight.  6. Integrated Digital Shelf Analytics Track keyword share of search, monitor category visibility, and measure competitor rankings. This integration bridges ad performance with digital shelf presence for a complete view.  7. Budget Management & Pacing Spreads ad spends across peak hours with automated pacing. The platform also provides instant alerts on low balances and intelligently shuffles budgets for maximum efficiency.  8. Deep Insights & Reporting Access a global Power BI dashboard with detailed insights on platform, brand, keyword, or product. This includes availability, ratings and reviews, and share-of-search, making decisions more data-driven.  9. Transparency Through Logs Every change, from bid updates to rule executions, is tracked in an activity log. This provides clarity, accountability, and a clear audit trail.  10. Better Outcomes at Scale By simplifying ad management, reducing manual effort, and applying automation, brands achieve higher ROAS, fewer errors, and continuous performance improvement.  How AI & Automation Help in Advanced Ad Campaign Management Unified ad manager solves the problem of fragmentation, but by leveraging AI-based ecommerce analytics, brands can move beyond visibility. AI brings the power of automation to everyday ad campaign management. Here’s how:  Smart budget allocation: Instead of manually deciding how much to spend on each marketplace, AI shifts budgets toward platforms and campaigns based on real time competitor insights delivering the best ROI.  Automated bid adjustments: Bids update in real-time to stay competitive, saving you from hours of manual tweaks. 

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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

Blog, Affiliate /

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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